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17Jan

Salesforce Foundations

We are excited that Agentforce Service Agents are now live! Agentforce Service Agent is the autonomous conversational AI assistant to help your customers with their service and support needs. What does this mean for Foundations Customers?Salesforce Foundations is required for all customers in order to try or buy Agentforce. Additionally, customers who have Foundations can try Agentforce Agents for free with a limited number of credits to test a use case or deploy a proof of concept. Salesforce Foundations is not a product or add-on. It’s a multi-cloud feature set that will be added to Sales and Service Cloud — no integration needed, with no additional upfront cost for our customers. It includes foundational features from Sales, Service, Marketing, Commerce, and Data Cloud. Salesforce Foundations provides a 360-degree view of your customer relationships across sales, service, marketing, and commerce through integrated applications and unified data. It also boosts productivity with streamlined, visually friendly user interface improvements, that you can turn on or off per your requirements. If you’re a Salesforce Sales Cloud or Service Cloud customer, you’ve become accustomed to the power, convenience, and full-featured functionality of our trusted CRM. Adding the additional functionality and engagement capabilities of a new Salesforce Cloud is exciting, but it’s also a big change for your organization to consider when you’re not sure about the value it brings. So, what if you could use essential features in the most popular Salesforce Clouds and turn them on when you’re ready? Now you can with Salesforce Foundations. Salesforce Foundations is a new, no-cost addition to your existing CRM that equips you to expand your business reach. The suite gives Salesforce customers on Enterprise, Unlimited, and Einstein 1 editions the power of Data Cloud, and access to essential Salesforce sales, service, Agentforce, marketing, and commerce capabilities. This suite is built into your existing CRM, and provides new functionality to give you a more robust 360-degree view of your customers. This chart shows the Salesforce Foundations features you get with your current Sales Cloud or Service Cloud package. You get Sales for Salesforce Foundations You get Service for Salesforce Foundations You get Marketing for Salesforce Foundations You get Commerce for Salesforce Foundations You get Data Cloud for Salesforce Foundations You get Agentforce for Salesforce Foundations If you already have Sales Cloud * Yes Yes Yes Yes Yes If you already have Service Cloud Yes * Yes Yes Yes Yes If you already have Sales & Service Clouds * * Yes Yes Yes Yes *Your current Salesforce product. Benefits of Salesforce Foundations The features you get with Salesforce Foundations open doors to all sorts of new ways your teams can work more efficiently and engage with your customers on a more personal level. The benefits listed below are only a few of the ways Salesforce Foundations can help your business grow and thrive. Check out Discover Salesforce Foundations to see the full list of capabilities included with Salesforce Foundations. With Salesforce Foundations, your organization benefits from: Sales features that help you take care of your entire sales pipeline, from prospecting to closing. You can manage your leads, opportunities, accounts, and contacts in the preconfigured Sales Console. Service features that make it easy to provide proactive, personalized support to your customers through the preconfigured Service Console. Omni-channel case routing makes sure the most qualified agents work each case, Knowledge Management helps agents provide accurate and relevant help articles to customers, and macros help agents complete repetitive tasks with a single click. Agentforce brings the power of conversational AI to your business. Try out an intelligent, trusted, and customizable AI agent and help your users get more done with Salesforce. Agentforce’s autonomous apps use LLMs and context to assist customers and human agents. Marketing features that allow you to join data from disparate sources, better understand and analyze your customers, and choose how to connect with your audiences. You can create customized marketing campaigns powered by Salesforce Flows to send at the right time. Commerce features that help boost sales with a Direct to Customer (D2C) online storefront. You can define customer experiences like search, carts, and checkout. Pay Now lets you generate secure payment links for customers when opportunities close, so you get paid faster. Data Cloud functionality that creates unified profiles by aggregating data from all of your data sources into a single view so you can better understand your customers. Create customer segments to more accurately target campaigns, analyze your customers, and manage consent data. Data Cloud also powers features so you can send online store order confirmation emails and marketing messages. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 17, 2025in Data, Enterprise, Salesforce, Salesforce Flow, Salesforce Foundations, Salesforce Sales Cloud0 Comments

14Jan

On Premise Gen AI

In 2025, enterprises transitioning generative AI (GenAI) into production after years of experimentation are increasingly considering on-premises deployment as a cost-effective alternative to the cloud. Since OpenAI ignited the AI revolution in late 2022, organizations have tested large language models powering GenAI services on platforms like AWS, Microsoft Azure, and Google Cloud. These experiments demonstrated GenAI’s potential to enhance business operations while exposing the substantial costs of cloud usage. To avoid difficult conversations with CFOs about escalating cloud expenses, CIOs are exploring on-premises AI as a financially viable solution. Advances in software from startups and packaged infrastructure from vendors such as HPE and Dell are making private data centers an attractive option for managing costs. A survey conducted by Menlo Ventures in late 2024 found that 47% of U.S. enterprises with at least 50 employees were developing GenAI solutions in-house. Similarly, Informa TechTarget’s Enterprise Strategy Group reported a rise in enterprises considering on-premises and public cloud equally for new applications—from 37% in 2024 to 45% in 2025. This shift is reflected in hardware sales. HPE reported a 16% revenue increase in AI systems, reaching $1.5 billion in Q4 2024. During the same period, Dell recorded a record $3.6 billion in AI server orders, with its sales pipeline expanding by over 50% across various customer segments. “Customers are seeking diverse AI-capable server solutions,” noted David Schmidt, senior director of Dell’s PowerEdge server line. While heavily regulated industries have traditionally relied on on-premises systems to ensure data privacy and security, broader adoption is now driven by the need for cost control. Fortune 2000 companies are leading this trend, opting for private infrastructure over the cloud due to more predictable expenses. “It’s not unusual to see cloud bills exceeding 0,000 or even million per month,” said John Annand, an analyst at Info-Tech Research Group. Global manufacturing giant Jabil primarily uses AWS for GenAI development but emphasizes ongoing cost management. “Does moving to the cloud provide a cost advantage? Sometimes it doesn’t,” said CIO May Yap. Jabil employs a continuous cloud financial optimization process to maximize efficiency. On-Premises AI: Technology and Trends Enterprises now have alternatives to cloud infrastructure, including as-a-service solutions like Dell APEX and HPE GreenLake, which offer flexible pay-per-use pricing for AI servers, storage, and networking tailored for private data centers or colocation facilities. “The high cost of cloud drives organizations to seek more predictable expenses,” said Tiffany Osias, vice president of global colocation services at Equinix. Walmart exemplifies in-house AI development, creating tools like a document summarization app for its benefits help desk and an AI assistant for corporate employees. Startups are also enabling enterprises to build AI applications with turnkey solutions. “About 80% of GenAI requirements can now be addressed with push-button solutions from startups,” said Tim Tully, partner at Menlo Ventures. Companies like Ragie (RAG-as-a-service) and Lamatic.ai (GenAI platform-as-a-service) are driving this innovation. Others, like Squid AI, integrate custom AI agents with existing enterprise infrastructure. Open-source frameworks like LangChain further empower on-premises development, offering tools for creating chatbots, virtual assistants, and intelligent search systems. Its extension, LangGraph, adds functionality for building multi-agent workflows. As enterprises develop AI applications internally, consulting services will play a pivotal role. “Companies offering guidance on effective AI tool usage and aligning them with business outcomes will thrive,” Annand said. This evolution in AI deployment highlights the growing importance of balancing technological innovation with financial sustainability. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 14, 2025in Data, Enterprise, Generative AI, Google, Technology0 Comments

12Jan

Amazon Q Business

Amazon Q Business: Revolutionizing Enterprise Productivity with Generative AI and Plugins Amazon Q Business is a generative AI-powered assistant that empowers employees by solving problems, generating content, and offering actionable insights from across enterprise data sources. In addition to its robust search capabilities across indexed third-party services, Amazon Q Business enables real-time access to dynamic data like stock prices, vacation balances, and location tracking through its plugins. These plugins also allow employees to perform direct actions—such as prioritizing service tickets—within enterprise applications, all through a single interface. This eliminates the need to toggle between systems, saving valuable time and increasing productivity. This insight delves into how Amazon Q Business plugins seamlessly integrate with enterprise applications through built-in and custom configurations. We’ll explore: Simplifying Enterprise Tasks with Plugins Amazon Q Business enables users to access non-indexed data—such as calendar availability, stock prices, or PTO balances—and execute actions like booking a meeting or submitting PTO using services like Jira, ServiceNow, Salesforce, Fidelity, Vanguard, ADP, Workday, and Google Calendar. This unified approach streamlines workflows and minimizes reliance on multiple apps for task completion. Solution Overview Amazon Q Business connects to over 50 enterprise applications using connectors and plugins: Plugins are categorized into two types: Built-in Plugins Amazon Q Business supports more than 50 actions across applications: Category Application Sample Actions Ticketing ServiceNow Create, update, delete tickets Zendesk Suite Search, create, update tickets Project Management Jira Cloud Read, create, update, delete issues Smartsheet Search and manage sheets and reports CRM Salesforce Manage accounts, opportunities, and cases Communication Microsoft Teams Send private or channel messages Productivity Google Calendar Find events, list calendars Salesforce Plugin Example The Salesforce plugin allows users to: Configuration Steps: Custom Plugins For scenarios not covered by built-in plugins, custom plugins enable seamless integration with proprietary systems. For example: HR Time Off Plugin Example This plugin allows employees to: Setup Steps: End-to-End Use Cases 1. Salesforce Integration Sam, a Customer Success Manager, retrieves high-value opportunities using the Salesforce plugin. She creates a new case directly from the Amazon Q interface, enhancing efficiency by reducing application switching. 2. ServiceNow Ticket Management Sam uses Amazon Q Business to resolve a laptop email sync issue. After referencing indexed IT documentation, she creates a ServiceNow ticket and escalates it directly through the plugin interface. 3. HR System Integration Sam checks her PTO balance and submits a vacation request using the HR Time Off custom plugin, ensuring seamless task completion without switching to another app. Impact on Workflow Efficiency Amazon Q Business plugins simplify workflows by: Conclusion Amazon Q Business plugins represent a transformative step in automating enterprise workflows and enhancing employee productivity. From preconfigured integrations to custom-built solutions, these plugins provide unparalleled flexibility to adapt to diverse business needs. How can Amazon Q Business transform workflows in your organization? Whether through built-in integrations or custom solutions, explore the power of Amazon Q Business plugins to unlock new levels of efficiency. Share your feedback and use cases to inspire innovation across enterprises! Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 12, 2025in Data, Enterprise, Generative AI, Google, Salesforce0 Comments

Salesforce and AWS-Agentic Enterprise

Salesforce and AWS: Driving the Future of the Agentic Enterprise As AI-powered agents redefine the way businesses operate, strategic partnerships are playing a pivotal role in harnessing the power of data and artificial intelligence. Salesforce and AWS, two industry leaders, have taken significant steps toward building a smarter, agentic enterprise through their expanded collaboration. One year into this strategic partnership, their joint efforts are delivering transformative AI and data solutions, helping customers like Buyers Edge Platform unlock new efficiencies and capabilities. A Partnership Fueling Agentic AI Salesforce and AWS are aligning their AI and data initiatives to pave the way for advanced agentic systems—autonomous AI agents designed to enhance business operations and customer experiences. Among their notable achievements over the past year are: These innovations are creating an ecosystem that supports the delivery of agentic AI, enabling businesses to streamline operations and tap into new value from their data. “By integrating data and AI capabilities across our platforms, Salesforce and AWS are building a strong foundation for the future of agentic systems,” said Brian Landsman, EVP of Global Business Development and Technology Partnerships at Salesforce. “With a majority of large companies planning to implement agents by 2027, organizations need trusted partners to help them achieve their vision of a smarter enterprise.” Making AI More Accessible Salesforce is simplifying access to AI technology through the AWS Marketplace, offering customers an integrated solution that includes Agentforce—the agentic layer of the Salesforce platform. Agentforce enables businesses to deploy autonomous AI agents across various operations, streamlining workflows and delivering measurable results. Available in 23 countries, Salesforce’s presence on AWS Marketplace offers customers key advantages, including: By removing barriers to adoption, Salesforce and AWS empower companies to focus on leveraging technology for growth rather than navigating complex procurement systems. A New Era of Enterprise Efficiency As businesses increasingly rely on data and AI to remain competitive, the Salesforce-AWS partnership is setting the stage for enterprises to achieve more with agentic systems. These systems allow companies to execute complex tasks with unprecedented efficiency, maximizing ROI on technology investments. “Our partnership with Salesforce empowers mutual customers to realize the full potential of their data and AI investments,” said Chris Grusz, Managing Director of Technology Partnerships at AWS. “Together, we’re delivering immediate, actionable insights with agentic AI, enabling organizations to automate strategically and unlock more value across their operations.” Looking Ahead By seamlessly integrating data and AI capabilities, Salesforce and AWS are not just building technology solutions—they’re reshaping how enterprises operate and thrive in the digital age. As agentic AI becomes an essential part of business strategy, this partnership provides a blueprint for leveraging technology to drive smarter, more agile, and more effective enterprises. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 11, 2025in Artificial Intelligence, Data, Enterprise, Salesforce, Salesforce Data Cloud, Technology0 Comments

Autonomy, Architecture, and Action

Redefining AI Agents: Autonomy, Architecture, and Action AI agents are reshaping how technology interacts with us and executes tasks. Their mission? To reason, plan, and act independently—following instructions, making autonomous decisions, and completing actions, often without user involvement. These agents adapt to new information, adjust in real time, and pursue their objectives autonomously. This evolution in agentic AI is revolutionizing how goals are accomplished, ushering in a future of semi-autonomous technology. At their foundation, AI agents rely on one or more large language models (LLMs). However, designing agents is far more intricate than building chatbots or generative assistants. While traditional AI applications often depend on user-driven inputs—such as prompt engineering or active supervision—agents operate autonomously. Core Principles of Agentic AI Architectures To enable autonomous functionality, agentic AI systems must incorporate: Essential Infrastructure for AI Agents Building and deploying agentic AI systems requires robust software infrastructure that supports: Agent Development Made Easier with Langflow and Astra DB Langflow simplifies the development of agentic applications with its visual IDE. It integrates with Astra DB, which combines vector and graph capabilities for ultra-low latency data access. This synergy accelerates development by enabling: Transforming Autonomy into Action Agentic AI is fundamentally changing how tasks are executed by empowering systems to act autonomously. By leveraging platforms like Astra DB and Langflow, organizations can simplify agent design and deploy scalable, effective AI applications. Start building the next generation of AI-powered autonomy today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 11, 2025in Agentic AI, Data, Enterprise, Technology0 Comments

Project Management With Asana and Salesforce

10Jan

Salesforce and Asana Integration Approach

How to Integrate Asana and Salesforce: A Complete Guide Table of Contents Integrating Asana and Salesforce can eliminate workflow silos and accelerate collaboration. Both platforms offer integration capabilities, but their suitability varies based on your needs and resources. This guide will help you navigate the options, evaluate their pros and cons, and choose the one that best suits your organization. Can You Integrate Asana and Salesforce? Yes! Asana and Salesforce integration is possible through three primary methods: Each option comes with unique features, costs, and technical requirements. This guide explores each solution to help you make an informed decision. Why Integrate Asana and Salesforce? Integration can achieve two major goals: Depending on your goals, certain integration methods may be better suited to your needs. Integration Options Overview 1. Asana for Salesforce This official integration is ideal for large organizations with Enterprise-level plans for both Asana and Salesforce. It enables automation of workflows between the two platforms, such as: Pros: Cons: Rating: 2.6/5 on Salesforce AppExchange. 2. Visor Visor offers bi-directional integration with Asana and Salesforce, making it a powerful choice for combining and visualizing data. Key Features: Best For: Setup Steps: Limitations: 3. Zapier Zapier enables custom automation between Asana and Salesforce. It’s perfect for automating simple, repetitive workflows, such as: Pros: Cons: Quick Comparison Table Feature Asana for Salesforce Zapier Visor Automates processes ✔ ✔ ✘ Combines Salesforce & Asana data ✘ ✘ ✔ Gantt charts and project boards ✘ ✘ ✔ Dashboards and timelines ✘ ✘ ✔ Two-way data sync ✘ ✘ ✔ Comparison Table Which Integration Option Is Best for You? The right choice depends on your goals: Get Started with Visor for Free Visor is one integration tool, that helps you bridge the gap between Asana and Salesforce, offering advanced visualization tools and seamless collaboration. Start using Visor for free today: Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 10, 2025in Data, Enterprise, Salesforce0 Comments

08Jan

A Revolution in Enterprise AI

Salesforce Unveils Agentforce 2.0: A Revolution in Enterprise AI Salesforce has launched Agentforce 2.0, a cutting-edge update poised to redefine how enterprises design, deploy, and manage AI-driven solutions. With a suite of innovative features, this upgrade emphasizes seamless collaboration, enhanced integration, and unprecedented flexibility in creating AI-powered workflows. Agentforce 2.0 focuses on three core advancements: headless agents for programmatic control, deep Slack integration for streamlined teamwork, and a revamped API-driven architecture that simplifies development and deployment. Core Highlights of Agentforce 2.0 1. Enhanced Integration Architecture Agentforce 2.0 introduces a sophisticated integration framework designed to streamline workflows and accelerate development. By leveraging MuleSoft for Flow, it provides 40 pre-built connectors for seamless integration with enterprise systems. At the heart of this architecture is the API Catalog, a centralized hub for discovering, managing, and optimizing APIs within Salesforce. The Topic Center simplifies deployment by embedding Agentforce metadata into API design workflows, minimizing manual configurations and reducing time-to-market. Key features of the API Catalog include: This API-first approach empowers DevOps teams to manage and optimize AI capabilities efficiently through a single interface. 2. Upgraded Atlas Reasoning Engine The Atlas Reasoning Engine takes enterprise AI capabilities to the next level, enabling smarter and more effective AI-driven operations. Key enhancements include: Preliminary testing shows a 33% improvement in response accuracy and a doubling of relevance in complex scenarios compared to previous models. The engine uniquely combines System 1 reasoning (fast, intuitive responses) with System 2 reasoning (deep analytical processing), setting a new benchmark for enterprise AI intelligence. 3. Headless Agents for Greater Control A game-changing feature of Agentforce 2.0 is the introduction of headless agents, which operate autonomously without requiring direct user interaction. Key capabilities include: This feature enables enterprises to build robust, autonomous workflows, making Agentforce 2.0 an indispensable tool for optimizing digital operations. 4. Deep Slack Integration Agentforce 2.0 seamlessly integrates AI with Slack, Salesforce’s collaboration platform, fostering real-time, AI-enhanced teamwork. Technical advancements include: By embedding AI agents directly into Slack, teams can break down silos, enabling smoother collaboration and faster decision-making across departments. 5. Data Cloud Integration Agentforce 2.0 leverages Salesforce’s Data Cloud to enhance data accessibility and intelligence. Key features include: This integration ensures that AI agents can provide real-time, actionable insights by tapping into a comprehensive, unified data ecosystem. Final Thoughts Agentforce 2.0 represents a transformative leap in enterprise AI, combining cutting-edge technologies like headless agents, deep Slack integration, and an advanced API-driven architecture. By empowering organizations to create intelligent, autonomous workflows, Agentforce 2.0 sets a new standard for AI innovation in the enterprise sector. With its ability to streamline collaboration, optimize operations, and unlock new levels of productivity, Agentforce 2.0 positions Salesforce as a leader in the evolving AI landscape, helping businesses stay ahead in the digital age. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 8, 2025in Data, Enterprise, Mulesoft, Salesforce0 Comments

07Jan

Why Choose Salesforce as Your Mortgage CRM?

Centralized Data Storage & Management Salesforce Mortgage CRM consolidates all your mortgage data into a single platform, offering a unified view of client information, loan details, and transaction history. This eliminates the confusion of scattered data, ensuring brokers have quick access to crucial information. For instance, if a client calls with questions about their loan, brokers can immediately retrieve accurate details, enhancing trust and improving the client experience. Accurate Loan Forecasting With AI-driven data analytics, Salesforce provides actionable insights into future loan opportunities, potential risks, and projected income. By analyzing historical data, brokers can predict client behavior, such as the likelihood of refinancing. This proactive approach allows brokers to deliver tailored offers, increasing conversions and client satisfaction. Seamless Collaboration & Secure Data Sharing Effective communication within an organization is essential, and Salesforce Mortgage CRM excels at connecting team members across locations and devices. Features like document management ensure efficient workflows through version control, rights management, and advanced search capabilities. Brokers can also share select records or documents securely with external stakeholders by granting limited access, ensuring confidentiality while streamlining the lending process. Top-Notch Security Salesforce Mortgage CRM prioritizes data security with multi-level protocols, including multi-factor authentication, data encryption, 24/7 monitoring, and an advanced Trust Layer. These features ensure that sensitive client information, such as financial and personal data, is safeguarded, fostering confidence among potential borrowers. Personalized Client Interactions Every client’s journey is unique, and Salesforce empowers brokers to deliver personalized experiences. For example, if a client’s fixed-rate term is nearing its end, Salesforce can automate outreach with refinancing options. This level of personalization improves client satisfaction and strengthens retention strategies. In-Depth Analytics and Visualization Salesforce offers robust analytics tools to provide mortgage professionals with insights into client behavior, market trends, operational performance, and risk factors. Interactive dashboards and customizable reports enable brokers to visualize metrics like loan-to-value ratios, debt-to-income ratios, and delinquency rates. These insights help streamline operations, improve profitability, and mitigate risks. Automation and AI-Powered Assistance Salesforce integrates cutting-edge AI tools to automate routine tasks, segment clients, and deliver tailored recommendations. Brokers can use these tools to identify refinancing opportunities, streamline workflows, and increase efficiency. While advanced AI features may require premium subscriptions, Salesforce also provides no-code automation capabilities. Tools like Salesforce Flow allow users to create automated workflows for tasks such as data entry, follow-ups, and approvals. For complex workflows, Flow Orchestrator enables brokers to coordinate multi-step processes seamlessly. These automation features eliminate manual tasks, freeing brokers to focus on high-value activities. Streamline Your Lending Process with Salesforce Mortgage CRM Whether you’re looking to centralize your data, enhance client relationships, or improve operational efficiency, Salesforce Mortgage CRM offers a comprehensive solution. Its combination of AI, analytics, and automation ensures that your team can work smarter, not harder. Ready to transform your mortgage business? Let Salesforce help you achieve greater efficiency and client satisfaction today. Unlock the Full Potential of Mortgage Lending with Salesforce Mortgage CRM Automation Without AI Salesforce Mortgage CRM streamlines repetitive tasks through its no-code automation capabilities, removing the need for AI. Salesforce Flow allows brokers to create automated workflows triggered by specific events, such as follow-up tasks, reminders, or status updates. For more intricate workflows, Flow Orchestrator provides seamless coordination for multi-step processes, including approvals, ensuring a smooth lending experience. Whether sending monthly statements or routing documents between stakeholders in the approval process, Salesforce Mortgage CRM automates these tasks based on your predefined rules. For enterprises, Financial Services Cloud (FSC) offers pre-built templates to manage mortgage applications. For SMBs, building tailored flows from scratch can be a more efficient and cost-effective solution, offering greater customization without overpaying for unused FSC features. An excellent example of Salesforce’s versatility is integrating scheduling tools like Calendly with borrower portals built in Experience Cloud. These portals allow clients to book appointments while considering time zone differences and send automated reminders, ensuring seamless borrower engagement. Platform Customization and Scalability Salesforce is an agile platform that adapts to your business needs. Need custom fields for underwriting criteria? A new object to track loan pipeline opportunities? Or automated workflows to manage approvals? Salesforce’s intuitive point-and-click configuration tools empower you to customize your system without complex coding, making it a perfect fit for businesses of any size. Seamless Integration with Third-Party Tools Salesforce’s vast ecosystem, powered by the AppExchange, offers over 7,000 add-ons to enhance your CRM’s functionality. From digital signature solutions to mortgage rate comparison tools, these integrations eliminate the need for extensive custom development. If your unique needs aren’t met by existing options, Salesforce’s certified AppExchange partners can help create tailored solutions. Salesforce Products Tailored for Mortgage Lending Firms 1. Financial Services Cloud (FSC) FSC is purpose-built for the financial services industry, including mortgage lending. It provides a 360-degree view of clients, integrating their financial holdings, activities, and loan details. With FSC, lenders can offer personalized recommendations, streamline the underwriting process, and stay compliant with industry regulations using built-in risk management tools. 2. Marketing Cloud Account Engagement (Pardot) Pardot empowers lenders to engage potential borrowers effectively. For example, a mortgage firm targeting first-time homebuyers can use Pardot to create automated, personalized email campaigns, nurturing leads with tailored content about loans, interest rates, and homebuying tips.Real-time insights and Einstein-powered predictive lead scoring help mortgage professionals prioritize high-value leads and track engagement through detailed campaign performance metrics, such as Multi-Touch Attribution Reports. 3. Experience Cloud For mortgage firms looking to provide a self-service option, Experience Cloud allows for building custom portals and websites. Borrowers can use these portals to upload documents, track application statuses, and access loan details. The drag-and-drop design tools and pre-built templates make it easy to create branded, user-friendly interfaces without requiring extensive coding. 4. Service Cloud Customer service is critical in the mortgage process, and Salesforce Service Cloud enhances this experience with omnichannel support across email, chat, and phone. Borrowers can quickly get answers to questions about their applications, while automation retrieves and shares relevant data instantly. This improves response times, reduces manual effort, and ensures borrowers receive

January 7, 2025in AI Tools, Data, Enterprise, Salesforce, Salesforce Development Services, Salesforce Experience Cloud, Salesforce Financial Services Solutions, Salesforce Flow, Salesforce Marketing Cloud, Salesforce Service Cloud0 Comments

07Jan

Exploring Generative AI

Like most employees at most companies, I wear a few different hats around Tectonic. Whether I’m building a data model, creating and scheduing an email campaign, standing up a platform generative AI is always at my fingertips. At my very core, I’m a marketer. Have been for so long I do it without eveven thinking. Or at least, everyuthing I do has a hat tip to its future marketing needs. Today I want to share some of the AI content generators I’ve been using, am looking to use, or just heard about. But before we rip into the insight, here’s a primer. Types of AI Content Generators ChatGPT, a powerful AI chatbot, drew significant attention upon its November 2022 release. While the GPT-3 language model behind it had existed for some time, ChatGPT made this technology accessible to nontechnical users, showcasing how AI can generate content. Over two years later, numerous AI content generators have emerged to cater to diverse use cases. This rapid development raises questions about the technology’s impact on work. Schools are grappling with fears of plagiarism, while others are embracing AI. Legal debates about copyright and digital media authenticity continue. President Joe Biden’s October 2023 executive order addressed AI’s risks and opportunities in areas like education, workforce, and consumer privacy, underscoring generative AI’s transformative potential. What is AI-Generated Content? AI-generated content, also known as generative AI, refers to algorithms that automatically create new content across digital media. These algorithms are trained on extensive datasets and require minimal user input to produce novel outputs. For instance, ChatGPT sets a standard for AI-generated content. Based on GPT-4o, it processes text, images, and audio, offering natural language and multimodal capabilities. Many other generative AI tools operate similarly, leveraging large language models (LLMs) and multimodal frameworks to create diverse outputs. What are the Different Types of AI-Generated Content? AI-generated content spans multiple media types: Despite their varied outputs, most generative AI systems are built on advanced LLMs like GPT-4 and Google Gemini. These multimodal models process and generate content across multiple formats, with enhanced capabilities evolving over time. How Generative AI is Used Generative AI applications span industries: These tools often combine outputs from various media for complex, multifaceted projects. AI Content Generators AI content generators exist across various media. Below are good examples organized by gen ai type: Written Content Generators Image Content Generators Music Content Generators Code Content Generators Other AI Content Generators These tools showcase how AI-powered content generation is revolutionizing industries, making content creation faster and more accessible. I do hope you will comment below on your favorites, other AI tools not showcased above, or anything else AI-related that is on your mind. Written by Tectonic’s Marketing Operations Director, Shannan Hearne. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 7, 2025in AI Tools, Data, Enterprise, Generative AI, Google, Technology0 Comments

04Jan

From Chatbots to Agentic AI

The transition from LLM-powered chatbots to agentic systems, or agentic AI, can be summed up by the old saying: “Less talk, more action.” Keeping up with advancements in AI can be overwhelming, especially when managing an existing business. The speed and complexity of innovation can make it feel like the first day of school all over again. This insight offers a comprehensive look at AI agents, their components, and key characteristics. The introductory section breaks down the elements that form the term “AI agent,” providing a clear definition. After establishing this foundation, we explore the evolution of LLM applications, particularly the shift from traditional chatbots to agentic systems. The goal is to understand why AI agents are becoming increasingly vital in AI development and how they differ from LLM-powered chatbots. By the end of this guide, you will have a deeper understanding of AI agents, their potential applications, and their impact on organizational workflows. For those of you with a technical background who prefer to get hands-on, click here for the best repository for AI developers and builders. What is an AI Agent? Components of AI Agents To understand the term “AI agent,” we need to examine its two main components. First, let’s consider artificial intelligence, or AI. Artificial Intelligence (AI) refers to non-biological intelligence that mimics human cognition to perform tasks traditionally requiring human intellect. Through machine learning and deep learning techniques, algorithms—especially neural networks—learn patterns from data. AI systems are used for tasks such as detection, classification, and prediction, with content generation becoming a prominent domain due to transformer-based models. These systems can match or exceed human performance in specific scenarios. The second component is “agent,” a term commonly used in both technology and human contexts. In computer science, an agent refers to a software entity with environmental awareness, able to perceive and act within its surroundings. A computational agent typically has the ability to: In human contexts, an agent is someone who acts on behalf of another person or organization, making decisions, gathering information, and facilitating interactions. They often play intermediary roles in transactions and decision-making. To define an AI agent, we combine these two perspectives: it is a computational entity with environmental awareness, capable of perceiving inputs, acting with tools, and processing information using foundation models backed by both long-term and short-term memory. Key Components and Characteristics of AI Agents From LLMs to AI Agents Now, let’s take a step back and understand how we arrived at the concept of AI agents, particularly by looking at how LLM applications have evolved. The shift from traditional chatbots to LLM-powered applications has been rapid and transformative. Form Factor Evolution of LLM Applications Traditional Chatbots to LLM-Powered Chatbots Traditional chatbots, which existed before generative AI, were simpler and relied on heuristic responses: “If this, then that.” They followed predefined rules and decision trees to generate responses. These systems had limited interactivity, with the fallback option of “Speak to a human” for complex scenarios. LLM-Powered Chatbots The release of OpenAI’s ChatGPT on November 30, 2022, marked the introduction of LLM-powered chatbots, fundamentally changing the game. These chatbots, like ChatGPT, were built on GPT-3.5, a large language model trained on massive datasets. Unlike traditional chatbots, LLM-powered systems can generate human-like responses, offering a much more flexible and intelligent interaction. However, challenges remained. LLM-powered chatbots struggled with personalization and consistency, often generating plausible but incorrect information—a phenomenon known as “hallucination.” This led to efforts in grounding LLM responses through techniques like retrieval-augmented generation (RAG). RAG Chatbots RAG is a method that combines data retrieval with LLM generation, allowing systems to access real-time or proprietary data, improving accuracy and relevance. This hybrid approach addresses the hallucination problem, ensuring more reliable outputs. LLM-Powered Chatbots to AI Agents As LLMs expanded, their abilities grew more sophisticated, incorporating advanced reasoning, multi-step planning, and the use of external tools (function calling). Tool use refers to an LLM’s ability to invoke specific functions, enabling it to perform more complex tasks. Tool-Augmented LLMs and AI Agents As LLMs became tool-augmented, the emergence of AI agents followed. These agents integrate reasoning, planning, and tool use into an autonomous, goal-driven system that can operate iteratively within a dynamic environment. Unlike traditional chatbot interfaces, AI agents leverage a broader set of tools to interact with various systems and accomplish tasks. Agentic Systems Agentic systems—computational architectures that include AI agents—embody these advanced capabilities. They can autonomously interact with systems, make decisions, and adapt to feedback, forming the foundation for more complex AI applications. Components of an AI Agent AI agents consist of several key components: Characteristics of AI Agents AI agents are defined by the following traits: Conclusion AI agents represent a significant leap from traditional chatbots, offering greater autonomy, complexity, and interactivity. However, the term “AI agent” remains fluid, with no universal industry standard. Instead, it exists on a continuum, with varying degrees of autonomy, adaptability, and proactive behavior defining agentic systems. Value and Impact of AI Agents The key benefits of AI agents lie in their ability to automate manual processes, reduce decision-making burdens, and enhance workflows in enterprise environments. By “agentifying” repetitive tasks, AI agents offer substantial productivity gains and the potential to transform how businesses operate. As AI agents evolve, their applications will only expand, driving new efficiencies and enabling organizations to leverage AI in increasingly sophisticated ways. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 4, 2025in Agentic AI, Artificial Intelligence, Data, Enterprise, Generative AI, Technology0 Comments

04Jan

What is Heroku

What is Heroku? Heroku is a modern, container-based Platform as a Service (PaaS) that enables developers to deploy, manage, and scale applications with ease. Designed for simplicity, flexibility, and elegance, it provides the fastest path for developers to take their apps to market. Key Features of Heroku: The Evolution of Heroku Heroku has recently undergone a transformation, becoming fully cloud-native with advanced integrations like Kubernetes, OpenTelemetry, and Agentforce, an AI-powered enhancement to its platform. These upgrades retain the platform’s hallmark simplicity while delivering more performance and tools, such as Graviton processors, EKS, ECR, and AWS Global Accelerator. AI-Powered Innovation: Agentforce Agentforce, Heroku’s latest feature, brings AI-powered automation to app development. It empowers both technical and non-technical users by offering natural language workflows for building applications, making it accessible to a wider range of business users. According to Betty Junod, Heroku’s Chief Marketing Officer at Salesforce, the platform now seamlessly combines user-friendly experiences with cutting-edge AI capabilities: “We’ve replatformed while keeping the experience as simple as ever, but now with added horsepower, Graviton performance, and managed AI tools like Bedrock.” Agentforce is particularly impactful for non-developers, guiding them through building apps and automating processes with no-code or low-code tools. This innovation aligns with Heroku’s mission to make app creation easier and more interactive: “It’s not just apps serving information anymore; users are engaging with them in entirely new ways.” Deliver Apps, Your Way Heroku is designed to serve a variety of needs, from quick prototypes to mission-critical enterprise applications. Its fully managed ecosystem allows you to build and scale apps efficiently, leveraging the tools and languages you already know and love. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 4, 2025in AI Tools, Data, Enterprise, Salesforce0 Comments

03Jan

Speed to Launch of Agentforce

Agentforce isn’t just another AI platform that requires months of customization. At most customers, they quickly saw its power, launching transformative generative AI experiences in just days—no AI engineers needed. For companies with larger admin teams, the benefits can be even greater. Unlike other platforms, Agentforce places a strong emphasis on data privacy, building on the trust that Salesforce is known for, making these virtual assistants invaluable. We began with employee-facing use cases, saving our team several hours per week. Now, with Agentforce, we’re seeing even more opportunities to drive efficiencies and better serve our customers. “We’re excited to leverage Agentforce to completely overhaul recruitment and enrollment at Unity Environmental University. Instead of traditional forms or chatbots, our students will soon engage with an autonomous recruitment agent directly on our website, offering personalized support throughout the college application process.”– Dr. Melik Khoury, President & CEO, Unity Environmental University “For first-generation college students, the 1:385 coach-to-student ratio makes personalized guidance challenging. By integrating Agentforce into our platform, we’re deploying cutting-edge solutions to better support students. These agents enable our coaches to focus on high-touch, personalized experiences while handling vital tasks like sharing deadlines and answering common questions—24/7.”– Siva Kumari, CEO, College Possible “Agentforce offers organizations a unique opportunity to move beyond incremental improvements and achieve exponential ROI. By automating customer interactions, improving outcomes, and reducing costs, it integrates data, flows, and user interfaces to mitigate risks and accelerate value creation. This agent-based platform approach allows businesses to harness AI’s full potential, revolutionizing customer engagement and paving the way for exponential growth.”– Rebecca Wettemann, CEO and Principal Analyst, Valoir “Autonomous agents powered by Salesforce’s Agentforce are revolutionizing customer experiences by providing fast, accurate, and personalized support around the clock. With advanced AI making decisions and taking actions autonomously, businesses can resolve customer issues more efficiently, fostering deeper interactions and enhancing satisfaction. This innovation enables companies to reallocate human resources to more complex tasks, boosting individual productivity and scaling business growth. Agentforce is setting new standards for seamless sales, service, marketing, and commerce interactions, reinforcing its leadership in customer experience.”– Michael Fauscette, CEO and Chief Analyst, Arion Research LLC “The best way to predict the future is to invent it.” — Alan Kay, Computer Science Pioneer Technology progresses in what biologists call punctuated equilibrium, with new capabilities slowly emerging from labs and tinkerers until a breakthrough shifts the axis of possibility. These pioneering feats create new paradigms, unleashing waves of innovation—much like the Apple Macintosh, the iPhone, and the Salesforce Platform, which revolutionized the enterprise software-as-a-service (SaaS) model and sparked an entire industry. The Age of Agentforce Begins At Dreamforce 2024, Salesforce Futures reflected on the launch of Agentforce, inspired by visions like the Apple Knowledge Navigator. In 2023, we used this inspiration to craft our Salesforce 2030 film, which showcased the collaboration between humans and autonomous AI agents. Now, with Agentforce, we’re witnessing that vision come to life. Agentforce is a suite of customizable AI agents and tools built on the Salesforce Platform, offering an elegant solution to the complexity of AI deployment. It addresses the challenges of integrating data, models, infrastructure, and applications into a unified system. With powerful tools like Agent Builder and Model Builder, organizations can easily create, customize, and deploy AI agents. Salesforce’s Atlas Reasoning Engine empowers these agents to handle both routine and complex tasks autonomously. A New Era of AI Innovation At Dreamforce 2024, over 10,000 attendees raced to build their own agents using the “Agent Builder” experience, turning verbal instructions into fully functioning agents in under 15 minutes. This wasn’t just another chatbot—it’s a new breed of AI that could transform how businesses operate and deliver superior customer experiences. Companies like Saks, OpenTable, and Wiley have quickly embraced this technology. As Mick Costigan and David Berthy of Salesforce Futures explain, “When we see signals like this, it pushes us toward the future. Soon, we’ll see complex, multi-agent systems solving higher-order challenges, both in the enterprise and in consumer devices.” Shaping the Future Agentforce isn’t just a product—it’s a platform for experimentation. With hundreds of thousands of Salesforce customers soon gaining access, the full potential of these tools will unfold in ways we can’t yet imagine. As with every major technological shift, the real magic will lie in how people use it. Every interaction, every agent deployed, and every problem solved will shape the future in unexpected ways. Platform Evolution Adam Evans, Salesforce SVP of Product, notes that Agentforce builds on the company’s transformation over the past four years, following the pattern of Salesforce’s original disruption of enterprise software. Unlike traditional solutions, Agentforce eliminates the need for customers to build their own AI infrastructure, providing a ready-to-use solution. At the core of Agentforce is the Atlas Reasoning Engine, delivering results that are twice as relevant and 33% more accurate than competing solutions. This engine integrates Salesforce Data Cloud, Flow for automation, and the Einstein Trust Layer for governance. Early Customer Results Early Agentforce deployments highlight how organizations are using autonomous agents to enhance, rather than replace, human workers: George Pokorny, Senior VP of Global Customer Success at OpenTable, shared, “Just saving two minutes on a ten-minute call lets our service reps focus on strengthening customer relationships, thanks to seamless integration with Service Cloud, giving us a unified view of diner preferences and history.” Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 3, 2025in Agentforce Platform, Data, Enterprise, Generative AI, Salesforce, Salesforce Data Cloud, Technology0 Comments

The Subscription Economy

The Subscription Economy: A $1.5 Trillion Opportunity by 2025The subscription economy has expanded by 435% over the last decade and is projected to reach a staggering $1.5 trillion market size by 2025, cementing its status as a dominant business model. Companies leveraging subscription and servitization strategies are unlocking consistent revenue streams and delivering tailored services that foster customer loyalty and satisfaction. The Challenge of Managing RenewalsWhile the subscription economy thrives, managing renewals effectively remains a critical challenge. Without a robust system, businesses risk: This is where Salesforce CPQ (Configure, Price, Quote) becomes essential. It not only automates the renewal process but also empowers businesses to deliver accurate, timely, and personalized renewal experiences. The Role of Salesforce CPQ in Renewal ManagementSalesforce CPQ streamlines the renewal process by automating workflows, ensuring pricing accuracy, and creating personalized customer experiences. Key benefits include: With Salesforce CPQ, renewals become a strategic opportunity to retain customers, drive revenue growth, and deliver exceptional service. The Importance of Renewal Metrics Tracking the right renewal metrics is crucial for understanding performance and identifying areas for improvement. These metrics provide actionable insights that drive better customer retention and revenue growth. 1. Renewal Rate 2. Churn Rate 3. Renewal Revenue 4. Net Revenue Retention (NRR) 5. Customer Lifetime Value (CLV) 6. Time to Renewal (TTR) 7. Renewal Upsell Rate 8. Renewal Discount Utilization Enhancing Renewal Metrics with Salesforce CPQ Salesforce CPQ transforms how you track and manage renewal metrics through automation, analytics, and workflow optimization. Here’s how: 1. Automate Renewal Tracking 2. Enhance Reporting and Analytics 3. Optimize Workflows 4. Analyze and Improve 5. Train and Support Teams Conclusion Salesforce CPQ revolutionizes renewal management by automating processes, reducing errors, and delivering actionable insights through renewal metrics. By implementing these tools and strategies, you can improve customer retention, increase revenue, and build stronger customer relationships. Whether managing hundreds or thousands of renewals, Salesforce CPQ ensures your business stays ahead with precision and care. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 2, 2025in Data, Enterprise, Salesforce, Salesforce CPQ0 Comments

AI is revolutionizing BI by transforming it from a retrospective tool into a proactive, real-time decision-making engine.

30Dec

AI in Business Intelligence

AI in Business Intelligence: Applications, Benefits, and Challenges AI is rapidly transforming business intelligence (BI) by enhancing analytics capabilities and streamlining processes. This shift is reshaping how organizations leverage data for decision-making. Here’s an in-depth look at how AI complements BI, its advantages, and the challenges it introduces. The Evolution of Business Intelligence with AI BI has traditionally focused on aggregating historical and current data to provide insights into business operations—a process known as descriptive analytics. However, many decision-makers seek more: insights into future trends (predictive analytics) and actionable recommendations (prescriptive analytics). AI bridges this gap. With advanced tools like natural language processing (NLP) and machine learning (ML), AI enables businesses to move beyond static dashboards to dynamic, real-time insights. It also simplifies complex analytics, making data more accessible to business users and fostering more informed, proactive decision-making. Key Benefits of AI in Business Intelligence AI brings significant benefits to BI, including: Real-World Applications of AI in BI AI’s integration into BI goes beyond internal efficiency, delivering external value by enhancing customer experiences and driving business growth. Notable applications include: Challenges of AI in Business Intelligence Despite its potential, integrating AI into BI comes with challenges: Best Practices for AI-Driven BI To successfully integrate AI with BI, organizations should: Future Trends in AI and BI AI is expected to augment rather than replace BI, enhancing its capabilities while keeping human expertise central. Emerging trends include: Conclusion AI is revolutionizing BI by transforming it from a retrospective tool into a proactive, real-time decision-making engine. While challenges remain, thoughtful implementation and adherence to best practices can help organizations unlock AI’s full potential in BI. By integrating AI into existing BI workflows, businesses can drive innovation, improve decision-making, and create more agile and data-driven operations. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

December 30, 2024in AI Tools, Data, Generative AI0 Comments

30Dec

2024 The Year of Generative AI

Was 2024 the Year Generative AI Delivered? Here’s What Happened Industry experts hailed 2024 as the year generative AI would take center stage. Operational use cases were emerging, technology was simplifying access, and general artificial intelligence felt imminent. So, how much of that actually came true? Well… sort of. As the year wraps up, some predictions have hit their mark, while others — like general AI — remain firmly in development. Let’s break down the trends, insights from investor Tomasz Tunguz, and what’s ahead for 2025. 1. A World Without Reason Three years into our AI evolution, businesses are finding value, but not universally. Tomasz Tunguz categorizes AI’s current capabilities into: While prediction and search have gained traction, reasoning models still struggle. Why? Model accuracy. Tunguz notes that unless a model has repeatedly seen a specific pattern, it falters. For example, an AI generating an FP&A chart might succeed — but introduce a twist, like usage-based billing, and it’s lost. For now, copilots and modestly accurate search reign supreme. 2. Process Over Tooling A tool’s value lies in how well it fits into established processes. As data teams adopt AI, they’re realizing that production-ready AI demands robust processes, not just shiny tools. Take data quality — a critical pillar for AI success. Sampling a few dbt tests or point solutions won’t cut it anymore. Teams need comprehensive solutions that deliver immediate value. In 2025, expect a shift toward end-to-end platforms that simplify incident management, enhance data quality ownership, and enable domain-level solutions. The tools that integrate seamlessly and address these priorities will shape AI’s future. 3. AI: Cost Cutter, Not Revenue Generator For now, AI’s primary business value lies in cost reduction, not revenue generation. Tools like AI-driven SDRs can increase sales pipelines, but often at the cost of quality. Instead, companies are leveraging AI to cut costs in areas like labor. Examples include Klarna reducing two-thirds of its workforce and Microsoft boosting engineering productivity by 50-75%. Cost reduction works best in scenarios with repetitive tasks, hiring challenges, or labor shortages. Meanwhile, specialized services like EvenUp, which automates legal demand letters, show potential for revenue-focused AI use cases. 4. A Slower but Smarter Adoption Curve While 2023 saw a wave of experimentation with AI, 2024 marked a period of reflection. Early adopters have faced challenges with implementation, ROI, and rapidly changing tech. According to Tunguz, this “dress rehearsal” phase has informed organizations about what works and what doesn’t. Heading into 2025, expect a more calculated wave of AI adoption, with leaders focusing on tools that deliver measurable value — and faster. 5. Small Models for Big Gains In enterprise AI, small, fine-tuned models are gaining favor over massive, general-purpose ones. Why? Small models are cheaper to run and often outperform their larger counterparts when fine-tuned for specific tasks. For example, training an 8-billion-parameter model on 10,000 support tickets can yield better results than a general model trained on a broad corpus. Legal and cost challenges surrounding large proprietary models further push enterprises toward smaller, open-source solutions, especially in highly regulated industries. 6. Blurring Lines Between Analysts and Engineers The demand for data and AI solutions is driving a shift in responsibilities. AI-enabled pipelines are lowering barriers to entry, making self-serve data workflows more accessible. This trend could consolidate analytical and engineering roles, streamlining collaboration and boosting productivity in 2025. 7. Synthetic Data: A Necessary Stopgap With finite real-world training data, synthetic datasets are emerging as a stopgap solution. Tools like Tonic and Gretel create synthetic data for AI training, particularly in regulated industries. However, synthetic data has limits. Over time, relying too heavily on it could degrade model performance, akin to a diet lacking fresh nutrients. The challenge will be finding a balance between real and synthetic data as AI advances. 8. The Rise of the Unstructured Data Stack Unstructured data — long underutilized — is poised to become a cornerstone of enterprise AI. Only about half of unstructured data is analyzed today, but as AI adoption grows, this figure will rise. Organizations are exploring tools and strategies to harness unstructured data for training and analytics, unlocking its untapped potential. 2025 will likely see the emergence of a robust “unstructured data stack” designed to drive business value from this vast, underutilized resource. 9. Agentic AI: Not Ready for Prime Time While AI copilots have proven useful, multi-step AI agents still face significant challenges. Due to compounding accuracy issues (e.g., 90% accuracy over three steps drops to ~50%), these agents are not yet ready for production use. For now, agentic AI remains more of a conversation piece than a practical tool. 10. Data Pipelines Are Growing, But Quality Isn’t As enterprises scale their AI efforts, the number of data pipelines is exploding. Smaller, fine-tuned models are being deployed at scale, often requiring hundreds of millions of pipelines. However, this rapid growth introduces data quality risks. Without robust quality management practices, teams risk inconsistent outputs, bottlenecks, and missed opportunities. Looking Ahead to 2025 As AI evolves, enterprises will face growing pains, but the opportunities are undeniable. From streamlining processes to leveraging unstructured data, 2025 promises advancements that will redefine how organizations approach AI and data strategy. The real challenge? Turning potential into measurable, lasting impact. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

December 30, 2024in Agentic AI, Artificial Intelligence, Data, Enterprise, Generative AI, Technology0 Comments

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2024 The Year of Generative AI

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