Data Archives - gettectonic.com - Page 5

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deepseek deep dive
05Feb

Deep Dive into DeepSeek

DeepSeek: The AI Lab Turned Controversial Global Player You know we have to write about anything AI related that is making waves. And DeepSeek is definitely doing that. On April 14, 2023, High-Flyer announced the launch of a dedicated artificial general intelligence (AGI) lab, focused on AI research independent of its financial business. This initiative led to the incorporation of DeepSeek on July 17, 2023, with High-Flyer as its primary investor and backer. DeepSeek’s Breakthrough and the Debate on AI Development DeepSeek quickly gained attention in the AI world, with former India IT Minister Rajeev Chandrasekhar highlighting its impact. He stated that DeepSeek’s success reinforced the idea that better datasets and algorithms—rather than increased compute capacity—are the key to advancing AI capabilities. National Security Concerns: Hidden Risks in DeepSeek’s Code Despite its technological achievements, DeepSeek is now at the center of global controversy. Cybersecurity experts have raised serious concerns about the tool’s potential data-sharing links to the Chinese government. According to a report by ABC News, DeepSeek contains hidden code capable of transmitting user data directly to China. Ivan Tsarynny, CEO of the Ontario-based cybersecurity firm Feroot Security, conducted an analysis of DeepSeek’s code and discovered an embedded function that connects user data to CMPassport.com—the online registry for China Mobile, a state-owned telecommunications company. Key Concerns Raised by Cybersecurity Experts: Global Backlash and Regulatory Actions DeepSeek’s security concerns have sparked international scrutiny. Several governments and organizations have moved swiftly to restrict or ban its use: John Cohen, a former acting Undersecretary for Intelligence and Analysis at the U.S. Department of Homeland Security, described DeepSeek as one of the most blatant cases of suspected Chinese surveillance. He emphasized that it joins a growing list of Chinese tech firms identified as potential national security threats. The Future of DeepSeek DeepSeek’s rapid rise and subsequent scrutiny reflect the broader tensions between AI innovation and national security. As regulators worldwide assess its risks, the company’s future remains uncertain—caught between technological breakthroughs and growing geopolitical concerns. Like1 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, 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

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February 5, 2025in AI Tools, Data0 Comments
Financial Services Sector
04Feb

Fundingo Outshines Mortgage Automator

Why Fundingo Outshines Mortgage Automator: A Salesforce-Based Perspective Introduction In the dynamic world of loan servicing and mortgage management, businesses face increasing demands for flexibility, efficiency, and scalability. While Mortgage Automator is a well-known provider, many users encounter significant challenges, including inflexible loan structures and cumbersome reporting processes. Fundingo, a Salesforce-native solution, addresses these issues head-on with a modern, adaptable, and user-friendly approach to loan management. Pain Points of Mortgage Automator Despite its established presence, Mortgage Automator comes with notable limitations: Fundingo’s Competitive Edge Fundingo offers a suite of advantages designed for modern lending institutions, making it the superior choice: Head-to-Head Comparison Feature Fundingo Mortgage Automator Flexibility High – Supports diverse loan products Limited – Rigid loan structures Reporting Automated and user-friendly Complex and manual processes Integrations Seamless with Salesforce ecosystem Poor integration capabilities Scalability Cost-effective, built-in scalability Expensive add-ons hinder growth Security & Compliance SOC 1 certified Basic security measures Summary Fundingo emerges as the ideal solution for modern loan servicing and mortgage management. By addressing the common challenges associated with Mortgage Automator—rigid loan structures, manual processes, and costly add-ons—Fundingo provides a flexible, scalable, and secure alternative. Its Salesforce-native design, built-in CRM, mobile accessibility, exceptional uptime, and robust security measures make it the best competitor in the market, empowering financial institutions to deliver exceptional service while optimizing operational efficiency. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 4, 2025in Data0 Comments
Content Marketing Lessons
03Feb

Marketing Cloud Editions & Agentforce

In Salesforce, Marketing Cloud editions refer to the different tiers of the platform, such as Growth Edition and Advanced Edition, each offering varying levels of marketing automation capabilities. Agentforce, an AI-powered feature within Marketing Cloud, enhances these editions by using generative AI to assist with tasks like creating email content, landing pages, and campaign briefs—essentially serving as a virtual marketing assistant. Both features work together to improve personalization and streamline marketing workflows across different editions. Marketing Cloud Editions Salesforce offers multiple Marketing Cloud editions, each designed to meet different business needs: Agentforce: AI-Powered Marketing Assistance Agentforce is available in both Growth and Advanced editions, enabling users to leverage generative AI to enhance marketing efficiency and effectiveness. Key Benefits of Agentforce ✅ Content Creation – Generate landing pages, email copy, and campaign briefs instantly.✅ Personalization – Tailor content dynamically based on customer data for highly relevant messaging.✅ Efficiency – Automate content generation tasks to reduce manual effort and improve productivity. By integrating Agentforce with Marketing Cloud, businesses can accelerate content creation, enhance personalization, and optimize marketing workflows for better results. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 3, 2025in Data, Generative AI, Marketing Automation, Salesforce0 Comments
Mastering Sales Forecasting
03Feb

Mastering Sales Forecasting

Mastering Sales Forecasting: The Art and Science Behind Predicting Revenue Building a sales forecast is both a strategic art and a data-driven science. Accurate sales predictions ensure business stability, keep leadership informed, and enable better decision-making. This guide explores the essentials of sales forecasting, equipping you with the knowledge to create precise revenue projections and align expectations effectively. A Comprehensive Guide to Sales Forecasting Drawing from over 20 years of experience in sales solutions, we’ve structured this guide around the most pressing questions sales teams face in forecasting. If you’re a seasoned sales leader familiar with the basics, you can skip ahead to sections on designing a forecasting strategy and leveraging tools to enhance forecast accuracy. For insights on handling unpredictable market conditions, explore the section on adapting forecasts during uncertainty. Insights from 7,700 Sales Professionals Our latest report unveils how sales professionals drive productivity and efficiency through data-driven forecasting. Understanding Sales Forecasting What Is a Sales Forecast? A sales forecast estimates expected sales revenue over a specific period, such as a quarter or year. The most effective forecasts are highly accurate and rely on data-driven insights. Sales forecasts address two fundamental questions: Achieving these projections requires careful analysis of key factors: By balancing factual data with industry expertise, sales teams improve forecasting precision over time. The Importance of Sales Forecasting Sales forecasting plays a vital role in business operations, influencing everything from inventory management to hiring decisions. Consider these examples: Accurate forecasting enables businesses to plan effectively, ensuring smooth operations and sustained growth. When forecasts align with actual sales, companies can make strategic investments, such as expanding teams or launching new initiatives. Who Is Responsible for Sales Forecasting? Different teams contribute to sales forecasting, including: Ultimately, sales leadership is accountable for the final forecast, ensuring transparency and accuracy throughout the process. Who Uses Sales Forecasts? Sales forecasts impact multiple business functions: At every level, accurate forecasts enhance strategic decision-making and operational efficiency. Objectives of Sales Forecasting The primary goal of sales forecasting is to predict revenue with precision. When forecasts align with actual performance, companies can optimize internal operations and maintain strong external relationships. Key objectives include: A reliable forecast fosters a positive work environment, boosting morale and collaboration. How to Design a Sales Forecasting Plan Sales forecasting is an ongoing process that evolves with business needs. A strong forecasting plan includes: Adapting Sales Forecasts in Uncertain Times Market fluctuations, economic shifts, and global events can disrupt sales forecasts. When uncertainty arises, sales and finance leaders must quickly assess: Leveraging CRM solutions ensures real-time visibility into deal statuses, allowing businesses to pivot strategies as needed. Accurate data collection and analysis enable informed decision-making, mitigating risks in volatile conditions. Sales Forecast Accuracy Based on extensive industry research, most sales leaders achieve forecast accuracy within 10%. Achieving a 5% variance or lower is rare but signifies exceptional forecasting capabilities. Tools for Sales Forecasting The Role of CRM in Forecasting Customer Relationship Management (CRM) systems, such as Salesforce, enhance forecast accuracy by providing: CRM-driven forecasting consolidates opportunities into a structured framework, improving precision through collaborative insights and AI-powered recommendations. How AI Enhances Forecasting AI-powered tools, like Salesforce Einstein, analyze historical data to identify trends and anomalies. AI-driven alerts highlight potential risks, improving forecast reliability and efficiency. Why CRM Outperforms Traditional Methods While spreadsheets suffice for early-stage businesses, scaling companies require CRM solutions for accurate sales forecasting. CRM systems streamline data integration, improving decision-making and revenue predictions. Conclusion Sales forecasting is a critical business function that blends analytical precision with industry expertise. By leveraging CRM tools and AI-driven insights, organizations can refine their forecasting strategies, optimize resource allocation, and drive sustained growth. Let’s continue the conversation and explore how data-driven forecasting can elevate your sales strategy. Contact Tectonic 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 3, 2025in Data, Salesforce, Salesforce Einstein0 Comments
AI evolves with tools like Agentforce and Atlas
03Feb

Salesforce Atlas

Salesforce Atlas: The Brainpower Behind AI-Driven Transformation A New Era of AI for Enterprise AI is reshaping industries at an unprecedented pace, and agentic AI—AI that can think, plan, and act autonomously—is at the forefront of this revolution. Salesforce is leading the charge with Agentforce, a low-code platform that allows businesses to build, refine, and deploy autonomous AI agents across multiple business functions. At the core of this innovation is Salesforce Atlas, the reasoning engine that empowers Agentforce to tackle complex decision-making tasks just like a human. But Atlas goes further—it continuously learns, adapts, and evolves, setting a new standard for AI-driven enterprises. Let’s explore how Atlas works, its capabilities, and why it’s a game-changer for businesses. Salesforce Atlas: The Reasoning Engine Powering Agentforce Atlas is the intelligent decision-making engine that powers Agentforce’s AI agents. Rather than simply following predefined rules, Atlas evaluates data, refines its approach, and continuously learns from outcomes. When an AI agent encounters a decision point, Atlas asks: ➡️ Do I have enough data to ensure accuracy?✔ If yes, it proceeds with a decision.❌ If no, it seeks additional data or escalates the issue. This iterative learning process ensures that AI agents become more reliable, context-aware, and autonomous over time. Salesforce CEO Marc Benioff teased the potential of Atlas, revealing that: 📊 “We are seeing 90-95% resolution on all service and sales issues with the new Atlas.” That’s a staggering success rate, demonstrating how AI-driven reasoning can transform enterprise efficiency and customer engagement. How Salesforce Atlas Works: The “Flywheel” Process Atlas operates using a structured flywheel process that enables self-improvement and adaptability. Here’s how it works: 1️⃣ Data Retrieval – Atlas pulls structured and unstructured data from the Salesforce Data Cloud.2️⃣ Evaluation – It analyzes the data, generates a plan of action, and assesses whether the plan will drive the desired outcome.3️⃣ Refinement – If the plan isn’t strong enough, Atlas loops back, refines its approach, and iterates until it’s confident in its decision. This cycle repeats continuously, ensuring AI agents deliver accurate, data-driven outcomes that align with business goals. Once a task is completed, Atlas learns from the results, refining its approach to become even smarter over time. The Core Capabilities of Salesforce Atlas Atlas stands out because of its advanced reasoning, adaptive learning, and built-in safeguards—all designed to deliver trustworthy, autonomous AI experiences. 1. Advanced Reasoning & Decision-Making Atlas doesn’t just execute tasks; it thinks critically, determining the best way to approach each challenge. Unlike traditional AI models that follow rigid scripts, Atlas: 🔍 Analyzes real-time data to determine the most effective course of action.📊 Refines its decisions dynamically based on live feedback.🌍 Adapts to changing circumstances to optimize outcomes. At Dreamforce 2024, Marc Benioff demonstrated Atlas’s power by showcasing how it could optimize theme park experiences in real time, analyzing: 🎢 Ride availability👥 Guest preferences🚶 Park flow patterns This real-time decision-making showcases the game-changing potential of agentic AI. 2. Advanced Data Retrieval Atlas leverages Retrieval-Augmented Generation (RAG) to pull highly relevant, verified data from multiple sources. This ensures: ✔ More accurate responses✔ Minimized AI hallucinations✔ Reliable, data-driven insights For example, Saks Fifth Avenue uses Atlas to personalize shopping recommendations for millions of customers—tailoring experiences with precision. 3. Built-in Guardrails for Security & Compliance Salesforce recognizes the importance of AI governance, and Atlas includes robust safeguards to ensure responsible AI usage. 🔐 Ethical AI protocols – Ensures compliance with evolving regulations.🚨 Escalation capabilities – AI knows when to seek human intervention for complex issues.🌍 Hyperforce security – Provides enterprise-grade privacy and security standards. These protections ensure Atlas operates securely, responsibly, and at scale across global enterprises. 4. Reinforcement Learning & Continuous Improvement Atlas doesn’t just process data—it learns from outcomes. 🔄 Refines decisions based on real-world results📈 Optimizes performance over time⚡ Becomes increasingly efficient and tailored to business needs Whether it’s increasing sales conversions, resolving service issues, or optimizing workflows, Atlas ensures AI agents grow smarter with every interaction. Why Salesforce Atlas is a Game-Changer Salesforce Atlas isn’t just another AI tool—it’s the brain behind Salesforce’s next-generation AI ecosystem. With Atlas, businesses can: ✅ Automate complex tasks with AI-driven decision-making.✅ Deliver hyper-personalized customer experiences with confidence.✅ Scale AI-powered workflows across sales, service, and operations.✅ Ensure compliance and trust with built-in governance measures.✅ Adapt AI capabilities to meet evolving business needs. Marc Benioff envisions Atlas as the core of a future where AI and humans collaborate to drive innovation and efficiency. By combining advanced reasoning, dynamic adaptability, and enterprise security, Atlas empowers organizations to work smarter, faster, and more effectively—unlocking the full potential of agentic AI. The future of AI-driven enterprise has arrived. With Salesforce Atlas, businesses can build AI agents that don’t just follow instructions—they think, learn, and evolve. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 3, 2025in Agentforce Platform, Agentic AI, Data, Enterprise, Hyperforce, Salesforce, Salesforce Data Cloud0 Comments
copilots and agentic ai
03Feb

Transforming Industries and Redefining Workflows

The Rise of Agentic AI: Transforming Industries and Redefining Workflows Artificial Intelligence (AI) is evolving faster than we anticipated. No longer limited to predicting outcomes or generating content, AI systems are now capable of handling complex tasks and making autonomous decisions. This new era—driven by Agentic AI—is set to redefine the workplace and transform industries. From Prediction to Autonomy: The Three Waves of AI To understand where we’re headed, it’s important to see how far AI has come. Arun Parameswaran, SVP & MD of Salesforce India, describes it as a fundamental shift: “What has changed with agents is their ability to handle complex reasoning… and, most importantly, to take action.” Unlike previous AI models that recommend or predict, Agentic AI executes tasks, reshaping customer experiences and operational workflows. Agentic AI in Action: Industry Applications At a recent Mint x Salesforce India deep-dive event on AI, industry leaders explored how Agentic AI is driving transformation across sectors. The panel featured: Here’s how Agentic AI is already making an impact: 1. Revolutionizing Customer Support Traditional chatbots have limited capabilities. Agentic AI, however, understands urgency and context. 2. Accelerating Business Decisions In finance and supply chain management, AI agents analyze vast amounts of data and execute decisions autonomously. 3. Transforming Travel & Aviation Airlines are leveraging AI to optimize booking systems, reduce costs, and enhance efficiency. 4. Automating Wealth Management AI agents in financial services monitor markets, adjust strategies, and offer personalized investment recommendations in real time. The Risks & Responsibilities of Agentic AI With great autonomy comes great responsibility. The potential of Agentic AI is vast—but so are the challenges: The Future of Work: AI as a Partner, Not a Replacement Despite concerns about job displacement, AI is more likely to reshape rather than replace roles. What Are AI Agents? AI agents go beyond traditional models like ChatGPT or Gemini. They are proactive, self-learning systems that: They fall into two categories: “AI agents don’t just wait for commands; they anticipate needs and act,” says Dr. Tomer Simon, Chief Scientist at Microsoft Research Israel. AI Agents in the Workplace: A Shift in Roles AI agents streamline processes, but they don’t eliminate the need for human oversight. Salesforce’s Agentforce is a prime example: “Companies need to integrate AI, not fear it. Those who fail to adopt AI tools risk drowning in tasks AI can handle,” warns Dr. Omri Allouche, Chief Scientist at Gong. The Road Ahead: AI-Driven Business Growth Agentic AI is not about replacing people—it’s about empowering them. As organizations re-evaluate workflows and embrace AI collaboration, the companies that act early will gain a competitive edge in efficiency and innovation. Final Thought The AI revolution is here, and Agentic AI is at its forefront. The key question isn’t whether AI will transform industries—it’s how organizations will adapt and thrive in this new era. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 3, 2025in Agentic AI, AI Tools, Artificial Intelligence, Data, Generative AI, Google, Laws, Salesforce, Technology0 Comments
Basejump on AI Analytics
01Feb

Basejump on AI Analytics

The Evolution of Data and AI: A New Frontier Once considered the new oil, data is no longer the sole focus of business transformation. The emergence of artificial intelligence (AI) has shifted the conversation toward compute power as the fundamental resource driving innovation. Sequoia Capital emphasizes AI’s transformative impact, stating: “The fields that generative AI addresses — knowledge work and creative work — comprise billions of workers. [If] Generative AI can make these workers at least 10% more efficient and/or creative: they become not only faster and more efficient, but more capable than before. Therefore, Generative AI has the potential to generate trillions of dollars of economic value.”— Sonya Huang, Pat Grady, Generative AI: A Creative New World Whether this vision materializes remains to be seen, but the comparisons to past technological revolutions—such as the internet and mobile computing—are hard to ignore. The Role of AI in Knowledge Work and Data Analytics Data analytics has seen unprecedented growth, prompting businesses to reassess its value. With a projected compound annual growth rate (CAGR) of 27.3% through 2030, the market’s rapid expansion has led to a push for better tools and standards. Data analytics has evolved from a discipline primarily rooted in physics, mathematics, accounting, and economics to a more structured academic field. This shift is evident in the surge of data science degrees. The National Center for Education Statistics reported a 968% increase in data science bachelor’s degrees awarded from 2020 to 2022, highlighting growing demand. Modern Data Analytics: From ETL to ELTL Traditional extract-transform-load (ETL) processes have struggled to keep up with modern analytical demands. The introduction of extract-load-transform (ELT) architectures, championed by tools like dbt, empowered data teams by shifting transformation ownership from data architects to analysts. However, this speed came at a cost: fragmented data governance and inconsistencies in reporting. A more refined approach—ELTL (extract-load-transform-load)—adds a critical governance step, ensuring structured data models before visualization and reporting. Data Governance, the Semantic Layer, and AI Unstructured data delivery has led to discrepancies across dashboards and reports. To address this, solutions such as dbt’s semantic layer and SQLMesh provide standardized testing, metadata management, and auditing mechanisms. AI plays a crucial role here, offering: AI-Driven Precision Analytics AI is set to revolutionize data querying by replacing cumbersome dashboards with precise, real-time insights. Borrowing from the concept of precision medicine, “precision analytics” ensures that businesses receive tailored data transformations instantly. This shift reduces reliance on static filters and rigid dashboards, allowing AI to dynamically generate and refine queries. The Rise of Data Objects AI-generated SQL queries—what we term “data objects”—are distinct from traditional dashboards in that they are: AI Solutions: Retrieving and Querying Data AI-powered data analytics falls into two broad categories: Building Trust in AI-Driven Analytics AI-generated analytics must be trustworthy, requiring: The Future of AI in Data Analytics AI will not replace data teams but will enhance their efficiency by reducing bottlenecks and accelerating insights. Organizations that integrate AI with strong data governance will achieve a competitive edge, enabling faster, more accurate, and more relevant analytics. The shift toward AI-driven data analytics is inevitable. The question is: will organizations embrace the change and refine their strategies, or will they be left behind in the wake of innovation? 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, 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

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February 1, 2025in Artificial Intelligence, Data, Enterprise, Generative AI, Technology0 Comments

Einstein Service Agent

It’s been a little over a year since the global surge in GenAI chatbots, sparked by the excitement around ChatGPT. Since then, numerous vendors, both large and mid-sized, have invested heavily in the technology, and many users have already adopted AI-powered chatbots. The competition is intensifying, with CRM giant Salesforce releasing its own GenAI chatbot software, Einstein Service Agent. Einstein Service Agent, built on the Einstein 1 Platform, is Salesforce’s first fully autonomous AI agent. It interacts with large language models (LLMs) by analyzing the context of customer messages to determine the next actions. Utilizing GenAI, the agent generates conversational responses grounded in a company’s trusted business data, including Salesforce CRM data. Salesforce claims that service organizations can now significantly reduce the number of tedious inquiries that hinder productivity, allowing human agents to focus on more complex tasks. For customers, this means getting answers faster without waiting for human agents. Additionally, the service promises 24/7 availability for customer communication in natural language, with an easy handoff to human agents for more complicated issues. Businesses are increasingly turning to AI-based chatbots because, unlike traditional chatbots, they don’t rely on specific programmed queries and can understand context and nuance. Alongside Salesforce, other tech leaders like AWS and Google Cloud have released their own chatbots, such as Amazon Lex and Vertex AI, continuously enhancing their software. Recently, AWS updated its chatbot with the QnAIntent capability in Amazon Lex, allowing integration with a knowledge base in Amazon Bedrock. Similarly, Google released Vertex AI Agent Builder earlier this year, enabling organizations to build AI agents with no code, which can function together with one main agent and subagents. The AI arms race is just beginning, with more vendors developing software to meet market demands. For users, this means that while AI takes over many manual and tedious tasks, the primary challenge will be choosing the right vendor that best suits the needs and resources of their business. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 31, 2025in Data, Einstein 1 Platform, Google, Salesforce, Technology0 Comments
AI Agents and Work
29Jan

Maximizing Generative AI in Learning and Development

Maximizing Generative AI in Learning and DevelopmentHow organisations can harness the power of generative AI to enhance learning and development with strategic integration, best practices, and a culture of continuous growth CREDIT: This is an edited version of an article originally published on Vistage Organisations are increasingly recognising the value of generative AI in learning and development. While your employees may already be using it, they may not yet be maximising its potential due to limited resources or understanding. This article offers strategies for organisations to more effectively leverage generative AI and amplify its impact on their teams. A global survey of 14,000 workers by Salesforce in late 2023 revealed that 28% were already using generative AI at work, with over half doing so without formal approval. Similarly, a 2023 McKinsey report echoed these findings, and these numbers are likely even higher now. A recent study by Harvard Business School and Boston Consulting Group (BCG) highlighted the transformative impact of AI, showing that consultants using generative AI completed tasks 22% faster and produced 40% higher quality work compared to those not using it. Unlocking AI Insights Begin by conducting an internal survey to better understand how your employees are using generative AI. Gather data on the tools they use, how often they use them, and how these tools enhance their work. Frame the survey as an opportunity to learn about their experiences rather than as an evaluation or compliance check. Once you’ve analysed the results, identify employees who are using generative AI in creative and effective ways. These individuals—often informal leaders—can provide valuable insights into the practical applications of AI, as well as the challenges they face and how they overcome them. Fostering a Learning Culture Incorporating generative AI into your organisation’s learning and development strategy helps employees tap into the knowledge of early adopters while aligning AI use with broader organisational goals. Cultivate a culture that prioritises continuous learning and upskilling to stay ahead in the rapidly evolving AI landscape. Regularly update training materials to reflect new advancements in AI. Provide opportunities for employees to attend conferences, webinars, and other educational events to stay current. Encourage peer learning by fostering a culture where employees are motivated to share their experiences, tips, and best practices with one another. Developing Best Practices Leverage the expertise of your AI pioneers to establish best practices that are tailored to your organisation’s needs. Create a collaborative environment where these early adopters can share their experiences and insights, and involve them in the development of formal training programs. This ensures that the content is both relevant and practical for your workforce. Pilot these best practices with a small, controlled group of employees before rolling them out more broadly. This allows you to gather feedback, refine the practices, and address any issues. Additionally, create comprehensive guides, FAQs, and video tutorials to give employees easy access to the information they need. Tracking the progress and outcomes of your AI-related learning initiatives is essential. Use data to customise learning experiences and promote a growth mindset among employees. By integrating generative AI into your learning and development strategy, you can tap into internal expertise to drive innovation and improve efficiency across the organisation. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 29, 2025in Data, Generative AI0 Comments
AI Agents as Tools of Trust
29Jan

Reviving Cold Leads with AI Agents

Reviving Cold Leads with AI Agents: Turning Dormant Prospects into Sales Opportunities In sales and marketing, cold or dormant leads often represent untapped potential. AI-powered agents can transform these “dead” leads into engaged prospects by analyzing past interactions, identifying key behavioral patterns, and executing data-driven re-engagement strategies. By leveraging AI, businesses can reignite interest and significantly improve conversion rates, ensuring that no potential customer is left behind. How AI Agents Revive Leads 1. Intelligent Lead Scoring and Prioritization AI can assess historical data, engagement levels, and demographic information to rank leads based on their likelihood to convert. This enables sales teams to focus on high-potential leads while automating engagement with lower-priority ones. 2. Hyper-Personalized Communication AI-driven insights allow businesses to craft highly relevant, tailored messages that align with each lead’s past interactions, preferences, and pain points. 3. Automated Nurture Campaigns AI streamlines lead nurturing through automated workflows that deliver relevant content across multiple channels, ensuring consistent engagement without manual intervention. 4. Predictive Analytics for Lead Conversion By leveraging machine learning models, AI predicts which leads are most likely to convert and recommends the best engagement strategies. 5. Real-Time Dynamic Content Adaptation AI ensures that communication remains relevant by adjusting messaging in real-time based on user behavior and engagement. Key Benefits of Using AI to Revive Leads 1. Increased Conversion Rates AI enhances engagement by delivering highly targeted, relevant messaging, increasing the likelihood of turning cold leads into paying customers. 2. Enhanced Sales Efficiency By automating lead nurturing and prioritization, AI allows sales teams to focus on high-value interactions, reducing manual workload and improving overall efficiency. 3. Cost Reduction and Resource Optimization AI minimizes wasted marketing spend by identifying which leads are worth pursuing, ensuring that budgets are allocated effectively. 4. Scalable and Consistent Engagement AI-powered systems ensure that no lead falls through the cracks, maintaining consistent follow-ups and personalized interactions at scale. 5. Data-Driven Decision Making By continuously analyzing engagement metrics and refining strategies, AI enables sales and marketing teams to make smarter, data-backed decisions. Conclusion AI agents are revolutionizing lead revival by intelligently prioritizing prospects, personalizing communication, and automating engagement strategies. Salesforce Agentforce is leading the charge. By leveraging AI-driven insights and predictive analytics, businesses can transform dormant leads into active opportunities, driving higher conversions and maximizing sales efficiency. As AI technology continues to evolve, its ability to re-engage and convert leads will only become more sophisticated, making it an essential tool for any sales and marketing team. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, 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

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January 29, 2025in Data, Technology0 Comments
salesforce agentforce ai powered agentic agents
29Jan

Agentforce 2.0

Salesforce, the leading CRM provider, is set to launch Agentforce 2.0 in February 2025—an AI-powered toolset designed as a “digital labor platform for building a limitless workforce for the enterprise.” Agentforce 2.0 is a comprehensive AI system that enhances teams with autonomous AI agents embedded in everyday workflows. Among its key offerings are AI-driven agents for Sales Development and Sales Coaching, with pricing starting at $2 per conversation. With this release, Salesforce introduces a library of pre-built skills and workflow integrations, enabling rapid customization and seamless deployment within Slack. Marc Benioff, Chair and CEO of Salesforce, stated, “We’re seamlessly bringing together AI, data, apps, and automation with humans to reshape how work gets done. Agentforce 2.0 cements our position as the leader in digital labor solutions, allowing any company to build a limitless workforce that can truly transform their business.” Agentforce 2.0 includes pre-built AI skills across CRM, Slack, Tableau, and partner-developed integrations via the AppExchange. Customers can further extend Agentforce’s capabilities using MuleSoft, enabling low-code workflows that integrate with any system. The release also introduces an enhanced Agent Builder, which interprets natural language instructions—such as “Onboard New Product Managers”—to automatically generate new AI agents. These agents combine pre-made skills with custom logic built directly in Salesforce, offering unmatched flexibility and efficiency. Additionally, Agentforce 2.0 features Tableau Skills for advanced analytics and insights, further empowering businesses to harness AI-driven decision-making. Like1 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 29, 2025in Agentforce Platform, Data, Enterprise, Mulesoft, Salesforce0 Comments
Unstructured Data
27Jan

Unstructured Data

Ultimately, combining the semantic depth of embeddings with the precision of structured retrieval methods will create more intelligent, robust AI systems—ones that understand the full context of the data and can deliver more precise, relevant results.

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January 27, 2025in Data, Generative AI
ai in marketing
27Jan

Guide to AI in Marketing

The Ultimate Guide to AI in Marketing AI-powered algorithms and machine learning are revolutionizing the marketing landscape by enabling swift processing and analysis of vast datasets. Unlike traditional methods, AI efficiently organizes large volumes of data in real time, redefining how marketing strategies are created and executed. Marketing success hinges on effective data utilization, precise targeting, engaging content, and seamless workflows. AI simplifies these complexities, making them more accessible, scalable, and impactful. Here’s how AI transforms modern marketing. Unleashing AI’s Potential in Marketing AI has become a cornerstone for enhancing customer experiences and boosting marketing productivity. However, to fully leverage AI, it’s essential to understand its capabilities and implementation strategies. Think of AI as your vehicle for uncovering actionable customer insights, optimizing campaigns, and creating tailored customer experiences. While the pace of AI’s evolution may seem overwhelming, this guide will help you take control and confidently drive your AI-powered marketing efforts. Future Trends in Generative AI and Marketing Generative AI is unlocking new possibilities in customer engagement. This guide explores the challenges, advantages, and emerging trends in AI-driven marketing. From attracting customers to maximizing ROI, you’ll discover best practices and real-world examples of successful AI adoption. How AI Works in Marketing AI uses advanced algorithms and pattern recognition to simulate human intelligence in processing data. Through machine learning and deep learning, it identifies trends, predicts outcomes, and automates tasks typically requiring human intervention. Like humans learning from experience, AI improves with practice. It rapidly identifies consumer preferences, behaviors, and purchasing patterns. Two primary types of AI stand out in marketing: These AI types work together—predictive AI extracts insights from data, while generative AI uses those insights to create personalized content and solutions. This synergy enables marketers to automate tasks, segment audiences, and deliver tailored messaging based on individual preferences. AI in Action: Enhancing Customer Engagement AI enables marketers to engage with customers more effectively by: The Power of AI-Driven Marketing Analytics AI-powered analytics revolutionize decision-making by identifying patterns and offering actionable insights. Marketers can use AI tools to: Maximizing ROI with AI AI enables businesses to expand audience reach, improve conversion rates, and enhance customer relationships through personalized content and product recommendations. Its real-time analytics empower marketers to make informed decisions, while automation frees up time for strategic innovation. Navigating Challenges in AI Marketing AI’s potential comes with challenges, including: By prioritizing ethical practices, transparent data policies, and robust compliance measures, marketers can overcome these obstacles and leverage AI responsibly. Best Practices for AI-Driven Marketing To maximize the benefits of AI, marketers should: The Future: AI Copilots in Marketing AI copilots—conversational AI integrated into platforms—are transforming marketing workflows. These tools draft content, provide recommendations, and offer guidance based on CRM data, significantly enhancing efficiency. Looking Ahead: Emerging Trends in AI Marketing Over the next two years, advancements in AI will continue to reshape marketing. Key trends include: By embracing these advancements, marketers can deliver exceptional customer experiences, drive business growth, and stay competitive in an evolving digital landscape. AI is not just a tool—it’s a transformative force. By integrating AI into your marketing strategy, you can unlock unparalleled opportunities to engage customers, optimize campaigns, and propel your organization into the future. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 27, 2025in AI Tools, Data, Generative AI
agetnforce for nonprofits
25Jan

Empowering Nonprofits with Salesforce Technology

Nonprofit organizations face unique challenges, from managing donor relationships and tracking donations to optimizing operations and driving impactful campaigns. AgentForce by Salesforce is an AI-powered solution designed to address these needs, helping nonprofits streamline workflows, enhance donor engagement, and amplify their mission impact. Why Choose AgentForce for Nonprofit Organizations? AgentForce simplifies nonprofit operations by integrating donor management, program tracking, and fundraising tools into a single platform. This allows organizations to focus on what matters most—fulfilling their mission. Powered by AI and automation, AgentForce strengthens donor relationships, improves transparency, and supports data-driven decision-making. Key Benefits of AgentForce for Nonprofits Key Features of AgentForce for Nonprofits Why Partner with Tectonic? At Tectonic, we specialize in empowering nonprofits by implementing AgentForce to meet their unique needs. With a team of Salesforce-certified experts, we ensure seamless integration that maximizes the platform’s capabilities, helping you achieve your goals efficiently. How We Help Nonprofits Real-World Impact of AgentForce in Nonprofits Ready to Transform Your Nonprofit Operations? Empower your team, engage supporters, and amplify your mission impact with AgentForce by Salesforce. Contact Tectonic Today Schedule a free meeting to learn how AgentForce can revolutionize your nonprofit’s operations and help you achieve your goals. Let’s work together to make the world a nicer place! 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 25, 2025in Data, Salesforce, Salesforce Marketing Cloud, Technology

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