Scala Archives - gettectonic.com - Page 6
Scaling Generative AI
23Oct

Scaling Generative AI

Many organizations follow a hybrid approach to AI infrastructure, combining public clouds, colocation facilities, and on-prem solutions. Specialized GPU-as-a-service vendors, for instance, are becoming popular for handling high-demand AI computations, helping businesses manage costs without compromising performance. Business process outsourcing company TaskUs, for example, focuses on optimizing compute and data flows as it scales its gen AI deployments, while Cognizant advises that companies distinguish between training and inference needs, each with different latency requirements.

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October 23, 2024in Data, Enterprise, Generative AI, Google, Salesforce
How Skechers Solved Its Ecommerce Challenges
21Oct

How Skechers Solved Its Ecommerce Challenges

Skechers Boosts Direct-to-Consumer Sales with Ecommerce Platform Upgrades Skechers, now a global brand in 2024, credits its recent ecommerce platform upgrades for saving time and increasing direct-to-consumer sales. However, it wasn’t always equipped with the right technology to support its massive growth. During Salesforce’s Dreamforce conference in San Francisco, Eric Cheng, Skechers USA Inc.’s director of ecommerce architecture, shared insights into how key technology decisions helped the brand expand and enhance its website and content capabilities. “Today, we’re present in over 180 countries worldwide,” Cheng said, speaking on stage at the Moscone Center. Skechers’ journey began in 1992, and its expansion has taken the brand across borders, reaching millions of customers worldwide. “We connect hundreds of millions of customers through our retail stores and ecommerce platform to deliver a unique experience,” Cheng noted, emphasizing the need to meet the diverse demands of each market. Skechers ranks No. 273 in the Top 1000, Digital Commerce 360’s ranking of the largest North American e-retailers by online sales, where it is categorized as an Apparel & Accessories retailer. Digital Commerce 360 projects that Skechers will reach 0.65 million in online sales by 2024. Ecommerce Platform Challenges Cheng acknowledged that Skechers’ digital transformation wasn’t immediate: “The journey did not just happen overnight; it took time and effort.” Skechers faced challenges in three key areas: content management, scalability, and customer experience. The legacy system was inadequate, lacking robust tools for efficient content delivery, previewing scheduled content, and handling localization. As Cheng described, launching a marketing page often required the content team to be on standby at midnight—an unsustainable approach for 17 countries. How Skechers Solved Its Ecommerce Challenges To overcome these hurdles, Skechers partnered with Astound Digital. Together, they implemented Salesforce Service Cloud and Manhattan Active Omni for order management. Kyle Montgomery, senior vice president of commerce at Astound Digital, joined Cheng on stage and highlighted the goal: “Their vision was to unify, supply, and scale.” This transformation enabled Skechers to bring 17 countries in Europe, Japan, and North America onto a single platform. Jennifer Lane, Salesforce’s director of success guides, also emphasized the flexibility achieved using Salesforce’s Page Designer and localization solutions from Salesforce’s AppExchange. Integrations with Thomson Reuters for tax, CyberSource for payments, and Salesforce Marketing Cloud for personalization further enhanced Skechers’ capabilities. The Results Cheng highlighted three key improvements after the ecommerce overhaul. First, content creation and localization tools improved operational efficiency by over 500%. The time to launch in new markets was dramatically reduced from five months to just a few weeks. Additionally, Skechers saw a notable sales boost, with a 24.5% increase in its direct-to-consumer segment during Q1 2023. Skechers’ success demonstrates the significant impact of a well-executed ecommerce platform upgrade, allowing the brand to scale globally while improving customer experience and operational efficiency. Contact Tectonic to learn what Salesforce can do for you. 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

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October 21, 2024in Google, Salesforce, Salesforce Marketing Cloud, Salesforce Service Cloud, Technology
Salesforce and Stripe Integration
19Oct

Salesforce and Stripe Integration

Processing weekly payments can often become time-consuming, with organizations spending significant time just tracking payments post-invoice. Timely updates on payment processing have been a longstanding priority, particularly for companies needing flexible payment options to meet beneficiary needs. The integration of Stripe with Salesforce addresses these challenges, offering a streamlined, efficient solution. Salesforce and Stripe Integration. With a focus on faster processing, this integration enhances payment management, invoicing, and financial oversight. Here’s an overview of the benefits that Stripe and Salesforce integration brings to businesses. Key Benefits of Integrating Stripe with Salesforce Modern businesses demand efficient, seamless transactions. Here are some of the major advantages of combining Stripe and Salesforce: Why Businesses Should Consider Salesforce and Stripe Integration Having implemented this integration for various clients, we have seen how it supports efficient operations. Here are a few reasons why businesses should consider this approach: Simplify Payments with Salesforce and Stripe Integration The Stripe and Salesforce integration represents a transformative opportunity for businesses to improve operational efficiency and customer experience. Beyond a simple tool pairing, this integration paves the way for scalable, complex business operations. Successful integration, however, requires knowledgeable professionals who understand the nuances of customization to fit each organization’s unique needs. Reach out to experienced experts to optimize your integration and harness its full potential. 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

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October 19, 2024in Data, Marketing Automation, Salesforce Communications Cloud, Salesforce Optimization
AI Customer Service Agents Explained
19Oct

AI Customer Service Agents Explained

AI customer service agents are advanced technologies designed to understand and respond to customer inquiries within defined guidelines. These agents can handle both simple and complex issues, such as answering frequently asked questions or managing product returns, all while offering a personalized, conversational experience. Research shows that 82% of service representatives report that customers ask for more than they used to. As a customer service leader, you’re likely facing increasing pressure to meet these growing expectations while simultaneously reducing costs, speeding up service, and providing personalized, round-the-clock support. This is where AI customer service agents can make a significant impact. Here’s a closer look at how AI agents can enhance your organization’s service operations, improve customer experience, and boost overall productivity and efficiency. What Are AI Customer Service Agents? AI customer service agents are virtual assistants designed to interact with customers and support service operations. Utilizing machine learning and natural language processing (NLP), these agents are capable of handling a broad range of tasks, from answering basic inquiries to resolving complex issues — even managing multiple tasks at once. Importantly, AI agents continuously improve through self-learning. Why Are AI-Powered Customer Service Agents Important? AI-powered customer service technology is becoming essential for several reasons: Benefits of AI Customer Service Agents AI customer service agents help service teams manage growing service demands by taking on routine tasks and providing essential support. Key benefits include: Why Choose Agentforce Service Agent? If you’re considering adding AI customer service agents to your strategy, Agentforce Service Agent offers a comprehensive solution: By embracing AI customer service agents like Agentforce Service Agent, businesses can reduce costs, meet growing customer demands, and stay competitive in an ever-evolving global market. 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 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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October 19, 2024in Agentforce Platform, Data, Generative AI, Salesforce, Technology
Salesforce Flows and LeanData
18Oct

Salesforce Flows and LeanData

Mastering Opportunity Routing in Salesforce Flows While leads are essential at the top of the funnel, opportunities take center stage as the sales process advances. In Salesforce, the opportunity object acts as a container that can hold multiple contacts tied to a specific deal, making accurate opportunity routing crucial. Misrouting or delays at this stage can significantly impact revenue and forecasting, while manual processing risks incorrect assignments and uneven distribution. Leveraging Salesforce Flows for opportunity routing can help avoid these issues. Salesforce Flows and LeanData. What Is Opportunity Routing? Opportunity routing is the process of assigning open opportunities to the right sales rep based on specific criteria like territory, deal size, industry, or product type. The goal is to ensure every opportunity reaches the right person quickly, maximizing the chance to close the deal. Opportunity routing also helps prioritize high-potential deals, improving pipeline efficiency. Challenges of Manual Routing Manual opportunity routing can lead to several challenges: Benefits of Automating Routing with Salesforce Flows Using Salesforce Flows for opportunity routing offers many benefits: Setting Up Opportunity Routing in Salesforce Flows Here’s an outline for setting up opportunity routing in Salesforce: Managing Complex Salesforce Flows Opportunity routing in Salesforce Flows is powerful, but managing complex sales environments can be challenging: How LeanData Enhances Opportunity Routing LeanData extends Salesforce routing capabilities with advanced, no-code automation and auditing features: Salesforce Flows and LeanData Whether using Salesforce Flows or LeanData, the goal is to optimize time to revenue. While Salesforce Flows offer a robust foundation, organizations without dedicated admins or developers may face challenges in making frequent updates. LeanData provides greater flexibility and real-time automation, helping to streamline the routing process and drive revenue growth. 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

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October 18, 2024in Data, Enterprise, Salesforce, Salesforce Flow
Ambient AI Enhances Patient-Provider Relationship
16Oct

Ambient AI Enhances Patient-Provider Relationship

How Ambient AI is Enhancing the Patient-Provider Relationship Ambient AI is transforming the patient-provider experience at Ochsner Health by enabling clinicians to focus more on their patients and less on their screens. While some view technology as a barrier to human interaction, Ochsner’s innovation officer, Dr. Jason Hill, believes ambient AI is doing the opposite by fostering stronger connections between patients and providers. Researchers estimate that physicians spend over 40% of consultation time focused on electronic health records (EHRs), limiting face-to-face interactions. “We have highly skilled professionals spending time inputting data instead of caring for patients, and as a result, patients feel disconnected due to the screen barrier,” Hill said. Additionally, increased documentation demands related to quality reporting, patient satisfaction, and reimbursement are straining providers. Ambient AI scribes help relieve this burden by automating clinical documentation, allowing providers to focus on their patients. Using machine learning, these AI tools generate clinical notes in seconds from recorded conversations. Clinicians then review and edit the drafts before finalizing the record. Ochsner began exploring ambient AI several years ago, but only with the advent of advanced language models like OpenAI’s GPT did the technology become scalable and cost-effective for large health systems. “Once the technology became affordable for large-scale deployment, we were immediately interested,” Hill explained. Selecting the Right Vendor Ochsner piloted two ambient AI tools before choosing DeepScribe for an enterprise-wide partnership. After the initial rollout to 60 physicians, the tool achieved a 75% adoption rate and improved patient satisfaction scores by 6%. What set DeepScribe apart were its customization features. “We can create templates for different specialties, but individual doctors retain control over their note outputs based on specific clinical encounters,” Hill said. This flexibility was crucial in gaining physician buy-in. Ochsner also valued DeepScribe’s strong vendor support, which included tailored training modules and direct assistance to clinicians. One example of this support was the development of a software module that allowed Ochsner’s providers to see EHR reminders within the ambient AI app. “DeepScribe built a bridge to bring EHR data into the app, so clinicians could access important information right before the visit,” Hill noted. Ensuring Documentation Quality Ochsner has implemented several safeguards to maintain the accuracy of AI-generated clinical documentation. Providers undergo training before using the ambient AI system, with a focus on reviewing and finalizing all AI-generated notes. Notes created by the AI remain in a “pended” state until the provider signs off. Ochsner also tracks how much text is generated by the AI versus added by the provider, using this as a marker for the level of editing required. Following the successful pilot, Ochsner plans to expand ambient AI to 600 clinicians by the end of the year, with the eventual goal of providing access to all 4,700 physicians. While Hill anticipates widespread adoption, he acknowledges that the technology may not be suitable for all providers. “Some clinicians have different documentation needs, but for the vast majority, this will likely become the standard way we document at Ochsner within a year,” he said. Conclusion By integrating ambient AI, Ochsner Health is not only improving operational efficiency but also strengthening the human connection between patients and providers. As the technology becomes more widespread, it holds the potential to reshape how clinical documentation is handled, freeing up time for more meaningful patient interactions. 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

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October 16, 2024in AI Tools, Data, Enterprise, Salesforce Health and Life Sciences Solutions, Technology
Multi AI Agent Systems
15Oct

Multi AI Agent Systems

Building Multi-AI Agent Systems: A Comprehensive Guide As technology advances at an unprecedented pace, Multi-AI Agent systems are emerging as a transformative approach to creating more intelligent and efficient applications. This guide delves into the significance of Multi-AI Agent systems and provides a step-by-step tutorial on building them using advanced frameworks like LlamaIndex and CrewAI. What Are Multi-AI Agent Systems? Multi-AI Agent systems are a groundbreaking development in artificial intelligence. Unlike single AI agents that operate independently, these systems consist of multiple autonomous agents that collaborate to tackle complex tasks or solve intricate problems. Key Features of Multi-AI Agent Systems: Applications of Multi-AI Agent Systems: Multi-agent systems are versatile and impactful across industries, including: The Workflow of a Multi-AI Agent System Building an effective Multi-AI Agent system requires a structured approach. Here’s how it works: Building Multi-AI Agent Systems with LlamaIndex and CrewAI Step 1: Define Agent Roles Clearly define the roles, goals, and specializations of each agent. For example: Step 2: Initiate the Workflow Establish a seamless workflow for agents to perform their tasks: Step 3: Leverage CrewAI for Collaboration CrewAI enhances collaboration by enabling autonomous agents to work together effectively: Step 4: Integrate LlamaIndex for Data Handling Efficient data management is crucial for agent performance: Understanding AI Inference and Training Multi-AI Agent systems rely on both AI inference and training: Key Differences: Aspect AI Training AI Inference Purpose Builds the model. Uses the model for tasks. Process Data-driven learning. Real-time decision-making. Compute Needs Resource-intensive. Optimized for efficiency. Both processes are essential: training builds the agents’ capabilities, while inference ensures swift, actionable results. Tools for Multi-AI Agent Systems LlamaIndex An advanced framework for efficient data handling: CrewAI A collaborative platform for building autonomous agents: Practical Example: Multi-AI Agent Workflow Conclusion Building Multi-AI Agent systems offers unparalleled opportunities to create intelligent, responsive, and efficient applications. By defining clear agent roles, leveraging tools like CrewAI and LlamaIndex, and integrating robust workflows, developers can unlock the full potential of these systems. As industries continue to embrace this technology, Multi-AI Agent systems are set to revolutionize how we approach problem-solving and task execution. 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

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October 15, 2024in Artificial Intelligence, Data, Technology
SingleStore Acquires BryteFlow
12Oct

SingleStore Acquires BryteFlow

SingleStore Acquires BryteFlow, Paving the Way for Real-Time Analytics and Next-Gen AI Use Cases SingleStore, the world’s only database designed to transact, analyze, and search petabytes of data in milliseconds, has announced its acquisition of BryteFlow, a leading data integration platform. This move enhances SingleStore’s capabilities to ingest data from diverse sources—including SAP, Oracle, and Salesforce—while empowering users to operationalize data from their CRM and ERP systems. With the acquisition, SingleStore will integrate BryteFlow’s data integration technology into its core offering, launching a new experience called SingleConnect. This addition will complement SingleStore’s existing functionalities, enabling users to gain deeper insights from their data, accelerate real-time analytics, and support emerging generative AI (GenAI) use cases. “This acquisition marks a pivotal step in our mission to deliver unparalleled speed, scale, and simplicity,” said Raj Verma, CEO of SingleStore. “Customer demands are evolving rapidly due to shifts in big data storage formats and advancements in generative AI. We believe that data is the foundation of all intelligence, and SingleConnect comes at a perfect time to address this need.” BryteFlow’s platform provides scalable change data capture (CDC) capabilities across multiple data sources, ensuring data integrity between source and target. It integrates seamlessly with major cloud platforms like AWS, Microsoft Azure, and Google Cloud, making it a powerful tool for cloud-based data warehouses and data lakes. Its no-code interface allows for easy and accessible data integration, ensuring that existing BryteFlow customers will experience uninterrupted service and ongoing support. “By combining BryteFlow’s real-time data integration expertise with SingleStore’s capabilities, we aim to help global organizations extract maximum value from their data and scale modern applications,” said Pradnya Bhandary, CEO of BryteFlow. “With SingleConnect, developers will find it easier and faster to access enterprise data sources, tackle complex workloads, and deliver exceptional experiences to their customers.” 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

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October 12, 2024in Data, Enterprise, Generative AI, Google, Salesforce, Technology
Salesforce AI Introduces SFR-Judge
12Oct

Salesforce AI Introduces SFR-Judge

Salesforce AI Introduces SFR-Judge: A Family of Three Evaluation Models with 8B, 12B, and 70B Parameters, Powered by Meta Llama 3 and Mistral NeMO The rapid development of large language models (LLMs) has transformed natural language processing, making the need for accurate evaluation of these models more critical than ever. Traditional human evaluations, while effective, are time-consuming and impractical for the fast-paced evolution of AI models. Salesforce AI Introduces SFR-Judge. To address this, Salesforce AI Research has introduced SFR-Judge, a family of LLM-based judge models designed to revolutionize how AI outputs are evaluated. Built using Meta Llama 3 and Mistral NeMO, the SFR-Judge family includes models with 8 billion (8B), 12 billion (12B), and 70 billion (70B) parameters. These models are designed to handle evaluation tasks such as pairwise comparisons, single ratings, and binary classifications, streamlining the evaluation process for AI researchers. Overcoming Limitations in Traditional Judge Models Traditional LLMs used for evaluation often suffer from biases such as position bias (favoring responses based on their order) and length bias (preferring longer responses regardless of their accuracy). SFR-Judge addresses these issues by leveraging Direct Preference Optimization (DPO), a training method that enables the model to learn from both positive and negative examples, reducing bias and ensuring more consistent and accurate evaluations. Performance and Benchmarking SFR-Judge has been rigorously tested across 13 benchmarks covering three key evaluation tasks. It outperformed existing judge models, including proprietary models like GPT-4o, achieving top performance on 10 of the 13 benchmarks. Notably, on the RewardBench leaderboard, SFR-Judge achieved a 92.7% accuracy, marking a new high in LLM-based evaluation and demonstrating its potential not only as an evaluation tool but also as a reward model for reinforcement learning from human feedback (RLHF) scenarios. Innovative Training Approach The SFR-Judge models were trained using three distinct data formats: These diverse data formats allow SFR-Judge to generate well-rounded, accurate evaluations, making it a more reliable and robust tool for model assessment. Bias Mitigation and Robustness SFR-Judge was tested on EvalBiasBench, a benchmark designed to measure six types of bias. The results demonstrated significantly lower bias levels compared to competing models, along with high consistency in pairwise order comparisons. This robustness ensures that SFR-Judge’s evaluations remain stable, even when the order of responses is altered, making it a scalable and reliable alternative to human annotation. Key Takeaways: Conclusion Salesforce AI Research’s introduction of SFR-Judge represents a breakthrough in the automated evaluation of large language models. By incorporating Direct Preference Optimization and a diverse training approach, SFR-Judge sets a new standard for accuracy, bias reduction, and consistency. Its ability to provide detailed feedback and adapt to various evaluation tasks makes it a powerful tool for the AI community, streamlining the process of LLM assessment and setting the stage for future advancements in AI evaluation. 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

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October 12, 2024in Data, Salesforce
Nvidia and Salesforce
11Oct

Nvidia and Salesforce

Salesforce and Nvidia have announced a groundbreaking collaboration to push the boundaries of AI, transforming both customer and employee experiences. Redefining AI in Enterprise Software As businesses worldwide face the complexities and costs of integrating AI into their operations, Salesforce and Nvidia are stepping in with a strategic partnership designed to redefine AI capabilities. This collaboration merges Salesforce’s extensive CRM and enterprise software expertise with Nvidia’s advanced AI and high-performance computing technologies. The goal is to create a new generation of AI agents and avatars that can operate autonomously, grasp complex business contexts, and engage with humans in a more natural, intuitive manner. Marc Benioff, Chair and CEO of Salesforce, states: “Together with Nvidia, we’re spearheading the third wave of the AI revolution—moving beyond copilots to a seamless integration of humans and intelligent agents driving customer success.” Enhancing Salesforce’s Platform The partnership focuses on integrating Nvidia’s accelerated computing and AI software to enhance Salesforce’s platform performance. Key to this effort is the optimization of Salesforce Data Cloud, which harmonizes structured and unstructured customer data in real time. Nvidia’s full-stack accelerated computing platform will significantly increase compute resources, leading to faster insights and improved AI performance across Salesforce’s offerings. AI-Powered Avatars and Beyond A major innovation from this collaboration is the development of AI-powered avatars. By combining Nvidia ACE, a suite of digital human technologies, with Salesforce’s new Agentforce platform, the companies aim to create more engaging, human-like experiences for interactions with customers and employees. These avatars will leverage multi-modal AI models for speech recognition, text-to-speech, and contextual visual responses, potentially revolutionizing business communication. Nvidia founder and CEO Jensen Huang envisions a future where “every company, every job will be enhanced by a wide range of AI agents—assistants that will transform how we work.” He adds, “Nvidia and Salesforce are uniting our technologies to accelerate the development of AI agents, supercharging productivity for companies.” Transforming Business Operations The Salesforce-Nvidia partnership is more than a technological alliance; it’s a strategic move to meet the increasing demand for AI-driven enterprise solutions. The collaboration positions both companies at the forefront of the AI revolution in enterprise software, aiming to reshape how businesses interact with customers and manage their operations. Key facts include: Real-World Applications The potential applications of this technology are extensive. For example: Looking Ahead As Salesforce and Nvidia’s partnership unfolds, it promises not only technological advancements but a fundamental shift in how businesses leverage AI for growth, efficiency, and customer satisfaction. Marc Benioff highlights the potential: “By combining Nvidia’s AI platform with Agentforce, we’re amplifying AI performance and creating dynamic digital avatars, delivering more engaging, intelligent, and immersive customer experiences than ever before.” This collaboration is set to lead the third wave of the AI revolution, integrating humans and intelligent agents to drive unprecedented customer success. 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

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October 11, 2024in Agentforce Platform, Data, Enterprise, Salesforce, Salesforce Data Cloud, Technology
Build Launch and Track Campaigns
10Oct

Build Launch and Track Campaigns

Revolutionizing Campaigns: How Marketing Agents Empower Your Marketing Team Marketing agents are transforming how businesses create, launch, and track campaigns—delivering better results while boosting internal team productivity and cohesion. With the power of AI and data, these agents act as collaborative partners, enhancing marketing efficiency and creativity in unprecedented ways. A Smarter Approach to Campaign Challenges Marketers have long faced the challenge of creating quality content at scale. According to the Content Marketing Institute, 54% of B2B marketers struggle to meet this demand, while B2C marketers often lack the resources to make their efforts scalable and consistent. On top of this, they must ensure campaigns are efficient, customer-centric, and stand out in a competitive landscape. Enter marketing agents—AI-powered tools that help teams manage and optimize campaigns, from strategy to execution. At Dreamforce 2024, Salesforce unveiled Agentforce, a suite of intelligent agents integrated across the Customer 360 platform, including Agentforce Campaigns. With 71% of marketers planning to adopt generative and predictive AI within the next 18 months, as per Salesforce’s State of Marketing report, tools like Agentforce are poised to redefine how campaigns are built and delivered. How Humans and AI Agents Work Together Marketing agents are AI-powered virtual assistants that collaborate with humans to analyze data, generate insights, and execute marketing plans. Unlike traditional tools, they understand the context behind your needs and suggest actionable solutions—whether that’s creating content, optimizing campaigns, or analyzing results. By automating time-consuming tasks, marketing agents free teams to focus on high-value activities like strategy and personalization. But the key to maximizing their potential lies in shifting your mindset: instead of simply seeking efficiency, aim to transform how you deliver exceptional customer experiences. 8 Ways Agentforce Campaigns Elevates Your Marketing 1. Intelligent Recommendations Agentforce Campaigns turns insights into actions. For example, Marketing Cloud’s Einstein not only tracks your goals but also suggests adjustments or new campaigns tailored to your objectives, helping you stay ahead. 2. Instant Campaign Briefs Building a campaign starts with a solid brief. With Agentforce, you can create one in seconds using natural language prompts. The AI-generated brief incorporates your goals and guidelines, making collaboration and approvals seamless. 3. Contextual Content Creation Agentforce generates emails, landing pages, and calls to action directly aligned with your brand’s tone and campaign goals. Marketers can refine outputs with natural language prompts, ensuring a perfect fit for their strategy. 4. Effortless Audience Segmentation No SQL skills? No problem. Describe your ideal audience in natural language, and Agentforce will translate that into actionable segments—helping you target precisely the right customers. 5. Automated Journey Activation Agentforce simplifies multi-channel journey creation by drafting personalized campaign flows. You can refine, approve, and activate these journeys with ease, saving time while enhancing impact. 6. Unlimited Content Variations AI eliminates content constraints, allowing you to generate multiple variations for personalized campaigns. Target high-value customers, newcomers, or loyal fans with tailored messages—all at scale. 7. Explore Nuanced Segments Agentforce enables marketers to create segments without relying on overburdened data science teams. Dive into deeper audience insights, such as churn rates based on location, age, or past behavior, with just a prompt. 8. Embed Continuous Testing Testing is often deprioritized due to time limitations. Agentforce automates testing workflows, making it easier to incorporate A/B testing and iterative learning into every campaign. Getting Started with Agentforce Campaigns Agentforce Campaigns is available in Marketing Cloud Growth and Advanced Editions, designed to empower businesses of all sizes. By integrating AI-driven tools into your workflow, you can elevate your marketing to new heights—enhancing creativity, efficiency, and customer engagement. Ready to revolutionize your campaigns? Explore how Agentforce can help you win customers and foster a more productive, cohesive marketing team. Salesforce Disclaimer: Unreleased features mentioned here are subject to change and may not become available as described. Make purchasing decisions based on currently available features. 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 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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October 10, 2024in Agentforce Platform, Artificial Intelligence, Data, Google, Salesforce, Salesforce Personalization
09Oct

Enterprise AI

Enterprise AI: Revolutionizing Business Operations for a Competitive Edge Enterprise AI refers to the suite of advanced artificial intelligence technologies—such as machine learning, natural language processing (NLP), robotics, and computer vision—that organizations use to transform operations, enhance efficiency, and gain a competitive advantage. These technologies demand high-quality data, skilled expertise, and adaptability to rapid advancements. Businesses increasingly adopt enterprise AI because of its ability to automate critical processes, reduce costs, optimize operations, and enable data-driven decision-making. According to McKinsey’s 2024 report, 72% of organizations now integrate AI into their operations, a significant increase from 50% just six years ago. However, implementing AI presents challenges, such as employee mistrust, data biases, lack of explainability, and managing AI’s fast evolution. Successful adoption requires aligning AI initiatives with organizational goals, fostering data trust, and building internal expertise. This guide provides a strategic roadmap for embracing enterprise AI, covering foundational concepts, advanced use cases, and ways to navigate common pitfalls. Why AI Matters in the Enterprise Enterprise AI is a transformative force, similar to how the internet revolutionized global businesses. By integrating AI into their operations, organizations can achieve: AI-driven applications are reshaping industries by enabling hyper-personalized customer experiences, optimizing supply chains, and automating repetitive tasks to free employees for higher-value contributions. The rapid pace of AI innovation requires leaders to consistently re-evaluate its alignment with their strategies while maintaining effective data management and staying informed on evolving tools and regulations. AI’s Transformational Impact on Business AI’s potential is as groundbreaking as electrification in the 20th century. Its immediate influence lies in automating tasks and augmenting human workflows. For example: Generative AI tools like ChatGPT and Copilot further accelerate adoption by automating creative and intellectual tasks. Key Benefits of Enterprise AI Challenges of Enterprise AI Despite its benefits, AI adoption comes with hurdles: Ethical concerns, such as workforce displacement and societal impacts, also demand proactive strategies. AI and Big Data: A Symbiotic Relationship AI thrives on large, high-quality datasets, while big data analytics leverage AI to extract deeper insights. The rise of cloud computing amplifies this synergy, enabling scalable, cost-effective AI deployments. Evolving AI Use Cases AI continues to redefine industries, turning complex tasks into routine operations: Future AI Trends to Watch Building the Future with Responsible AI As AI advances, organizations must prioritize responsible AI practices, balancing innovation with ethical considerations. Developing robust frameworks for transparency and governance is essential to maintaining trust and fostering sustainable growth. AI’s future offers vast opportunities for businesses willing to adapt and innovate. By aligning AI initiatives with strategic goals and investing in robust ecosystems, enterprises can unlock new efficiencies, drive innovation, and lead in their industries. 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

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October 9, 2024in AI Tools, Artificial Intelligence, Data, Enterprise, Generative AI
dbt Labs and Salesforce
08Oct

dbt Labs and Salesforce

dbt Labs, a leader in analytics engineering, announced at Coalesce 2024 a groundbreaking partnership with Salesforce to integrate Salesforce Data Cloud’s AI, automation, and analytics capabilities with dbt Labs’ expertise in data transformation and metrics management. This collaboration aims to deliver a seamless, trustworthy, and comprehensive data experience for users. “Together, Salesforce and dbt Labs are redefining what’s possible with data,” said Ryan Segar, Chief Customer Officer at dbt Labs. “By integrating our solutions, we’re helping customers accelerate their analytics development journey, delivering powerful, flexible data insights that drive better business outcomes.” The partnership offers Salesforce Data Cloud, Tableau, and Agentforce users access to dbt Labs’ robust data transformation pipeline, ensuring high data accuracy, quality, and reliability. An independent metrics layer from dbt Labs will allow Salesforce and Tableau users to define, manage, and standardize key business metrics, providing consistent and comparable insights across platforms. This supports confident, data-driven decision-making directly within the flow of work. New integrations include the ability to connect dbt Semantic Layer with Tableau Pulse, export metrics from dbt Cloud to Tableau Cloud, and leverage dbt models within Tableau and Einstein. Future integrations will explore features such as alignment with Tableau Semantics and enabling instant Tableau analytics from the dbt Cloud console. Ali Tore, Senior Vice President of Advanced Analytics at Salesforce, emphasized the benefits of this collaboration: “By combining the strengths of dbt with Salesforce Data Cloud, we’re empowering customers with AI-powered insights built on a foundation of trusted, reliable data. This integration unlocks the full potential of their data to drive impactful business outcomes.” With over 50,000 teams already using dbt, Salesforce customers can now leverage advanced data modeling techniques trusted by leading global organizations. This partnership offers scalable, robust data modeling directly within Salesforce Data Cloud, benefiting both technical and non-technical users alike. 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

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October 8, 2024in Data, Salesforce, Salesforce Data Cloud
Data Cloud Model
08Oct

Data Cloud Model

While many Salesforce products like Sales Cloud, Service Cloud, Education Cloud, Health Cloud, and various industry clouds are built on a common ‘core’ platform that shares the same datastore (an Oracle relational database), Salesforce Data Cloud operates on (Data Cloud Model) a distinct architecture and technology stack. This insight explores the data models and related concepts that underpin the platform. Data Cloud Architecture and Storage Starting with the storage layer, Salesforce Data Cloud integrates multiple services: This combination enables Data Cloud to provide a petabyte-scale data store, overcoming the scalability and performance constraints of traditional relational databases. The physical architecture of Data Cloud is represented as a set of data objects, which form the foundation for how data is ingested, harmonized, and activated within the platform. Key Data Cloud Objects Data Source A Data Source is the initial data layer in Data Cloud, representing an external platform or system from which your data originates. Data Sources can include: Data Stream A Data Stream is an entity extracted from a Data Source, such as ‘Orders’ from Commerce Cloud, ‘Contacts’ from Sales Cloud, or ‘Subscribers’ from Marketing Cloud. Once a Data Source is connected to Data Cloud, Data Streams provide access to these entities and require assignment to a category: Profile, Engagement, or Other. A single Data Source can contain multiple Data Streams. Data Source Object (DSO) Data Streams are ingested into Data Source Objects (DSOs), which serve as temporary staging stores containing data in its raw, native format (e.g., CSV files). Minor transformations can be applied to fields during data ingestion. Data Lake Object (DLO) The next step in the data flow is the Data Lake Object (DLO). DLOs are typed, schema-based, materialized views that reside in the data lake (Amazon S3) and are generally stored as Apache Parquet files. This format, along with Apache Iceberg’s abstraction layer, supports efficient data storage and retrieval. DLOs are the first objects available for inspection and preparation of data, including field mapping and additional transformations. Data Model Object (DMO) Unlike DSOs and DLOs, which use a physical data store, Data Model Objects (DMOs) provide a virtual, non-materialized view into the data lake. Queries against a DMO return results based on the current data snapshot in DLOs, without storing them. DMOs can aggregate attributes from different Data Streams, Calculated Insights, and other sources. DMOs inherit their category from the first DLO mapped to them, and only DLOs with the same category can be mapped to the DMO. Like Salesforce objects, DMOs offer a canonical data model with pre-defined attributes (standard objects), and you can also create custom DMOs (custom objects). DMOs can have one-to-one or many-to-one relationships with other DMOs. Currently, there are 89 standard DMOs in Data Cloud, and this number is growing to support more use cases. DMOs are organized into various subject areas, including: Data Spaces Data Spaces offer logical partitions, allowing data to be segregated between different brands, regions, or departments, without the need for multiple Data Cloud instances. They also align with a Software Development Lifecycle (SDLC), enabling you to stage and test Data Objects in separate environments without affecting production data. Data Sources, Data Streams, and DLOs can be shared across Data Spaces, while DMOs and other platform features are isolated based on user permissions. Final Thoughts With the drop in storage costs and advancements in technology, companies now have vast datasets at their disposal. Every customer interaction, whether it’s a purchase, an email open, or a web page view, can be captured and stored. When properly organized, this data allows businesses to understand customers better, predict their needs, personalize interactions, and much more. However, one of Salesforce’s challenges is that its original platform, built over 20 years ago, was designed for a different era and struggles with handling voluminous, “big” data. Salesforce Data Cloud addresses these limitations with a modern architecture that overcomes the constraints of relational databases. Data Cloud is poised to become the backbone of the Salesforce platform, supporting the data needs of customers and products for the next two decades. If you’re interested in learning how to implement and integrate Salesforce Data Cloud in your organization, following best practices, reach out 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

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October 8, 2024in Data, Google, Salesforce, Salesforce Data Cloud, Snowflake, Technology, Unified Knowledge

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