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AgentForce Flex Pricing

Salesforce Introduces Flexible Pricing for Agentforce to Accelerate AI Adoption Across Enterprises Salesforce, the global leader in AI-powered CRM, last week announced a new flexible pricing model for Agentforce, its digital labor platform, designed to meet surging demand for AI-driven automation across every employee, department, and business process. As AI adoption accelerates, CIOs face mounting pressure to balance innovation with cost control. According to Salesforce’s CIO AI Trends research, 90% of IT leaders say managing AI expenses is hindering their ability to drive value—a challenge underscored by recent findings from CIO.com. To address this, Salesforce is introducing three groundbreaking pricing innovations that empower businesses to scale AI adoption efficiently, align costs with outcomes, and adapt investments as needs evolve: 1. Flex Credits: Pay Only for the AI Actions You Use Moving beyond traditional per-conversation pricing, Salesforce now offers Flex Credits, a consumption-based model where customers pay only for the specific AI actions performed—whether updating records, automating workflows, or resolving cases. 2. Flex Agreement: Shift Investments Between Human & Digital Labor The new Flex Agreement allows organizations to dynamically reallocate budgets—converting user licenses into Flex Credits (or vice versa)—ensuring optimal resource allocation as business priorities shift. 3. Agentforce User Licenses & Add-Ons: Unlimited AI for Every Employee Salesforce is simplifying AI adoption with per-user-per-month (PUPM) pricing, offering unlimited employee-facing AI agent usage. Seamlessly integrated with Salesforce and Slack, these licenses eliminate usage caps, enabling businesses to deploy AI at scale across sales, service, HR, and IT. Industry & Customer Reactions Availability & Pricing With this move, Salesforce reinforces its commitment to making AI accessible, scalable, and cost-effective for enterprises worldwide. 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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The Paradox of Jagged Intelligence in AI

The Paradox of Jagged Intelligence in AI

AI systems are breaking records on complex benchmarks, yet they falter on simpler tasks humans handle intuitively—a phenomenon dubbed jagged intelligence. This ainsight explores this uneven capability, tracing its evolution in frontier models and the impact of reasoning models. We introduce SIMPLE, a new public benchmark with easy reasoning tasks solvable by high schoolers, vital for enterprise AI where reliability trumps advanced math skills. Since ChatGPT’s 2022 debut, foundation models have been marketed as chat interfaces. Now, reasoning models like OpenAI’s o3 and DeepSeek’s R1 leverage extra inference-time computation for step-by-step internal reasoning, boosting performance in math, engineering, and coding. This shift to scaling inference compute arrives as pretraining gains may be plateauing. Benchmarking the Gaps Traditional AI benchmarks measure peak performance on tough tasks, like graduate exams or complex code, creating new challenges as old ones are mastered. However, they overlook reliability and worst-case performance on basic tasks, masking jaggedness in “solved” areas. Modern models outshine humans on some challenges but stumble unpredictably on others, unlike specialized tools (e.g., calculators or photo editors). Despite advances in modeling and training, this inconsistent jaggedness persists. SIMPLE targets easy problems where AI still lags, offering insights into jaggedness trends. Evolution of Jaggedness Will jaggedness shrink or grow as models advance? This question shapes enterprise AI success. Lacking jaggedness benchmarks, we created SIMPLE—a dataset of 225 simple questions, each solvable by at least 10% of high schoolers. Example Questions from SIMPLE Performance Trends Evaluating current and past top models on SIMPLE traces jaggedness over time. Green tasks are high school-level; blue are expert-level. School-level benchmarks saturated by 2023-2024, shifting focus to harder tasks. SIMPLE, using the best of gpt-4, gpt-4-turbo, gpt-4o, o1, and o3-mini, scores lowest on school-level questions. Yet, reasoning models show a ~30% improvement, suggesting they reduce jaggedness by double-checking work, linking reasoning to better simple-task performance. Case Study Insights and Implications Reasoning models transfer top-line gains to simple tasks to some extent, but SIMPLE remains unsaturated. Jaggedness persists, with top-line progress outpacing worst-case improvements. This mirrors computing’s history: excelling in narrow domains, outpacing human limits once applied, yet always facing new challenges. Jaggedness may not just define AI—it could be computation’s inherent nature. 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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Salesforce prompt builder

Mastering Agentforce

Mastering Agentforce: How to Supercharge Salesforce with AI-Powered Prompts Unlocking the Power of Agentforce Salesforce’s Agentforce is transforming how businesses automate marketing and sales—using generative AI to handle repetitive tasks, respond to prospect behavior in real time, and drive smarter strategies with less effort. But to fully leverage Agentforce, you need to master prompt engineering—the art of crafting effective AI instructions. (Don’t let the term “engineering” intimidate you—it simply means writing clear, structured prompts!) AI Prompts 101: The Key to Personalized Automation An AI prompt is a detailed instruction that guides Salesforce’s large language model (LLM) to generate relevant, business-specific responses. Why Prompts Matter Introducing Salesforce Prompt Builder Prompt Builder is Agentforce’s central hub for creating, managing, and applying reusable prompt templates across your AI Agents. How It Works 3 Types of Prompt Templates Step-by-Step: How to Use Prompt Builder 1. Get Access 2. Open Prompt Builder 3. Craft Your Prompt Every effective prompt should include:✅ Who’s involved? (Roles, relationships, data)Example: “You are a marketer named {!user.firstname} writing to {!account.name}, a potential customer.” ✅ Context (Tone, style, language)Example: “Write a professional yet conversational email in British English.” ✅ Goal (What should the AI accomplish?)Example: “Persuade {!account.name} to book a 15-minute intro call.” ✅ Constraints (Word limits, data boundaries)Example: “Keep under 300 words. Avoid jargon and unsupported claims.” 📌 Pro Tip: Draft prompts in a separate doc first for easy editing. 4. Test & Refine Before going live:✔ Verify responses match your goals & brand voice.✔ Check for bias, errors, or inconsistencies.✔ Fine-tune by adding more context or rephrasing. 5. Deploy Activate your prompt for use in: Why This Changes Everything With Agentforce + Prompt Builder, Salesforce users can:🚀 Scale hyper-personalized outreach without manual work.🤖 Automate repetitive tasks while maintaining brand consistency.📈 Drive higher ROI with AI that adapts to real-time data. Ready to transform your Salesforce automation? Start engineering smarter prompts 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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Informatica, Agentforce, and Salesforce

Informatica, Agentforce, and Salesforce

Informatica and Salesforce Deepen AI Partnership to Power Smarter Customer Experiences Las Vegas, [May, 2025] – At Informatica World, Informatica (NYSE: INFA) announced an expanded collaboration with Salesforce to integrate its Intelligent Data Management Cloud (IDMC) with Salesforce Agentforce, enabling enterprises to deploy AI agents fueled by trusted, real-time customer data. Bringing Trusted Data to AI-Powered Workflows The integration centers on Informatica’s Master Data Management (MDM), which distills fragmented customer data into unified, accurate “golden records.” These records will enhance Agentforce AI agents—used by sales and service teams—to deliver: “Data is foundational for agentic AI,” said Tyler Carlson, SVP of Business Development at Salesforce. “With Informatica’s MDM, Salesforce customers can ground AI interactions in high-quality data for more targeted service and engagement.” Key Capabilities (Available H2 2025 on Salesforce AppExchange) “This is about action, not just insights,” emphasized Rik Tamm-Daniels, GVP of Strategic Ecosystems at Informatica. “We’re embedding reliable enterprise data directly into Agentforce to drive measurable outcomes.” Why It Matters As AI agents handle more customer interactions, data quality becomes critical. This partnership ensures Agentforce operates on clean, governed data—reducing hallucinations and bias while improving relevance. The MDM SaaS tools for Agentforce will enter pilot testing soon, with general availability slated for late 2025. 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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Next-Gen Fundraising: How Salesforce Empowers Nonprofits of All Sizes

Next-Gen Fundraising: How Salesforce Empowers Nonprofits of All Sizes

Personalized donor engagement has always been the cornerstone of successful fundraising. Building meaningful connections—tailored to individual interests and giving histories—drives generosity and loyalty. Yet, scaling this level of personalization has been a persistent challenge for nonprofits. Enter Salesforce, the world’s leading CRM, now transforming nonprofit fundraising with AI-driven insights, automation, and hyper-personalized engagement. By unifying donor data and leveraging cutting-edge technology, Salesforce empowers organizations—from grassroots initiatives to large institutions—to deepen relationships and maximize impact. Here’s how Salesforce is revolutionizing nonprofit fundraising: 1. Unified Donor Intelligence Salesforce consolidates donor data from giving history, event attendance, email interactions, advocacy actions, and more into a single, actionable profile. No more siloed spreadsheets—just a 360-degree view of every supporter. 2. AI-Powered Fundraising Salesforce Einstein AI analyzes donor behavior to:✔ Predict future giving potential✔ Identify major gift prospects✔ Recommend personalized engagement strategies 3. Automated, Personalized Outreach From targeted emails to tailored event invites, Salesforce automates communications that resonate—boosting engagement and increasing repeat donations. Scalable for Nonprofits of Any Size Whether you’re a small local charity or a national organization, Salesforce grows with you. Its flexible, cloud-based platform ensures you always have the right tools to meet—and exceed—your fundraising goals. How to Get Started with Salesforce 1. Identify Your Fundraising Pain Points 2. Prepare Your Data Start with a lean migration (e.g., last 3-5 years of giving history). You can always add more later. 3. Implement Core Features Begin with essentials:✔ Donation tracking✔ Moves management✔ Automated reporting 4. Integrate with Existing Tools Connect Salesforce to your:✔ Website✔ Email marketing✔ Event & volunteer management systems 5. Leverage Automation Reduce manual work with automated workflows, acknowledgments, and follow-ups. 6. Train Your Team Salesforce offers extensive training resources—take advantage to maximize adoption. Take Your Fundraising to the Next Level 1. Advanced Donor Segmentation Go beyond basic filters. Use engagement analytics (email opens, event attendance, website behavior) to create dynamic, AI-refined segments. 2. Predictive Analytics with Einstein AI 3. Smarter Email Marketing ✔ Personalize content beyond just names✔ Automate journeys (welcome series, re-engagement campaigns)✔ Track performance in real time 4. Optimize the Donor Lifecycle Map each stage—from first-time donor to loyal advocate—and identify areas to improve retention. 5. Personalized Digital Experiences Integrate Salesforce with your website to customize donation forms, CTAs, and content based on donor profiles. Tectonic: Your Salesforce Fundraising Partner As certified Salesforce nonprofit experts, Tectonic helps organizations unlock the platform’s full potential. We provide: ✔ Custom Salesforce strategy tailored to your goals✔ Seamless implementation & integration✔ Ongoing training & support✔ Expert guidance on AI & automation Partner with Tectonic today and transform your fundraising with Salesforce. Ready to elevate your donor engagement? Contact us to get started. 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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Agentic AI is Here

How IT Leaders Are Deploying Agentic AI to Transform Business Workflows

The next wave of enterprise AI isn’t just about chatbots—it’s about autonomous agents that execute complex workflows end-to-end. Leading CIOs and CTOs are now embedding agentic AI across sales, customer service, finance, and IT operations to drive efficiency, accuracy, and scalability. “We’re not just automating tasks—we’re reimagining how work gets done,” says Kellie Romack, CDIO at ServiceNow. The momentum is undeniable: So where are the biggest impacts? Here’s how forward-thinking execs are deploying AI agents today. 🚀 Top Use Cases for Agentic AI 1. Supercharging Sales & Pipeline Growth “Agentic AI helps sales teams focus on high-potential clients while automating routine follow-ups.” — Jay Upchurch, CIO, SAS 2. Hyper-Personalized Customer Experiences “We cut student research time from 35 minutes to under 3—freeing advisors for deeper mentorship.” — Siva Kumari, CEO, College Possible 3. Self-Healing IT & Security Operations Gartner predicts AI will reduce manual data integration work by 60%. 4. Frictionless Back-Office Automation “We’re targeting repetitive, rules-based workflows first—like finance and procurement.” — Milind Shah, CTO, Xerox 🔑 Key Implementation Insights What’s Working ✅ Start with high-volume, repetitive tasks (e.g., ticket routing, data entry)✅ Prioritize workflows with clean, structured data✅ Use AI for augmentation—not replacement Biggest Challenges ⚠️ Data integration hurdles (55% of leaders cite this as #1 blocker)⚠️ Governance & compliance risks⚠️ Testing non-deterministic AI outputs “The real breakthrough comes when AI agents collaborate across systems—not just operate in silos.” — Kellie Romack, ServiceNow 🔮 The Future: From Assistants to Autonomous Decision-Makers Early adopters see agentic AI evolving in three phases: Salesforce, Microsoft, and IBM are already rolling out agentic frameworks—but only 11% of enterprises have full-scale adoption today. “Soon, thousands of AI agents will work in the background like a digital workforce—always on, always improving.” — Romack Your Move Where could agentic AI eliminate bottlenecks in your workflows? The most successful implementations: The question isn’t if you’ll deploy AI agents—but where they’ll drive the most value first. How is your organization experimenting with agentic AI? Share your insights below! 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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Boost Your Reps' Efficiency with AI-Powered Service Replies

Boost Your Reps’ Efficiency with AI-Powered Service Replies

In today’s demanding customer service game, 86% of reps say expectations on them are higher than ever. Agents shouldn’t waste time searching for answers—they need smart, instant support to deliver exceptional service. Boost Your Reps’ Efficiency with AI-Powered Service Replies. With Salesforce’s Service Replies, reps get AI-generated response suggestions in real time as customer conversations unfold—helping them resolve issues faster while maintaining high satisfaction. This insight covers how Service Replies works, its benefits, and best practices for implementation. What Are Service Replies? Einstein Service Replies is a Salesforce feature that provides contextual, AI-generated response suggestions for customer chats and emails. For live chats, replies are generated instantly, so agents don’t waste time toggling between tabs. Key Features:✅ Real-time AI suggestions – Get instant, relevant replies as chats progress.✅ Grounded in your knowledge base – Responses leverage your articles, FAQs, and records for accuracy.✅ Customizable tone & style – Admins tailor responses using Prompt Builder.✅ Data Libraries integration – AI indexes your knowledge articles and files to generate richer replies. How Service Replies Works Powered by a large language model (LLM), Service Replies: Agents can send suggestions as-is, tweak them, or flag unhelpful ones—ensuring every reply is polished and on-brand. Pro Tip: Keep your knowledge base updated—AI relies on it for accuracy. Why Service Replies Matter 🔹 Faster resolutions – Cuts response time, reducing customer wait.🔹 Consistent messaging – Ensures replies align with company policies.🔹 Reduced agent burnout – Lowers cognitive load, letting reps focus on complex cases.🔹 Data-driven support – Responses are grounded in your trusted sources. Best Practices for Success 1️⃣ Keep knowledge bases current – Regularly update articles to ensure AI accuracy.2️⃣ Track key metrics – Monitor CSAT, response time, and agent adoption to measure impact.3️⃣ Customize for brand voice – Use Prompt Builder to align AI responses with your tone.4️⃣ Train your team – Leverage Trailhead and the Serviceblazer Community to master AI tools. Measuring Success 📊 Agent adoption – Are reps using AI suggestions?📊 Customer satisfaction (CSAT) – Are scores improving?📊 Response time – Are replies faster?📊 Data usage – Are you staying within credit limits? Final Thoughts Service Replies empowers agents with AI-driven efficiency, ensuring quick, consistent, and accurate customer interactions. By integrating this tool with a well-maintained knowledge base, you can enhance productivity, reduce burnout, and elevate customer experiences. Ready to transform your service operations? Start optimizing with Service Replies 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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Mastering AI Prompts

Mastering AI Prompts: OpenAI’s Guide to Optimizing Reasoning Models OpenAI has released an updated prompting guide that reveals how to get the most accurate and useful responses from its reasoning models. As AI becomes more advanced, how you ask questions significantly impacts the quality of answers. Whether you’re a developer, business leader, or researcher, these best practices will help refine your AI interactions. Key Prompting Strategies from OpenAI 1. Simplicity Wins: Keep Prompts Direct Overloading prompts with unnecessary instructions can confuse the model. Instead of micromanaging its reasoning, trust the AI’s built-in logic. ✅ Better:“Analyze sales trends from this dataset.” ❌ Less Effective:“Break down this dataset step-by-step, explain each calculation, and ensure statistical best practices are followed.” 2. Skip the “Think Step by Step” Approach While some believe explicitly asking for reasoning helps, OpenAI found that models already optimize for logic—adding such instructions can backfire. ✅ Better:“What’s 25% of 200?” ❌ Less Effective:“Explain your reasoning step-by-step to calculate 25% of 200.” Need an explanation? Ask for it after getting the answer. 3. Use Delimiters for Complex Inputs When feeding structured data, contracts, or multi-part questions, clear separators prevent misinterpretation. ✅ Better: Copy Summarize the contract below: — [Contract text] — ❌ Less Effective:“Summarize this contract: The first party agrees to…” 4. Limit Context in Retrieval-Augmented Tasks When referencing external documents, only include relevant sections—too much info dilutes accuracy. ✅ Better:“Summarize key points from Sections 2 and 3 of this report.” ❌ Less Effective:“Read this 10-page document and summarize everything.” 5. Define Constraints for Precision The more specific your requirements, the better the output. ✅ Better:“Suggest a $500/month LinkedIn ad strategy for a B2B SaaS startup.” ❌ Less Effective:“Suggest a marketing plan.” 6. Iterate for Better Results If the first response isn’t perfect, refine your prompt with additional details. First Attempt:“Give me startup ideas.” Refined Prompt:“Suggest AI-powered B2B SaaS ideas for small business accounting.” Why This Matters OpenAI’s findings show that optimized prompting = better outputs. Whether you’re integrating AI into apps or using it for research, these techniques ensure smarter, faster, and more reliable responses. Try these strategies today—how will you refine your prompts? 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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Streamline Data Collection from Connected Vehicles and Assets with AWS and Salesforce

Streamline Data Collection from Connected Vehicles and Assets with AWS and Salesforce

Unlock Real-Time Insights with AWS IoT and Salesforce Industry Clouds This guide explains how to gather, process, and distribute data from connected vehicles and industrial assets—such as manufacturing equipment or utility meters—into Salesforce Industry Cloud solutions using Amazon Web Services (AWS). Key AWS IoT Services for Data Collection By leveraging these services, businesses can integrate telemetry data into: Why This Integration Matters Strong customer relationships rely on real-time insights. Automakers, manufacturers, and utility providers can enhance customer interactions by unifying telemetry data with CRM workflows—enabling smarter marketing, sales, and service decisions. Prerequisites To integrate AWS IoT with Salesforce, you’ll need: AWS Services Salesforce Requirements Use Cases 1. Predictive Maintenance with AWS & Salesforce 2. In-Car Notifications 3. On-Demand Vehicle/Asset Health Insights 4. Data-Driven Customer Engagement Solution Architecture Data Flow Overview Implementation Steps 1. Set Up AWS IoT Rules 2. Configure Salesforce Event Handling 3. Enable Real-Time Analytics Conclusion By integrating AWS IoT with Salesforce Industry Clouds, businesses can:✔ Improve operational efficiency with predictive maintenance.✔ Enhance customer experiences through real-time alerts and diagnostics.✔ Drive data-driven decisions with unified analytics. Next Steps: Empower your teams with real-time IoT insights—start building 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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Salesforce analytics insurance

4 Steps to Unlock the Right Marketing Insights

Overwhelmed by Dashboard Data? 4 Steps to Unlock the Right Marketing Insights An effective dashboard should present marketing data clearly and concisely, enabling teams to quickly extract insights and make confident decisions. 4 Steps to Unlock the Right Marketing Insights Turning Data into Action with Trusted Insights Imagine walking into a restaurant with an overwhelming menu—dozens of dishes spanning multiple cuisines, making it difficult to choose. While the food may be good, the sheer volume of options leads to decision fatigue, causing diners to default to familiar choices rather than exploring new possibilities. The same challenge applies to marketing dashboards. When cluttered with excessive metrics, they become difficult to navigate, obscuring key insights rather than revealing them. A well-designed dashboard, like a well-curated menu, should guide users to the most valuable information—helping them act quickly and strategically. The Difference Between Reporting and Insights Many dashboards fall into the trap of displaying every possible metric, but true value comes from actionable insights, not just raw data. Example: A live campaign shows that email conversions outperform social ads. Instead of just noting the discrepancy, an insights-driven dashboard helps marketers diagnose why—perhaps stronger subject lines or better landing page alignment—and adjust social strategies in real time for immediate improvement. 4 Steps to Build Dashboards That Drive Decisions To transform dashboards from data overload into insight engines, follow this structured approach: 1. Define the User Persona Dashboards should cater to specific roles, not broad audiences. Different stakeholders need different insights: A one-size-fits-all dashboard drowns users in irrelevant data. Instead, tailor views to each persona’s core needs. 2. Align with Daily Tasks Collaborate with users to understand how they apply data in their workflows. A well-designed dashboard should: 3. Answer Key Business Questions Every dashboard should directly address the user’s most critical questions, such as: Prioritize KPIs that drive action, like:✔ Impressions (Reach)✔ Click-through rate (CTR) (Engagement)✔ Conversion rate (CVR) (Effectiveness)✔ Revenue per sale (ROI) Supplement these with supporting metrics (e.g., time on site, repeat visits) to uncover deeper trends. 4. Design for Clarity and Impact A great dashboard balances simplicity with depth: Example for Executives: A high-level dashboard showing revenue, CAC, and CLTV by region helps identify growth opportunities. If one region shows strong CLTV, leadership might invest further in similar markets. The Result? Faster, Smarter Decisions By focusing on personas, tasks, key questions, and clarity, marketers can move beyond data overload and unlock real business value. The best dashboards don’t just report numbers—they illuminate the path forward. Ready to streamline your insights? Start by having Tectonic refine one dashboard using these steps—and watch decision-making improve. 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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Natural Language Processing Explained

Exploring 3 Types of Natural Language Processing in Healthcare

Healthcare generates vast amounts of unstructured, text-based data—primarily in the form of clinical notes stored in electronic health records (EHRs). While this data holds immense potential for improving patient outcomes, extracting meaningful insights from it remains a challenge. Natural language processing (NLP) offers a solution by enabling healthcare stakeholders to analyze and interpret this data efficiently. NLP technologies can support population health management, clinical decision-making, and medical research by transforming unstructured text into actionable insights. Despite the excitement around NLP in healthcare—particularly amid clinician burnout and EHR inefficiencies—its two core components, natural language understanding (NLU) and natural language generation (NLG), receive less attention. This insight explores NLP, NLU, and NLG, highlighting their differences and healthcare applications. Understanding NLP, NLU, and NLG While related, these three concepts serve distinct purposes: Healthcare Applications NLP technologies offer diverse benefits across clinical, administrative, and research settings: 1. NLP in Clinical and Operational Use Cases Real-World Examples: 2. NLU for Research & Chatbots While less widely adopted than NLP, NLU shows promise in: 3. NLG for Generative AI in Healthcare Challenges & Barriers to Adoption Despite their potential, NLP technologies face several hurdles: 1. Data Quality & Accessibility 2. Bias & Fairness Concerns 3. Regulatory & Privacy Issues 4. Performance & Clinical Relevance The Future of NLP in Healthcare Despite these challenges, NLP, NLU, and NLG hold tremendous potential to revolutionize healthcare by:✔ Enhancing clinical decision-making✔ Streamlining administrative workflows✔ Accelerating medical research As the technology matures, addressing data, bias, and regulatory concerns will be key to unlocking its full impact. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more 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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Analytics tools like Einstein Analytics can identify patterns and trends in patient data, helping healthcare providers optimize workflows and improve the effectiveness of care delivery.

Healthcare Payers Turn to Data Analytics for Cost Savings and Improved Outcomes

Facing persistent financial and staffing pressures, healthcare payers are increasingly adopting data analytics platforms to streamline operations, reduce costs, and enhance member outcomes. A new April 2025 report from KLAS Research offers its first evaluation of payer experiences with these solutions, highlighting key vendors and emerging trends. The Growing Role of Data Analytics in Payer Operations With healthcare organizations under constant pressure to improve efficiency and decision-making, data analytics tools provide critical visibility into claims data, utilization patterns, and financial performance. These platforms enable payers to: While KLAS’ research in this space is still evolving, the initial report assesses three leading vendors, with plans to expand coverage as more data becomes available. Key Vendor Performances 1. MedInsight – Best in KLAS 2025 (Score: 85.8) 2. MedeAnalytics (Score: 87.1) 3. Clarify Health Solutions 4. Salesforce Health Cloud Looking Ahead: Expanding the Vendor Landscape Additional players like CareJourney (acquired by Arcadia in 2024), Cedar Gate Technologies, and Cognizant are expected to be evaluated in future KLAS reports as more performance data emerges. The Bottom Line As payers seek greater efficiency and data-driven decision-making, analytics platforms are becoming indispensable. While MedInsight and MedeAnalytics lead in early adoption, the competitive landscape is still evolving—making future KLAS insights critical for payer organizations evaluating their options. Next Steps: With the right analytics partner, payers can unlock cost savings, operational efficiencies, and better member outcomes—key priorities in today’s challenging healthcare environment. 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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Autonomous AI Service Agents

The AI Agent Revolution

The AI Agent Revolution: How Tectonic is Unifying Disparate AI Systems for Enterprises AI agents are proliferating at breakneck speed—embedded in platforms, deployed as standalone apps, and built on proprietary or open-source SDKs. Yet as these intelligent systems multiply, enterprises face a critical challenge: getting them to communicate, collaborate, and scale effectively across complex IT environments. Recent moves by Tectonic, Salesforce, and Google Cloud highlight the next frontier of enterprise AI: seamless, cross-platform agent orchestration. We’ve reached an inflection point where human-AI synergy can transform business operations—but only if organizations can unify their agent ecosystems. The AI Agent Collaboration Challenge Today’s enterprises use AI agents for:✔ Salesforce’s Agentforce (CRM automation)✔ Google’s Agentspace (cloud-based workflows)✔ Custom agents (built on Vertex AI, OpenAI, or open-source models) But without interoperability, these agents operate in silos—limiting their potential. Tectonic bridges this gap with secure, enterprise-grade agent orchestration, enabling businesses to: Tectonic and Supported Agent OS: The Glue Holding AI Ecosystems Together Tectonic and Agent Operating Systems (OS) are business-focused platform for orchestrating AI agents across enterprise environments. An “agent operating system” (AOS) is a type of operating system designed to facilitate the development, deployment, and management of AI agents, which are software systems that can act autonomously to achieve goals. AOS systems aim to provide a platform for AI agents to operate efficiently and effectively, offering features like resource management, context switching, and tool integration. AIOS, for example, is a particular implementation of this concept that aims to address the challenges of managing large language model (LLM)-based AI agents How It Works Real-World Use Cases 1. Salesforce + Google Gemini: Smarter CRM Salesforce’s Agentforce now integrates Google Gemini, enabling:🔹 Better RAG (Retrieval-Augmented Generation) for faster, more accurate customer responses🔹 Predictive trend analysis embedded directly in CRM workflows Tectonic’s Role: Deploys multi-agent solutions that turn AI insights into actionable items—like auto-recommending next steps for sales teams. 2. Retail: Unified Customer Experiences A retailer combines: Result: Customers get instant, accurate updates on orders—no manual backend checks required. 3. Financial Services: AI-Powered Risk Analysis Banks use: Outcome: Suspicious transactions trigger automated compliance workflows without leaving Salesforce. Tectonic’s AI Activation Path: From Pilot to Production For enterprises ready to scale AI agents, Tectonic offers a rapid deployment framework:✅ Discovery and Road Mapping – Co-design high-impact use cases✅ Rapid Implementation – Deploy working agents in sandbox environments✅ Pre-Built Industry Libraries – Accelerate time-to-value The Future: Harmonized AI Ecosystems The biggest barrier to AI adoption isn’t technology—it’s fragmentation. With the Agent OS in place, businesses can finally:✔ Break down silos between Salesforce, Google Cloud, and custom AI✔ Automate complex workflows end-to-end✔ Scale AI responsibly with enterprise-grade governance The bottom line? AI agents are powerful alone—but unstoppable when unified. Ready to orchestrate your AI ecosystem?Discover how Tectonic’s Agentforce approach can transform your enterprise AI strategy. 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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Time Series AI

Time Series AI

Key Aspects of Time Series AI 1. Time Series Data Time series data consists of sequential data points recorded at regular intervals, enabling the analysis of trends, seasonality, and patterns over time. This structured format is essential for forecasting, anomaly detection, and other AI-driven analyses. 2. AI Techniques for Time Series Analysis Multiple AI and machine learning techniques are applied to time series data, including: These techniques help in forecasting future values, detecting anomalies, classifying sequences, and imputing missing data. 3. Applications of Time Series AI Time series AI is widely used across industries for: 4. Real-World Examples 5. Benefits of Time Series AI By leveraging AI for time series analysis, businesses and organizations gain a competitive edge through smarter forecasting and automation. 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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Can Grok Talk to Salesforce

Tectonic at Public Sector Partner Summit

Salesforce State & Local Government Partner Summit Event Date: April 29, 2025Hosted By: CarahsoftLocation: New Orleans, LA Key Takeaway With regard to data, analytics, and performance management across State Government EVERY agency says: This invitation only event was a great networking and learning experience. Plus, Brian and Tom had a great time. 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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