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AI Agent Revolution
17May

The Salesforce AI Agent Maturity Model

The Salesforce AI Agent Maturity Model: A Roadmap for Scaling Intelligent Automation With 84% of CIOs believing AI will be as transformative as the internet, strategic adoption is no longer optional—it’s a competitive imperative. Yet many organizations struggle with where to begin, how to scale AI agents, and how to measure success. To help enterprises navigate this challenge, Salesforce has introduced the Agentic Maturity Model, a four-stage framework that guides businesses from basic automation to advanced, multi-agent ecosystems. “While agents can be deployed quickly, scaling them effectively requires a thoughtful, phased approach,” said Shibani Ahuja, SVP of Enterprise IT Strategy at Salesforce. “This model provides a clear roadmap to help organizations progress toward higher levels of AI maturity.” How Leading Companies Are Using the Framework Wiley: Building a Future-Ready AI Foundation “Visionary leadership is essential in today’s rapidly evolving AI landscape,” said Kevin Quigley, Director of Process Improvement at Wiley. “Salesforce’s framework ensures the building blocks we create today will support our long-term AI strategy.” Alpine Intel: Accelerating Efficiency in Insurance “Every minute saved counts in our high-volume claims business,” said Kelly Bentubo, Director of Architecture at Alpine Intel. “This model brings clarity to scaling AI—helping us move from time-saving automations to advanced multi-agent applications.” The Four Levels of Agentic Maturity Level 0: Fixed Rules & Repetitive Tasks (Chatbots & Co-pilots) What it is: Basic automation with no reasoning—think FAQ bots or scripted workflows.Example: A chatbot handling password resets via predefined decision trees. How to Advance to Level 1:✔ Identify rigid processes ripe for AI reasoning.✔ Measure time/cost savings from automation.✔ Start with low-risk, employee-facing agents. Level 1: Information Retrieval Agents What it is: AI that fetches data and suggests actions (but doesn’t act alone).Example: A support agent recommending troubleshooting steps from a knowledge base. How to Advance to Level 2:✔ Shift from recommendations to autonomous actions.✔ Improve data quality and governance.✔ Track metrics like case deflection and CSAT. Level 2: Simple Orchestration (Single Domain) What it is: Agents automating multi-step tasks within one system.Example: Scheduling meetings + sending follow-ups using calendar/email data. How to Advance to Level 3:✔ Choose between specialized agents or a “mega-agent.”✔ Extend capabilities with API integrations.✔ Design scalable architecture for future growth. Level 3: Complex Orchestration (Cross-Domain) What it is: AI coordinating workflows across departments (e.g., sales + service).Example: An agent analyzing CRM, support tickets, and financial data to optimize deals. How to Advance to Level 4:✔ Build a universal communication layer for agents.✔ Implement dynamic agent discovery & governance.✔ Measure ROI via cost savings and revenue impact. Level 4: Multi-Agent Ecosystems What it is: AI teams collaborating across systems with human oversight.Example: Agents processing orders, managing inventory, and routing feedback in real time. Maximizing Value:✔ Strengthen security for ecosystem-wide AI.✔ Develop new business models powered by agent collaboration.✔ Track revenue growth, retention, and operational efficiency. Beyond Technology: Key Implementation Factors “AI success hinges on more than just tech,” notes Ahuja. Organizations must: By addressing these pillars, businesses can accelerate AI adoption—turning experimentation into scalable, measurable value. Contact Tectonic today to harness the power of AI and move along the AI Agent maturity continuum. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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May 17, 2025in Artificial Intelligence, Artificial Intelligence, Data, Enterprise, Salesforce, Technology
Informatica, Agentforce, and Salesforce
16May

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 Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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May 16, 2025in Agentic AI, Data, Enterprise, Salesforce
Agentic AI is Here
11May

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 Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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May 11, 2025in Agentic AI, Data, Enterprise, Salesforce, Snowflake

Salesforce Industry Clouds

Salesforce Industry Clouds: Tailored Solutions for Public Sector Transformation Government-Specific CRM Built for the Digital Era Salesforce Public Sector Solutions (PSS) represents a paradigm shift in government technology, offering purpose-built applications that combine the power of CRM with public sector operational needs. This comprehensive suite enables agencies to modernize constituent services while maintaining rigorous compliance standards. Core Differentiators Public Sector Solutions Architecture 1. Foundation Layer ![Government Cloud Infrastructure] 2. Government Data Model Standard Object Enhanced Capability Case Violation tracking, benefit eligibility Account Citizen/business entity differentiation Inspection Mobile checklist workflows 3. Prebuilt Applications Diagram Code Download License & Permits Dynamic Forms Fee Automation Grants Mgmt Application Portal Disbursement Tracking Key Solution Areas 🆘 Emergency Program Management 📑 License & Permit Management 🔍 Inspection Management 💰 Grants Management Implementation Framework Phased Rollout Approach Add-On Modules Proven Outcomes BioMADE Case StudyChallenge: 9-month grant approval cyclesSolution: PSS Grants Management + DocuSignResults: Local Government Impact python Copy Download # Productivity metrics after PSS adoption print(f”Case resolution time: {before_hrs}hrs → {after_hrs}hrs”) print(f”Constituent satisfaction: {before_score} → {after_score}”) Typical Output:Case resolution time: 72hrs → 18hrsConstituent satisfaction: 62% → 89% Why Governments Choose Salesforce “PSS allowed us to stand up pandemic relief programs in 11 days – something that previously took 11 months.”— State CIO, Northeast U.S. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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May 8, 2025in Data, Mulesoft, Public Sector Solutions, Salesforce, Salesforce Public Sector Solutions, Technology
Create a Service Provider Portal in PSS
07May

Salesforce Industry Clouds: Tailored Solutions for Public Sector Transformation

Salesforce Public Sector Solutions (PSS) represents a paradigm shift in government technology, offering purpose-built applications that combine the power of CRM with public sector operational needs. This comprehensive suite enables agencies to modernize constituent services while maintaining rigorous compliance standards. Core Differentiators Public Sector Solutions Architecture 1. Foundation Layer ![Government Cloud Infrastructure] 2. Government Data Model Standard Object Enhanced Capability Case Violation tracking, benefit eligibility Account Citizen/business entity differentiation Inspection Mobile checklist workflows 3. Prebuilt Applications Diagram Code Download License & Permits Dynamic Forms Fee Automation Grants Mgmt Application Portal Disbursement Tracking Key Solution Areas 🆘 Emergency Program Management 📑 License & Permit Management 🔍 Inspection Management 💰 Grants Management Implementation Framework Phased Rollout Approach Add-On Modules Proven Outcomes BioMADE Case StudyChallenge: 9-month grant approval cyclesSolution: PSS Grants Management + DocuSignResults: Local Government Impact python Copy Download # Productivity metrics after PSS adoption print(f”Case resolution time: {before_hrs}hrs → {after_hrs}hrs”) print(f”Constituent satisfaction: {before_score} → {after_score}”) Typical Output:Case resolution time: 72hrs → 18hrsConstituent satisfaction: 62% → 89% Why Governments Choose Salesforce “PSS allowed us to stand up pandemic relief programs in 11 days – something that previously took 11 months.”— State CIO, Northeast U.S. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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May 7, 2025in Data, Mulesoft, Public Sector Solutions, Salesforce, Salesforce Public Sector Solutions, Technology
AI Adoption Not Even Across the Board
07May

State of AI Adoption in 2024

The State of AI Adoption in 2024: Trends, Impacts, and Industry Shifts AI Goes Mainstream: Adoption Reaches Tipping Point The AI revolution has transitioned from experimentation to enterprise-wide implementation, with adoption rates accelerating across industries. Current data reveals a watershed moment in business technology: Key Adoption Metrics Sector-by-Sector Breakdown Early Adopter Industries (60%+ adoption) Emerging Adopters (30-50% adoption) Late Adopters (<30%) Geographic Note: Colorado, Florida and Utah lead U.S. adoption while Mississippi and Maine trail significantly. The Generative AI Boom The 2023-2024 period saw explosive growth in specific technologies: Proven Business Impact Organizations report tangible benefits from AI integration: The Global Perspective While U.S. adoption lags at 33% (Exploding Topics), international markets show stronger uptake: The Road Ahead Three critical trends emerging: “We’ve passed the inflection point where AI advantage separates market leaders from laggards.”— AI Strategy Report 2024 Organizations that accelerate adoption while addressing ethical, security and workforce challenges will define the next era of competitive advantage. The question is no longer if to adopt AI, but how fast to scale impact. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

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May 7, 2025in Data, Enterprise, Generative AI, Technology
When Will Quantum Computing Be Ready?
02May

When Will Quantum Computing Be Ready?

When Will Quantum Computing Be Ready? The Answer Is More Complex Than You Think Quantum computing doesn’t have a single “launch date”—it’s arriving in stages, with different milestones depending on how you define “availability.” The Quantum Computing Landscape Today Right now, hundreds of quantum computers exist worldwide, deployed by companies like IBM, D-Wave, IonQ, and Quantinuum. They’re accessible via: But today’s quantum machines are mostly used for research, experimentation, and skill-building—not yet for real-world commercial advantage. The Quantum Readiness Spectrum: 4 Key Milestones 1️⃣ Quantum Supremacy (Achieved in Niche Cases) 2️⃣ Quantum Economic Advantage (2025-2027) 3️⃣ Quantum Computational Advantage (2028-2030+) 4️⃣ Quantum Practicality (Ongoing Adoption) What’s Accelerating (or Slowing) Quantum’s Progress? ✅ Positive Signs ⚠️ Remaining Challenges The Bottom Line: When Should Businesses Prepare? 🔹 Now: Experiment with cloud-based quantum access (IBM, AWS, Azure).🔹 2025-2027: Watch for quantum economic advantage in optimization, chemistry, and AI.🔹 2030+: Expect broad commercial impact in finance, logistics, and materials science. “Quantum computing won’t arrive with a bang—it’ll seep into industries, one breakthrough at a time.”— McKinsey Quantum Research, 2024 Want to stay ahead? Start piloting quantum use cases today—before your competitors do. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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May 2, 2025in Google, Salesforce
01May

Salesforce Research Pioneers Enterprise-Grade AI Reliability

Bridging the Gap Between AI Potential and Business Reality Salesforce AI Research has unveiled groundbreaking work to solve one of enterprise AI’s most persistent challenges: the “jagged intelligence” phenomenon that makes AI agents unreliable for business tasks. Their latest findings, published in the inaugural Salesforce AI Research in Review report, introduce three critical innovations to make AI agents truly enterprise-ready. The Jagged Intelligence Problem “Today’s AI can solve advanced calculus but might fail at basic customer service queries. This inconsistency is what we call ‘jagged intelligence’ – and it’s the biggest barrier to enterprise adoption.”— Shelby Heinecke, Senior AI Research Manager Key Findings: Three Pillars of Enterprise AI Reliability 1. SIMPLE Benchmark: Testing What Actually Matters 225 real-world business questions that reveal an AI’s true operational readiness: Why it matters: Unlike academic benchmarks, SIMPLE evaluates:✅ Practical reasoning✅ Consistency across repetitions✅ Business context understanding Early Results: Top models score 89% on coding tests but just 62% on SIMPLE. 2. ContextualJudgeBench: Fixing the AI Judge Problem When AIs evaluate other AIs, how do we know the judges are reliable? Salesforce’s solution: Evaluation Criteria Traditional Benchmarks ContextualJudgeBench Assessment Depth Single-score output 2,000+ response pairs Bias Detection None Measures rater consistency Enterprise Focus General knowledge Business decision-making Impact: Reduces “hallucinated” evaluations by 40% in testing. 3. CRMArena: The First AI Agent Proving Ground A specialized framework testing AI agents on real CRM tasks: Test Categories Sample Results: python Copy Download { “Agent”: “Einstein_Service_Pro”, “Task”: “Prioritize 50 support cases”, “Accuracy”: 92%, “Speed”: 3.2 sec/case, “Consistency”: 88% } Enterprise Benefit: Finally answers “Which AI agent actually works for my sales team?” Under-the-Hood Breakthroughs SFR-Embedding v2 SFR-Guard AI watchdog models that monitor:🔒 Toxicity🔒 Prompt injections🔒 Data leakage xLAM Updates TACO Models Generates chains of thought-and-action for complex workflows like: Why This Matters for Businesses “These aren’t flashy demos—they’re the industrial-grade foundations for AI that actually works in your ERP, CRM, and service systems,” explains Chief Scientist Silvio Savarese. Immediate Applications: What’s Next:Salesforce will open-source SIMPLE and expand CRMArena to 50+ industry-specific tasks by EOY 2024. “We’re not chasing artificial general intelligence—we’re building enterprise general intelligence: AI that’s boringly reliable where it matters most.”— Salesforce AI Research Team Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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May 1, 2025in Data, Enterprise, Salesforce
Changes to Salesforce permissions
29Apr

Changes to Salesforce Permission Sets

Salesforce is phasing out permissions on profiles in favor of permission sets and permission set groups for a more flexible and manageable user access model. This shift aims to simplify user management, improve data security, and streamline access control. By 2026, profiles will be limited to basic settings like login hours, while permissions will be managed primarily through permission sets.  Here’s a more detailed look at the changes: Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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April 29, 2025in Data
Healthcare Cybersecurity Challenges Persist
28Apr

Healthcare Cybersecurity Challenges Persist

Healthcare Cybersecurity Challenges Persist as Sector Struggles to Shift from Reactive to Proactive Strategies Healthcare organizations of all sizes continue to face significant challenges in addressing systemic cybersecurity risks, with new benchmarking data revealing that the industry remains largely reactive rather than proactive in its approach. The findings come from the 2025 Healthcare Cybersecurity Benchmarking Study, a collaborative effort by KLAS Research, Censinet, the American Hospital Association (AHA), the Health Information Sharing and Analysis Center (H-ISAC), the Healthcare and Public Health Sector Coordinating Council (HSCC), and the Scottsdale Institute. The study gathered responses from 69 healthcare and payer organizations between September and December 2024, assessing their alignment with key cybersecurity frameworks, including: Key Findings: Strong Response & Recovery, but Gaps in Prevention & Risk Management 1. Persistent Focus on Reactive Measures Consistent with past years, healthcare organizations reported high coverage in the “Respond” and “Recover” functions of the NIST CSF 2.0, indicating strong incident response and disaster recovery capabilities. However, long-term recovery planning lags behind immediate response efforts, suggesting room for improvement. “As cyber threats grow, healthcare organizations are preparing for when—not if—they will face a breach, emphasizing incident response and business continuity strategies,” the study noted. 2. Critical Gaps in Supply Chain & Asset Management Under the NIST CSF, the lowest coverage areas were: This is particularly concerning given the rising number of third-party breaches impacting healthcare. 3. Cybersecurity Insurance Benefits from Framework Adoption Organizations implementing the NIST CSF saw slower growth in cybersecurity insurance premiums, reinforcing the financial benefits of proactive risk management. 4. Emerging AI Risk Management Efforts Adoption of the NIST AI RMF remains in early stages, with many organizations still establishing governance structures for AI-related risks. 5. HICP & HPH CPG Findings Align with Past Trends Moving from Reactive to Proactive Security While progress has been made, the study highlights that greater adherence to leading cybersecurity frameworks can help healthcare organizations transition to a more proactive security posture, reducing risk and improving resilience. “The healthcare sector must prioritize foundational cybersecurity practices—particularly in supply chain and asset management—to mitigate escalating threats,” the report concluded. Final Takeaway:Healthcare cybersecurity remains heavily reactive, but organizations that invest in comprehensive risk management, third-party oversight, and AI governance can better protect patient data and reduce long-term vulnerabilities. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

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April 28, 2025in Data, Life Sciences Cloud, Salesforce Health and Life Sciences Solutions
SaaS Data Protection from Own
24Apr

Salesforce Integrates Own Co. Capabilities

Salesforce Integrates Own Co. Capabilities to Strengthen Data Resilience, Security, and AI Readiness Salesforce has fully integrated Own Co.’s data backup, recovery, and security solutions into its platform, equipping partners and customers with enhanced tools for data resilience, compliance, and security—critical foundations as businesses adopt AI-driven solutions. Marla Hay, Vice President of Product Management for Security, Privacy, and Data Management at Salesforce, emphasized in an interview with CRN that these new capabilities are essential as partners guide customers through AI adoption. “Before launching any major AI initiative, ensuring robust data backup and hygiene is critical,” Hay said. “With AI and autonomous agents, the quality of insights depends entirely on the integrity of your data. These new tools help businesses minimize risk while maximizing AI’s potential.” Key Enhancements for AI and Security The integration empowers solution providers to: “Clean, well-managed data isn’t just about compliance—it accelerates operations, enhances customer experiences, and ensures accuracy,” Hay added. Salesforce announced its acquisition of Own Co. in September 2023, bringing over 7,000 customers into its ecosystem. The newly integrated features include: 1. Secure Data Masking & Sandbox Testing 2. Enhanced Monitoring & Threat Detection 3. Robust Backup & Recovery 4. AI-Ready Data Insights with Salesforce Discover 5. Cost-Efficient Data Archiving Why This Matters for AI Adoption As businesses increasingly rely on AI agents and predictive analytics, ensuring data integrity, security, and recoverability is non-negotiable. Salesforce’s integration of Own Co.’s capabilities provides a low-risk pathway to cleaner, more resilient data—ultimately leading to: For partners and customers, these enhancements mean smoother AI deployments, reduced risk, and better business outcomes. Interested in leveraging these new capabilities? Contact Tectonic today. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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April 24, 2025in Agentforce Platform, Data, Salesforce, Salesforce Data Cloud, Salesforce Shield, Salesforce Tableau

Unlocking the Power of Agentic AI with a Strong API Strategy

IT leaders are embracing agentic AI at an unprecedented pace, but success depends on the strength of the APIs that power these intelligent agents. According to a recent MuleSoft survey, 97% of IT leaders in the Asia-Pacific region have already implemented or plan to deploy AI agents within the next two years. However, fully harnessing this technology requires more than just AI adoption—it demands a well-structured API strategy. APIs: The Foundation of Effective AI Agents Andrew Comstock, Senior Vice President and General Manager of MuleSoft at Salesforce, emphasizes that APIs must do more than just provide data access—they need to embody business processes. “If APIs are merely access points to data, AI agents will have information, but they won’t have the context needed to execute complex tasks,” Comstock explains. To maximize AI capabilities, APIs must integrate business logic, enabling agents to perform real-world functions beyond simple queries. For instance, an AI agent assisting with hotel reservations must not only retrieve room availability but also apply customer loyalty rewards and process transactions seamlessly. Bridging the Gap with Actionable API Instructions For AI agents to function effectively, they need clear instructions on how to use APIs. In Salesforce’s agentic AI platform, Agentforce, metadata-powered “action instructions” provide natural language descriptions of API functions, helping agents understand how to interact with them. To further enhance this capability, MuleSoft has introduced Topic Centre, which allows organizations to annotate APIs with these action instructions. This ensures APIs can be readily used by AI agents while maintaining their traditional functionality for other applications. “With Topic Centre, APIs serve dual purposes—they support existing systems while also being immediately accessible to AI-powered solutions like Agentforce,” Comstock adds. The Future of AI-Driven Business Operations AI agents are already being used for simple tasks like answering document-related queries, but their true potential lies in executing complex business operations. As AI adoption accelerates, companies must rethink their API strategies, ensuring that APIs are not just data access points but intelligent pathways to automated decision-making and seamless customer interactions. With solutions like MuleSoft and Agentforce, businesses can build AI-driven workflows that improve efficiency, enhance customer experiences, and drive competitive advantage in the digital economy. 🚀 Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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April 19, 2025in Agentic AI, Data, Mulesoft, Salesforce, Technology
enterprise ai rag
18Apr

Enterprise AI RAG

Retrieval-Augmented Generation (RAG): Enhancing AI with External Knowledge Large language models (LLMs) can answer nearly any question—but their responses aren’t always based on verified or up-to-date information. Retrieval-augmented generation (RAG) bridges this gap by enabling AI applications to access external knowledge sources, making it invaluable for enterprises leveraging proprietary data. By integrating RAG into their AI strategy, organizations can deliver accurate, secure, and compliant AI-powered solutions grounded in real-time, internal knowledge. To get started, explore RAG’s architecture, benefits, and challenges, then follow a six-step best practices checklist for enterprise adoption. How RAG Works In a standard LLM, responses are generated solely from pre-trained data, limiting accuracy to the model’s training cutoff date and excluding proprietary business knowledge. RAG enhances this process in three stages: Why Enterprises Need RAG RAG overcomes three key LLM limitations: Challenges to Address: 6 Best Practices for Implementing RAG Integrating RAG into Your AI Roadmap Start with high-impact use cases like customer support, internal knowledge bases, or compliance documentation. Take a phased approach, building expertise in data preparation, embeddings, and prompt engineering. Complement RAG with fine-tuning and supervised learning for a robust, enterprise-ready AI solution. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

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April 18, 2025in Data, Enterprise
gettectonic.com