Chatbots Archives - gettectonic.com

Revolutionizing Healthcare with Salesforce Einstein AI

Imagine reducing patient no-shows by 30%, cutting administrative workload in half, and delivering hyper-personalized care—all powered by AI. This isn’t the future of healthcare; it’s what leading providers are achieving today with Salesforce Einstein. Why Healthcare Needs AI Now More Than Ever With rising patient expectations and staffing shortages, healthcare organizations must work smarter—not harder. Salesforce Einstein integrates predictive analytics, intelligent automation, and AI-driven insights directly into clinical and administrative workflows to: ✔ Prevent patient risks before they escalate✔ Automate repetitive tasks wasting staff time✔ Personalize care at scale✔ Forecast operational needs with precision But success depends on strategic implementation—which is where Salesforce healthcare consultants make the difference. How Salesforce Einstein Transforms Healthcare 1. Predictive Patient Risk Scoring 🔍 Identifies high-risk patients (readmissions, no-shows, sepsis) using real-time EHR, claims, and behavioral data. ✅ Proven Impact: Cleveland Clinic reduced missed appointments by 25% using AI-driven reminders. 2. Intelligent Workflow Automation 🤖 Auto-assigns cases, schedules follow-ups, and verifies insurance—freeing staff for patient care. ✅ Proven Impact: A multi-location practice cut case handling time by 40% with smart routing. 3. AI-Powered Virtual Assistants 💬 Chatbots handle 80% of routine queries (appointments, billing, FAQs), escalating only complex issues. ✅ Proven Impact: Johns Hopkins reduced call center wait times by 50%. 4. Real-Time Clinical Decision Support ⚠️ Alerts care teams to critical changes (e.g., abnormal labs, medication conflicts) for faster intervention. ✅ Proven Impact: A hospital network improved early sepsis detection by 35%. 5. Hyper-Personalized Patient Engagement 📲 Tailors communications (SMS, email, portal) based on individual preferences and behaviors. ✅ Proven Impact: Mayo Clinic boosted care plan adherence by 20% with personalized journeys. Real-World Success Stories Organization Use Case Result Kaiser Permanente AI-driven staffing forecasts 15% fewer overtime hours Belle Medical Geo-targeted patient promotions 30% higher campaign conversion Johns Hopkins AI triage for patient inquiries 50% faster case resolution The Key to Maximizing ROI? Expert Implementation Salesforce Einstein’s power comes from strategic deployment. The right consulting partner ensures: 🔹 Seamless integration with EHRs, telehealth, and legacy systems🔹 HIPAA-compliant AI workflows🔹 Change management for staff adoption🔹 Ongoing optimization based on real-world performance Tectonic’s healthcare-specialized Salesforce consultants have helped providers: Ready to Transform Your Healthcare Organization? ⚡ Book a free consultation to discover how Salesforce Einstein can: Let’s build a smarter, AI-powered healthcare system—together. Contact Tectonic today! Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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AI Agents and Open APIs

The Future of AI Agents

The Future of AI Agents: A Symphony of Digital Intelligence Forget simple chatbots—tomorrow’s AI agents will be force multipliers, seamlessly integrating into our workflows, anticipating needs, and orchestrating complex tasks with near-human intuition. Powered by platforms like Agentforce (Salesforce’s AI agent builder), these agents will evolve in five transformative ways: 1. Beyond Text: Multimodal AI That Sees, Hears, and Understands Today’s AI agents mostly process text, but the future belongs to multimodal AI—agents that interpret images, audio, and video, unlocking richer, real-world applications. How? Neural networks convert voice, images, and video into tokens that LLMs understand. Salesforce AI Research’s xGen-MM-Vid is already pioneering video comprehension. Soon, agents will respond to spoken commands, like:“Analyze Q2 sales KPIs—revenue growth, churn, CAC—summarize key insights, and recommend two fixes.”This isn’t just about speed; it’s about uncovering hidden patterns in data that humans might miss. 2. Agent-to-Agent (A2A) Collaboration: The Rise of AI Teams Today’s AI agents work solo. Tomorrow, specialized agents will collaborate like a well-oiled team, multiplying efficiency. Human oversight remains critical—not for micromanagement, but for ethics, strategy, and alignment with human goals. 3. Orchestrator Agents: The AI “Managers” of Tomorrow Teams need leaders—enter orchestrator agents, which coordinate specialized AIs like a restaurant GM oversees staff. Example: A customer service request triggers: The orchestrator integrates all inputs into a seamless, on-brand response. Why it matters: Orchestrators make AI systems scalable and adaptable. New tools? Just plug them in—no rebuilds required. 4. Smarter Reasoning: AI That Thinks Like You Today’s AI follows basic commands. Tomorrow’s will analyze, infer, and strategize like a human colleague. Example: A marketing AI could: Key Advances: As Anthropic’s Jared Kaplan notes, future agents will know when deep reasoning is needed—and when it’s overkill. 5. Infinite Memory: AI That Never Forgets Current AI has the memory of a goldfish—each interaction starts from scratch. Future agents will retain context across sessions, like a human recalling notes. Impact: The Bottom Line The next generation of AI agents won’t just assist—they’ll augment human potential, turning complex workflows into effortless collaborations. With multimodal perception, team intelligence, advanced reasoning, and infinite memory, they’ll redefine productivity across industries. The future isn’t just AI—it’s AI working for you, with you, and ahead of 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 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 Rise of AI Agents

The Rise of AI Agents: How Autonomous AI is Reshaping Business As artificial intelligence advances, so does the terminology around it. The term “AI agent” is gaining traction as generative AI becomes deeply embedded in business operations. Unlike traditional AI tools that follow rigid scripts, AI agents are autonomous programs capable of learning, adapting, and executing tasks with minimal human intervention. Why AI Agents Are Booming The rapid expansion of large language models (LLMs) has slashed the cost of developing AI agents, fueling a surge in startups specializing in industry-specific AI solutions. According to Stripe’s 2024 research, AI startups achieved record revenue growth last year, signaling a shift from generic AI tools (like ChatGPT) to verticalized AI agents tailored for specific sectors. In their annual letter, Stripe co-founders Patrick and John Collison noted: “Just as SaaS evolved from horizontal platforms (Salesforce) to vertical solutions (Toast), AI is following the same path. Industry-specific AI agents ensure businesses fully harness LLMs by integrating contextual data and workflows.” AI Agents in Action: Industry Success Stories From manufacturing to finance, AI agents are already delivering tangible benefits: David Lodge, VP of Engineering at IBS Software, explains: “Fragmented systems limit AI’s potential. Unifying CRM, PMS, and loyalty data into a single platform is critical for AI to drive real transformation.” Hospitality’s AI Revolution: Breaking Down Data Silos Hotels like Wyndham and IHG have partnered with Salesforce to consolidate millions of guest records, enabling AI agents to deliver hyper-personalized service. In February 2025, Apaleo launched an AI Agent Marketplace for hospitality, allowing hotels to integrate AI solutions without costly system overhauls. Case Study: mk Hotels The Future: Autonomous Agents Redefining Workflows In September 2024, Salesforce introduced Agentforce, a platform for building secure, data-grounded AI agents that automate complex workflows. Jan Erik Aase, Partner at ISG, predicts: “The shift to agent-driven enterprises isn’t just technological—it’s cultural. As AI agents grow smarter, they’ll redefine customer interactions and decision-making.” Key Takeaways The AI agent revolution is here—and businesses that embrace it will lead the next wave of productivity and innovation. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more 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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Why Salesforce Release Management Matters

Salesforce Summer ’25 Release

Salesforce Summer ’25 Release: Key Updates & What You Need to Know The Salesforce Summer ’25 Release is here—packed with AI-powered automation, critical deprecations, and game-changing enhancements to Flow, Agentforce, and approvals. Whether you’re an admin, developer, or business leader, these updates will impact how you work on the platform. Let’s break down the biggest changes. 1. The End of Legacy Automation Tools Salesforce is officially sunsetting older automation features, pushing users toward next-gen solutions. Key Deprecations: 2. Flow Gets a Major Upgrade Flow is now faster, more intuitive, and packed with new features—making it the go-to automation tool. New Enhancements: ✔ Redesigned Flow Builder – Faster loading, responsive layouts, and mobile/tablet previews.✔ Rich In-Line Email Editor – No more external templates! Format emails directly in Flow with merge fields, colors, and styling.✔ Debug Fault Paths – Test error-handling logic for more reliable automations.✔ Reusable Flow Templates – Save and reuse common flow patterns across your org. Biggest Game-Changer: Flow-Based Approvals Salesforce is phasing out classic approval processes in favor of Flow-based approvals (though the old tool isn’t retired yet). Why switch? Action Item: Start testing Flow-based approvals in sandbox. 3. Agentforce Gets Smarter & More Versatile Salesforce’s AI-powered Agentforce is expanding beyond customer service into HR, field service, and sales. Key Upgrades: 🔹 Embed LWCs in Chatbots – Users can now interact with buttons, calendars, and custom UIs inside chat.🔹 New HR & Employee Service Templates – Automate onboarding, time-off requests, and internal workflows.🔹 Field Service AI Upgrades – Agents now: Action Item: Explore Agentforce for internal use cases (HR, IT, field service). 4. Admin Productivity Boosters Salesforce is making permissions and user management easier than ever. New Admin Features: 🔸 Bulk Object Permissions in Object Manager – No more jumping between permission sets!🔸 Enhanced Permission Set Summaries – Now includes tab access, public groups, and queues.🔸 Improved User Access Reports – Track permissions during onboarding/offboarding. 5. Release Timeline & Checklist When is Summer ‘25 Rolling Out? Your Summer ‘25 Prep Checklist ✅ Migrate off Workflow Rules & Process Builder → Move to Flow.✅ Audit API integrations → Ensure they use v31+.✅ Test outbound messaging → Confirm it works with 20s timeout.✅ Pilot Flow-based approvals → Start rebuilding in sandbox.✅ Explore Agentforce upgrades → Test chat LWC embeds & Siri voice.✅ Simplify permissions → Use bulk object permissions. Need Help Navigating These Changes? Transitioning to Flow, Agentforce, or new APIs can be complex. Our Salesforce experts can help you: Contact us today to get release-ready! Final Thought Salesforce is doubling down on AI, automation, and modern UX. The message is clear: The future is Flow, Agentforce, and clean data. Start preparing now! 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 Promise of AI in Health Outcomes

10 AI Healthcare Trends Shaping the Future

10 AI Healthcare Trends Shaping the Future (2025 & Beyond) Artificial intelligence is transforming healthcare at an unprecedented pace. With a projected 49% CAGR through 2030 (MarketsandMarkets) and generative AI accelerating innovation, hospitals, clinics, and insurers are integrating AI into clinical workflows, diagnostics, and operations. Here are the 10 biggest AI healthcare trends to watch: 1. AI Chatbots for Patient Engagement “AI chatbots cut our call center volume by 30% while improving response times.” —Jordan Archer, COO, Tryon Medical Partners 2. AI-Powered Clinical Documentation 3. Unstructured Data Analysis 4. AI Radiology & Imaging Assistants 5. Robotic Surgery & Automation 6. AI in Physical Therapy 7. AI-Generated Fitness & Wellness Plans 8. Automated Revenue Cycle Management 9. Predictive Supply Chain Optimization 10. AI-Driven Business Strategy Challenges: Equity & Adoption While AI offers immense potential, smaller clinics and rural hospitals risk falling behind due to: “We must ensure equitable access—AI shouldn’t just benefit large health systems.” —Dr. Margaret Lozovatsky, AMA The Future of AI in Healthcare ✅ 2025-2030: AI becomes standard in EHRs, diagnostics, and surgery✅ Generative AI drafts treatment plans, research papers, and insurance appeals✅ Regulatory frameworks evolve to ensure safety & fairness Bottom Line: AI isn’t replacing doctors—it’s empowering them to work smarter, faster, and more precisely. Which trend will impact your organization most? 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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Grok 3 Model Explained

Grok 3 Model Explained: Everything You Need to Know xAI has introduced its latest large language model (LLM), Grok 3, expanding its capabilities with advanced reasoning, knowledge retrieval, and text summarization. In the competitive landscape of generative AI (GenAI), LLMs and their chatbot services have become essential tools for users and organizations. While OpenAI’s ChatGPT (powered by the GPT series) pioneered the modern GenAI era, alternatives like Anthropic’s Claude, Google Gemini, and now Grok (developed by Elon Musk’s xAI) offer diverse choices. The term grok originates from Robert Heinlein’s 1961 sci-fi novel Stranger in a Strange Land, meaning to deeply understand something. Grok is closely tied to X (formerly Twitter), where it serves as an integrated AI chatbot, though it’s also available on other platforms. What Is Grok 3? Grok 3 is xAI’s latest LLM, announced on February 17, 2025, in a live stream featuring CEO Elon Musk and the engineering team. Musk, known for founding Tesla, SpaceX, and acquiring Twitter (now X), launched xAI on March 9, 2023, with the mission to “understand the universe.” Grok 3 is the third iteration of the model, built using Rust and Python. Unlike Grok 1 (partially open-sourced under Apache 2.0), Grok 3 is proprietary. Key Innovations in Grok 3 Grok 3 excels in advanced reasoning, positioning it as a strong competitor against models like OpenAI’s o3 and DeepSeek-R1. What Can Grok 3 Do? Grok 3 operates in two core modes: 1. Think Mode 2. DeepSearch Mode Core Capabilities ✔ Advanced Reasoning – Multi-step problem-solving with self-correction.✔ Content Summarization – Text, images, and video summaries.✔ Text Generation – Human-like writing for various use cases.✔ Knowledge Retrieval – Accesses real-time web data (especially in DeepSearch mode).✔ Mathematics – Strong performance on benchmarks like AIME 2024.✔ Coding – Writes, debugs, and optimizes code.✔ Voice Mode – Supports spoken responses. Previous Grok Versions Model Release Date Key Features Grok 1 Nov. 3, 2023 Humorous, personality-driven responses. Grok 1.5 Mar. 28, 2024 Expanded context (128K tokens), better problem-solving. Grok 1.5V Apr. 12, 2024 First multimodal version (image understanding). Grok 2 Aug. 14, 2024 Full multimodal support, image generation via Black Forest Labs’ FLUX. Grok 3 vs. GPT-4o vs. DeepSeek-R1 Feature Grok 3 GPT-4o DeepSeek-R1 Release Date Feb. 17, 2025 May 24, 2024 Jan. 20, 2025 Developer xAI (USA) OpenAI (USA) DeepSeek (China) Reasoning Advanced (Think mode) Limited Strong Real-Time Data DeepSearch (web access) Training data cutoff Training data cutoff License Proprietary Proprietary Open-source Coding (LiveCodeBench) 79.4 72.9 64.3 Math (AIME 2024) 99.3 87.3 79.8 How to Use Grok 3 1. On X (Twitter) 2. Grok.com 3. Mobile App (iOS/Android) Same subscription options as Grok.com. 4. API (Coming Soon) No confirmed release date yet. Final Thoughts Grok 3 is a powerful reasoning-focused LLM with real-time search capabilities, making it a strong alternative to GPT-4o and DeepSeek-R1. With its DeepSearch and Think modes, it offers advanced problem-solving beyond traditional chatbots. Will it surpass OpenAI and DeepSeek? Only time—and benchmarks—will tell.  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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AI Agent Revolution

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 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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AI evolves with tools like Agentforce and Atlas

Salesforce Doubles Down on Agentic AI to Transform Partner Ecosystem

Salesforce is making a major push into agentic artificial intelligence with its newest offering, Agentforce for Partner Community, now integrated directly into the Salesforce Partner Community platform, according to Channel Futures. Lynne Zaledonis, EVP of Customer Success and Partner Marketing at Salesforce, hailed the tool as a “game-changing innovation” that enables consulting and systems integrator partners to tap into round-the-clock AI support, streamline operations, and accelerate case resolution through real-time conversational assistance. Unlike traditional chatbots, Agentforce doesn’t just fetch technical and programmatic answers—it can also execute actions, such as extending Trial Orgs. By tackling workflow inefficiencies and breaking down data silos, Salesforce aims to equip partners with the tools needed to guide clients through every stage of AI adoption, from initial assessment to full implementation. As consulting partners roll out Agentforce, Zaledonis noted that this shift toward AI-driven operations is reshaping business models and demanding new skill sets. To support partners in this transition, Salesforce is rolling out workshops, certifications, and strategic playbooks—helping them adapt, monetize, and spearhead the move toward an AI-powered future. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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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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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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Biggest Mistakes Universities Make When Using Salesforce

Biggest Mistakes Universities Make When Using Salesforce

The Biggest Mistakes Universities Make When Using Salesforce (And How to Fix Them) Many universities invest in Salesforce for higher education to improve student engagement, streamline operations, and boost fundraising—but struggle to see meaningful results. Without the right strategy, institutions face scattered data, low adoption, and inefficiencies, turning Salesforce into just another system to manage rather than a transformative tool. The good news? These challenges are avoidable. In this insight, we’ll explore the most common Salesforce mistakes in higher education and how to fix them—helping your university maximize ROI and create a seamless experience for students, staff, and alumni. Salesforce Education Cloud: A Quick Overview Salesforce Education Cloud is a powerful CRM platform designed for universities, colleges, and K-12 schools. It helps institutions: Yet, many institutions fail to leverage its full potential due to poor implementation, lack of training, or misaligned strategies. 11 Common Salesforce Mistakes in Higher Ed (And How to Solve Them) 1. No Clear Strategy or Goals Problem: Jumping into Salesforce without a plan leads to disconnected teams, wasted resources, and unclear ROI. Solution:✔ Define university-wide objectives (e.g., improving student retention, increasing alumni donations).✔ Establish a governance team to align Salesforce with institutional goals.✔ Prioritize key initiatives and track measurable outcomes. 2. Lack of Stakeholder Buy-In Problem: Without leadership and faculty support, adoption stalls or becomes siloed. Solution:✔ Engage decision-makers early in planning.✔ Assign cross-functional champions to drive adoption.✔ Provide training & clear value propositions for each department. 3. No Clear Ownership Problem: When no one “owns” Salesforce, data decays, processes break, and updates lag. Solution:✔ Form a centralized Salesforce admin team.✔ Assign department leads to oversee usage.✔ Define clear roles & accountability for system maintenance. 4. Siloed Implementation Problem: Departments use Salesforce separately, creating data fragmentation. Solution:✔ Use Education Data Architecture (EDA) for a unified student view.✔ Integrate with Student Information Systems (SIS).✔ Ensure admissions, advising, and alumni teams share data seamlessly. 5. Poor Data Governance Problem: Inconsistent data entry leads to duplicates, errors, and unreliable reports. Solution:✔ Standardize data entry rules across teams.✔ Use Salesforce duplicate management tools.✔ Create real-time dashboards for accurate insights. 6. Underusing Self-Service Portals Problem: Over-reliance on staff for basic tasks (e.g., FAQs, event sign-ups). Solution:✔ Deploy Experience Cloud for student/alumni self-service.✔ Implement AI chatbots (Einstein Copilot) for instant support.✔ Build a knowledge base for common inquiries. 7. Inadequate Training & Support Problem: Staff avoid Salesforce because they don’t know how to use it. Solution:✔ Offer ongoing training programs.✔ Assign in-house Salesforce super-users.✔ Provide resources for new features & updates.✔ Employ a dedicated Salesforce Solutions Provider..✔ Utilize a Salesforce Managed Services Provider. 8. Ignoring Mobile Optimization Problem: Students expect mobile access—but many portals are desktop-only. Solution:✔ Enable the Salesforce Mobile App.✔ Use push notifications for deadlines & events.✔ Ensure responsive design for all student portals. 9. Misaligned Reporting & KPIs Problem: Departments track different metrics, making progress hard to measure. Solution:✔ Standardize university-wide KPIs (e.g., enrollment rates, alumni engagement).✔ Use Salesforce dashboards for real-time insights.✔ Align reports with strategic goals. 10. Not Using AI & Automation Problem: Manual processes slow down admissions, student support, and fundraising. Solution:✔ Use Einstein AI to predict at-risk students.✔ Automate student communications & follow-ups.✔ Deploy AI chatbots for instant responses.✔ Integrate Salesforce Agentforce. 11. Falling Behind on Salesforce Updates Problem: Missing out on new AI features, automations, and best practices. Solution:✔ Follow Salesforce Trailhead & webinars.✔ Attend Education Summit & industry events.✔ Assign a team to evaluate & implement new tools. Maximizing Salesforce ROI in Higher Education By avoiding these mistakes, universities can:✅ Improve student engagement & retention✅ Streamline admissions & operations✅ Boost alumni fundraising✅ Make data-driven decisions The key? Strategy, training, integration, and innovation. Is your university getting the most out of Salesforce? Let’s optimize your approach. 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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Real-World AI

AI in the Travel Industry

AI in Travel: How the Industry is Transforming with Intelligent Technology The travel sector has long been at the forefront of AI adoption, with airlines, hotels, and cruise lines leveraging advanced analytics for decades to optimize pricing and operations. Now, as artificial intelligence evolves—particularly with the rise of generative AI—the industry is entering a new era of smarter automation, hyper-personalization, and seamless customer experiences. “AI and generative AI have emerged as truly disruptive forces,” says Kartikey Kaushal, Senior Analyst at Everest Group. “They’re reshaping how travel businesses operate, compete, and serve customers.” According to Everest Group, AI adoption in travel is growing at 14-16% annually, driven by demand for efficiency and enhanced customer engagement. But as adoption accelerates, the industry must balance automation with the human touch that travelers still value. 10 Key AI Use Cases in Travel & Tourism 1. Dynamic Pricing Optimization Travel companies pioneered AI-driven dynamic pricing, adjusting fares based on demand, competitor rates, weather, and events. Now, AI takes it further with hyper-personalized pricing—tracking user behavior (like repeated searches) to offer tailored deals. 2. Customer Sentiment Analysis AI evaluates traveler emotions through voice tone, reviews, and social media, enabling real-time adjustments. Hotels and airlines use sentiment tracking to improve service before complaints escalate. 3. Automated Office Tasks Travel agencies use generative AI (like ChatGPT) to draft emails, marketing content, and customer onboarding materials, freeing staff for high-value interactions. 4. Self-Service & Customer Empowerment AI-powered chatbots, itinerary builders, and booking tools let travelers plan trips independently. Some even bring AI-generated plans to agents for refinement—blending automation with human expertise. 5. Operational Efficiency & Asset Management Airlines and cruise lines deploy AI for:✔ Predictive maintenance (reducing downtime)✔ Route optimization (cutting fuel costs)✔ Staff scheduling (improving productivity) 6. AI-Powered Summarization Booking platforms use generative AI to summarize hotel reviews, local attractions, and FAQs—delivering concise, personalized travel insights. 7. Frictionless Travel Experiences From contactless hotel check-ins to AI-driven real-time recommendations (restaurants, shows, transport), AI minimizes hassles and enhances convenience. 8. AI Agents for Problem-Solving Agentic AI autonomously resolves disruptions—like rebooking flights, rerouting luggage, and updating hotels—without human intervention. 9. Enhanced Personalization Without “Creepiness” AI tailors recommendations based on past behavior but must avoid overstepping. The challenge? “A customer segment of one”—balancing customization with privacy. 10. Risk & Compliance Management AI helps navigate data privacy laws (GDPR, CCPA) and detects fraud, but companies must assign clear accountability for AI-driven decisions. Challenges in AI Adoption for Travel The Future: AI + Human Collaboration The most successful travel companies will blend AI efficiency with human empathy, ensuring technology enhances—not replaces—the art of travel. “The goal isn’t full automation,” says McKinsey’s Alex Cosmas. “It’s using AI to make every journey smoother, smarter, and more personal.” As AI evolves, so will its role in travel—ushering in an era where smarter algorithms and human expertise work together to create unforgettable experiences. What’s Next? The journey has just begun. 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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Second Wave of AI Agents

Second Wave of AI Agents

The “second wave” of AI agents refers to the evolution of AI beyond simple chatbots and into more sophisticated, autonomous systems that can plan, execute, and deliver results independently, often leveraging large language models (LLMs). These agents are characterized by their ability to interact with other applications, interpret the screen, fill out forms, and coordinate with other AI systems to achieve a desired outcome. They are also seen as a significant step beyond the first wave of AI, which primarily focused on predictive models and statistical learning.  Key Characteristics of the Second Wave of AI Agents: Examples and Applications: In 2023 Bill Gates prophesized AI Agents would be here in 5 years. His timing was off. But not his prediction. The Future of Computing: Your AI Agent, Your Digital Sidekick Imagine this: No more juggling apps. No more digging through menus. No more searching for a document or a spreadsheet. Just tell your device—in plain English—what you need, and it handles the rest. Whether it’s planning a tour, managing your schedule, or helping with work, your AI assistant will understand you personally, adapting to your life based on what you choose to share. This isn’t science fiction. Today, everyone online has access to an AI-powered personal assistant far more advanced than anything available in 2023. Meet the Agent: The Next Era of Computing This next-generation software—called an agent—responds to natural language and accomplishes tasks using deep knowledge of you and your needs. Bill Gates first wrote about agents in his 1995 book The Road Ahead, but only now, with recent AI breakthroughs, have they become truly possible. Agents won’t just change how we interact with technology. They’ll reshape the entire software industry, marking the biggest shift in computing since we moved from command lines to touchscreens. Consider Salesforce’s AgentForce. A platform driven by automated AI agents that can be trained to do virtually anything. Freeing staff up from mundane data entry and administrative work to really set them loose. Marketers can once again create content, but with the insights provided by AI. Sales teams can close deals, but with the lead rating details provided by AI. Developers can devote more time to writing code but letting AI do the repetitive pieces that take time away from awe inspiring development. Why This Changes Everything We’re on the brink of a revolution—one where technology doesn’t just respond to commands but anticipates your needs and acts on your behalf. The age of the AI agent is here, and it’s going to redefine how we live and work. By Tectonic’s Marketing Operations Manager, Shannan Hearne Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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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Agentforce: Modernizing 311 and Case Management

Join Tectonic for an informational webinar on Salesforce Agentforce, Modernizing 311 services, and Case management. In this webinar you will hear: For more information fill out the contact us form below or reach out to the Public Sector team PublicSector@GetTectonic.com Get ready for the Next Frontier in Enterprise AI: Shaping Public Policies for Trusted AI Agents! AI agents are a technological revolution – the third wave of artificial intelligence after predictive and generative AI. They go beyond traditional automation, being capable of searching for relevant data, analyzing it to formulate a plan, and then putting the plan into action. Users can configure agents with guardrails that specify what actions they can take and when tasks should be handed off to humans. For the past 25 years, Salesforce has led their customers through every major technological shift: from cloud, to mobile, to predictive and generative AI, and, today, agentic AI. We are at the cusp of a pivotal moment for enterprise AI that has the opportunity to supercharge productivity and change the way we work forever. This will require governments working together with industry, civil society, and all stakeholders to ensure responsible technological advancement and workforce readiness. We look forward to continuing our contributions to the public policy discussions on trusted enterprise AI agents. 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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How AI Can Help Canadian Manufacturers Stay Competitive in a Changing Economy

Canada’s manufacturing sector faces mounting pressures—from a weak Canadian dollar to persistent supply chain disruptions. According to Salesforce’s Trends in Manufacturing Report, 63% of Canadian manufacturers say supply chain issues that began years ago still linger today, while unexpected equipment downtime costs large producers 8% of annual revenue. To navigate these challenges and future-proof operations, Canadian manufacturers must embrace AI-driven modernization—leveraging data intelligence, predictive analytics, and autonomous AI agents to boost efficiency, cut costs, and unlock new revenue streams. The Data Accessibility Challenge While 84% of Canadian manufacturers recognize the need to modernize, many struggle to extract real value from their digital investments. Key findings reveal: The problem? Siloed data prevents manufacturers from delivering real-time insights to frontline workers and AI tools—hindering predictive maintenance, inventory optimization, and customer service improvements. How AI Agents Drive Manufacturing Efficiency To maximize AI’s impact, manufacturers need a unified data platform (like Salesforce’s Manufacturing Data Cloud) that integrates: Autonomous AI agents (powered by natural language processing) can then automate decision-making, such as:✅ Detecting sales contract deviations and auto-correcting pricing or fulfillment issues.✅ Predicting equipment failures and scheduling proactive maintenance.✅ Optimizing stock levels by auto-reordering when inventory dips. 3 Key Areas Where AI Delivers Immediate ROI The Path Forward: Building an AI-Ready Foundation With economic uncertainty looming, Canadian manufacturers must act now to:🔹 Break down data silos (integrate IoT, ERP, and CRM systems).🔹 Deploy AI agents for autonomous decision-making in sales, maintenance, and logistics.🔹 Train teams to work alongside AI—not against it. The bottom line? AI isn’t just a competitive advantage—it’s becoming a necessity for survival in modern manufacturing. By harnessing connected data and intelligent automation, Canadian manufacturers can cut costs, boost productivity, and secure their future in an unpredictable global market. Ready to modernize? Start by auditing your data infrastructure—because AI is only as powerful as the insights it can access. Tectonic can help. 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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