Technology Applications in Business

Human-in-the-loop and AI orchestration are the most misunderstood concepts in B2B SaaS. 1️⃣ Most think "human-in-the-loop" means AI makes their work easier. Wrong. 👋 It means humans handle the cases AI can't solve. All day long. In real time, or as close as possible. The 30% of support tickets that are too complex. The sales conversations that need real judgment. The edge cases that break automated systems. 🚵 As AI gets better, the remaining human work gets HARDER, not easier. 2️⃣ And "orchestration" isn't picking vendors and watching dashboards. It's 60+ days of intensive training after deployment. Daily quality auditing. Managing 5-10 AI systems that each have unique failure modes. 👉 SaaStr's reality check: We sent 4,495 AI emails with top response rates, but it required: • 90 minutes every morning training the AI • 1 hour every night reviewing performance • Real-time responses throughout the day • 20+ million words of training content 🫵 Doing AI right is more work than not using AI at all Perplexity's CBO revealed another layer at SaaStr AI Summit 2025: AI changes WHEN you work, not just what you do. Sales reps now use AI live during prospect calls, making split-second decisions about what intelligence to surface while maintaining authentic conversations. Support already proved this model works: • Decagon: 70% deflection rates • Duolingo: 80%+ automation • Intercom: 86% resolution rates But those numbers hide the human orchestration behind them. Support teams evolved into AI managers, not disappearing but becoming more specialized. They do the tough stuff now. The multiplication effect hits when you deploy >multiple< AI systems. Now you need people who understand how your chatbot's limitations interact with your email automation's strengths. How to prevent AI systems from amplifying each other's errors. The uncomfortable truth: AI success requires "S-tier human orchestration" to get top-tier results. The companies winning with AI aren't replacing humans—they're making humans AI-capable. The future with AI in B2B isn't >less< human work. It's different and more human work: more complex, more valuable, and just plain more of it. And yes, more intense. Higher ROI? Yes. Much more work? Also yes.

3 Workflows I've Automated for in-house teams. ① Ask Legal ② Procurement ③ Contract Review (not just the review!) 1. Ask Legal [or any department for that matter 🤷🏼♀️] You've heard me talk about legal teams and knowledge management. Long story short, your legal team is answering the same 20 questions over and over 😵💫 A simple way to save a CHUNK of time answering questions from the business (enabling them to go faster) ALL while having complete control & keeping a human in the loop? ↪️ Set up an 'Ask Legal' bot in your comms platform. ↪️ Sync it with your knowledge base (e.g GDrive/Notion/Sharepoint). ↪️ Set up your custom instructions (Want it to tag Bob on privacy questions only, specifically on a Tuesday? No problem).  ↪️ Don't want the answer to go straight out to the business without reviewing it first? Cool, turn on co-pilot mode. The result? 60-80% fewer repetitive queries. Your team focuses on the high value things that need a human lawyer. 2. Procurement Businesses have 100's of tools, but when departments don't speak to each other you end up with duplicate tools & subscriptions 😭 💵 🚽.  What if there was a way for the business to find out in <1 minute if there was a tool available that covered their needs, before needing to spend some hard secured department budget? Moreover, what if I told you, they could kick off the internal procurement process from the comfort of your comms platform? Team member : “Do we already have a tool for X?” in Slack/Teams ✅ Bot checks knowledge base (policies, procurement tool). ✅ If a match is found, it shares the approved tool & owner to contact. ✅ If not, the bot can ask the user for more info and direct them with next steps to kick off the procurement process from inside Slack/Teams. Ensuring your users ACTUALLY follow the process, without adding friction. Did I just see your CFO cry tears of joy? 3. Third Party Vendor Contract Review & Project Management Getting AI to redline a contract (as a first pass) is a huge win, but there's still the other pieces of the process missing, like: 🤷🏼♀️ The business figuring out IF legal review is even needed (according to company policy). 📨 The business actually submitting the contract to legal. 😩 Managing review capacity within the legal team. 🖥️ Getting the legal team to log & update the PM tool. The list never ends. Legal reviews only what actually needs their eyes, turnaround times improve, and the business stops pinging the team for “update pls?” in Slack : ) TLDR; Most legal teams are drowning in admin work that could be automated. I've built all of these using simple processes and tools (that I've found most businesses have). You also know I love a good Figma flow. So I’ve built them for all three of the above (see a sneak peak below). Want the entire thing? Comment "FLOWS" and I'll send them over. Also, tell me what you want to see - more of the above or step-by-step how-to build videos?

A simple pattern I've implemented that drastically improves agentic AI systems: human-in-the-loop tool calls. While many focus on autonomous agents, the real breakthrough comes from elegantly handling human intervention within agent workflows. How: implement a specialized tool call that suspends execution when human input is required: (1) Serialize and persist the entire agent state - including conversation context, execution trace, and reasoning path - preserving the agent's cognitive thread in your database (2) Await human judgment on critical decisions or ambiguous scenarios (3) Resume execution by reconstructing the original agent state from your database, ensuring continuity without forcing the agent to rebuild context or repeat work Consider a financial advisor agent encountering an edge case requiring human expertise. Rather than failing, it gracefully delegates through a human_input() tool call, persists its reasoning chain, and seamlessly continues after receiving guidance. Or a content creation pipeline where an agent drafts multiple options, triggers a human_review() tool call, and then refines based on selected preferences without restarting the entire creative process. This approach maintains the efficiency of automation while incorporating human judgment precisely where it adds the most value.

This week's defining shift for me is that XR is a practical tool for reducing real-world risk. It helps people see what they are dealing with before they commit to a choice or an action. Teams can spot problems before they happen, drivers can get comfortable with harder scenarios before hitting the road, and shoppers can get a better feel for fit and style before purchase. Better awareness at the start tends to pay off later. This week’s news surfaced signals like these: 🏎️ Mercedes-AMG PETRONAS F1 is using TeamViewer’s AR tools to speed up how its test rigs are put together. Engineers can point a tablet at the setup and see step-by-step guidance placed directly on the hardware. The overlays come from the team’s CAD files and help staff check part placement and confirm that everything is ready before testing starts. 😎 Tom Ford Fashion has added an AR try-on feature for its eyewear on its online stores. The experience, powered by Perfect Corp., uses a person’s pupillary distance to show frames at the right size on their face. This gives shoppers a more accurate sense of how different styles will look and can help cut down on returns. 🚘 South Carolina State University opened a VR training lab for commercial drivers, using full-size simulators to prepare people for roadway hazards such as fatigue, congestion, and aggressive driving. The system also captures physiological data to support safety research and improve training design. Why this matters: Tools that help people understand things earlier can lead to better outcomes. XR does this by making moments that used to feel uncertain easier to anticipate. As more organizations adopt it, the technology becomes a powerful way to bring more confidence into everyday decisions. #spatialcomputing #XR #virtualreality #VR #augmentedreality #AR

Not the tech of today or tomorrow, this is what Auto giants have been doing with Augmented Reality since 2015…Let's talk cars this Sunday ☀ Sharing 3 AR use-cases from my archives…By Mercedes, Hyundai & Porsche 🚨 Mercedes-Benz overlays important information, graphics and audio cues to help you find your way.  A camera in the windscreen films the area in front of the vehicle and shows either the video or a stationary image on the media display. 🚨 Hyundai has taken the concept one step further with its Virtual Guide app, which allows owners to use a smartphone or tablet to get interactive information on vehicle features via an augmented reality overlay. Users simply point their portable device's camera to a part of the car they want to learn more about, and the app highlights and delivers information on certain features. 🚨 Porsche has introduced augmented reality glasses to reduce repair times by up to 40%. Porsche has been using augmented reality (AR) to solve tricky service problems since 2018, letting local dealership technicians communicate with specialists thousands of miles away and access technical information hands-free while working. Today, there’s no auto-brand that’s untouched by Immersive Tech/ Metaverse. I remember my conversation with Piyush Gupta, CEO, Vosmos on how the automotive industry has direct fitment to AR, VR & Metaverse. In fact, his team is also actively working on numerous use-cases for the automobile sector. What do you think? Inviting meaningful conversations in comments. 🤔 #automotiveindustry #immersivelearning #virtualreality #metaverse Nicht die Technologie von heute oder morgen, das ist es, was Autogiganten seit 2015 mit Augmented Reality machen … Reden wir diesen Sonntag über Autos ☀ Ich teile 3 AR-Anwendungsfälle aus meinen Archiven … Von Mercedes, Hyundai und Porsche 🚨 Mercedes-Benz blendet wichtige Informationen, Grafiken und Audiohinweise ein, um Ihnen die Orientierung zu erleichtern. Eine Kamera in der Windschutzscheibe filmt den Bereich vor dem Fahrzeug und zeigt entweder das Video oder ein Standbild auf dem Media-Display an. 🚨 Hyundai hat das Konzept mit seiner Virtual Guide-App noch einen Schritt weitergeführt, die es Besitzern ermöglicht, über ein Augmented-Reality-Overlay mit einem Smartphone oder Tablet interaktive Informationen zu Fahrzeugfunktionen abzurufen. Benutzer richten einfach die Kamera ihres tragbaren Geräts auf einen Teil des Autos, über den sie mehr erfahren möchten, und die App hebt bestimmte Funktionen hervor und liefert Informationen zu ihnen. 🚨 Porsche hat eine Augmented-Reality-Brille eingeführt, um die Reparaturzeiten um bis zu 40 % zu verkürzen. Seit 2018 nutzt Porsche Augmented Reality (AR), um knifflige Serviceprobleme zu lösen. So können die Techniker des örtlichen Autohauses mit Spezialisten in tausenden Kilometern Entfernung kommunizieren und während der Arbeit freihändig auf technische Informationen zugreifen.

6 𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗖𝗮𝘀𝗲 𝗦𝘁𝘂𝗱𝗶𝗲𝘀 𝗶𝗻 𝗘𝘅𝘁𝗲𝗻𝗱𝗲𝗱 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: 𝗥𝗲𝗮𝗹 𝗜𝗺𝗽𝗮𝗰𝘁, 𝗥𝗲𝗮𝗹 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 Want proof that #VR, #MR, and #AI are transforming education and training? Here’s how global organisations are creating measurable impact with extended reality: 1️⃣ 𝗣𝘂𝗿𝗱𝘂𝗲 𝗚𝗹𝗼𝗯𝗮𝗹 (𝗡𝘂𝗿𝘀𝗶𝗻𝗴 𝗘𝗱𝘂𝗰𝗮𝘁𝗶𝗼𝗻) ✦ 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲: Addressing nursing shortages and training working adults. ✦ 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻: VR training with Meta Quest for clinical and soft skills, in partnership with PCS Spark and Oxford Medical Simulation. ✅ 𝗥𝗲𝘀𝘂𝗹𝘁: 10–15% increase in national nursing exam pass rates. 4,000+ nurses trained. Marked improvements in student confidence and real-world preparedness. 2️⃣ 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆 𝗼𝗳 𝗚𝗹𝗮𝘀𝗴𝗼𝘄 ✦ 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲: Physical constraints in teaching 3D subjects and remote learning accessibility. ✦ 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻: Mixed reality lab with Meta Quest headsets and 12 custom MR apps, developed with Edify. VR labs created in partnership with leading immersive tech companies, allowing teachers to lead 3D classes remotely. ✅ 𝗥𝗲𝘀𝘂𝗹𝘁: Thousands of students taught per semester. £3.7M UK government investment. Recognized in The Times Higher Education Awards 2021. Students reported increased confidence and deeper understanding of material, even in remote settings. 3️⃣ 𝗡𝗬𝗨 𝗖𝗼𝗹𝗹𝗲𝗴𝗲 𝗼𝗳 𝗗𝗲𝗻𝘁𝗶𝘀𝘁𝗿𝘆 ✦ 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲: Risky, limited traditional anesthetic training. ✦ 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻: VR simulation for oral anesthesia using Meta Quest. ✅ 𝗥𝗲𝘀𝘂𝗹𝘁: 1,200+ dental students trained. Greater student confidence. VR program licensed to other schools. 4️⃣ 𝗜𝗻𝘀𝗽𝗶𝗿𝗲𝗱 𝗘𝗱𝘂𝗰𝗮𝘁𝗶𝗼𝗻 𝗚𝗿𝗼𝘂𝗽 ✦ 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲: Making science practical for online and in-person learners. ✦ 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻: Mixed reality classes with Meta Quest, immersive views, and AI avatars. ✅ 𝗥𝗲𝘀𝘂𝗹𝘁: 100% of teachers reported improved student confidence. 85% improvement in content recall. 94% of students learned better in VR. 5️⃣ 𝗖𝗲𝗻𝘁𝗿𝗲 𝗳𝗼𝗿 𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 (𝗧𝗮𝗻 𝗧𝗼𝗰𝗸 𝗦𝗲𝗻𝗴 𝗛𝗼𝘀𝗽𝗶𝘁𝗮𝗹) ✦ 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲: Training efficiency and safety in healthcare settings. ✦ 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻: VR modules for Lean principles with Meta Quest 2. ✅ 𝗥𝗲𝘀𝘂𝗹𝘁: 100% of participants said VR deepened their understanding. Plans to expand VR training hospital-wide. 6️⃣ 𝗩𝗲𝗵𝗶𝗰𝗹𝗲𝘀 𝗳𝗼𝗿 𝗖𝗵𝗮𝗻𝗴𝗲 ✦ 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲: Scaling auto-mechanic training for formerly incarcerated people. ✦ 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻: VR training with Meta Quest 2 and the EMPACT Immersive Training Platform. ✅ 𝗥𝗲𝘀𝘂𝗹𝘁: Early graduates securing jobs quickly. Reduced recidivism rates. Major potential for broader socio-economic impact. #ExtendedReality #MetaForWork #EdTech #VRTraining #MixedReality #Impact

My latest in today's print edition of The Wall Street Journal: Companies Finally Find a Use for Virtual Reality at Work. More employees are strapping on virtual reality headsets as the immersive technology becomes an increasingly common method for workforce training on a range of topics, from hardware maintenance to leadership and empathy. Companies such as UPS and Walmart have taken a slow but measured approach to adopting a technology that has drawn extreme hype and extreme skepticism over the years as businesses have tested, piloted and pulled back on various uses. “It’s an interesting, but slower than expected journey. But for training—I think VR will always be a good way to use it,” said Johan Hellqvist, head of mobile and XR/3D at Volvo Group, about the process. The company today uses VR to train employees on actions like replacing the battery on an electric truck. What are your thoughts on getting trained in virtual reality? Read the full story here for more from Mark Gröb, Head of Immersive Technology at UPS, Christopher Botzum, Deputy Police Chief, Joliet Illinois Police Department, Nicki Finnigan, director of learning and development at St James's Place, Jennifer Buchanan vice president of the Walmart Academy training program, and Brad Scoggin, co-founder and chief executive of ArborXR: https://lnkd.in/ewYyumhn

The best training room is where the work actually happens. That's the logic behind VR passthrough in SynergyXR 3.5 released yesterday. Put on a headset and your real surroundings stay visible - the actual machine, the actual workspace. Virtual content is layered on top: step-by-step instructions, 3D models, interactive procedures. You train in context, on real equipment, without leaving the floor. For industries where procedures are complex and equipment is expensive, this isn't just "more immersive training." It's the ability to run a procedure on the actual asset, in the actual space, before ever touching it unsupervised. There's a forward-looking angle I keep coming back to. Every serious AR glasses roadmap - Meta, Apple, Google and others - is converging on exactly this modality: lightweight, spatially anchored content layered over the physical world. Companies building physical space procedures in SynergyXR today are already working in that paradigm. The content model maps directly to where the hardware is heading. The video shows it better than I can describe. What use cases would you test first? #EnterpriseXR #MixedReality #XRTraining #SynergyXR

🚨 Agentic Workflow for Insider Threat Monitoring 🧠🛡️ As enterprise data grows in complexity, insider threats are no longer just anomalies—they're sophisticated patterns that demand intelligent, context-aware monitoring. This cutting-edge Agentic AI architecture showcases how we can combine Machine Learning (ML), Large Language Models (LLMs), and rule-based automation to stay several steps ahead of potential security risks. 🔍 Key Highlights of the Workflow: 📥 Ingestion Layer: Seamlessly processes structured & unstructured security telemetry using Kafka, Amazon MSK, and Kinesis. 🧹 Preprocessing & Identity Mapping: Data Cleaner + PII Redactor (ML) ensures privacy by scrubbing sensitive information. Identity Graph Builder (ML) connects disparate user activities across systems to form a unified behavioral profile. 📊 Behavioral Analysis & Anomaly Detection: Baseline Behavior Modeler (ML) establishes “normal” behavior for every identity. Anomaly Detection Agent (ML) flags deviations using ML guardrails for precision and accountability. 🤖 Agentic Intelligence (LLM + Rule Engine): Threat Synthesizer Agent (LLM) reasons over anomalies and combines contextual signals from vector databases like Pinecone, Weaviate, and Amazon OpenSearch. Soar Executor Agent triggers appropriate actions using pre-set rules. Feedback Interpreter & Learner (LLM) learns from analyst feedback and continuously improves threat detection. 🧠 LLM Infra: Powered by Amazon Bedrock, OpenAI, and Claude 3 Sonnet—providing the scale and intelligence needed for complex, real-time decision making. 📈 Transparency & Explainability Tools: Integration with SageMaker Clarify, EvidentlyAI, and Bedrock Guardrails ensures fairness, transparency, and compliance. 💬 Human-in-the-loop: Analysts can review and interact through tools like Slack, Jira, and a dedicated Analyst Interface for final verdicts or overrides. 🔐 This isn’t just automation—it's augmented security intelligence, capable of evolving with your threat landscape.

If you're running automations that handle sensitive data, here's how I'm implementing human-in-the-loop workflows to add a safety layer.   Just integrated Velatir into my n8n workflows, and it works quite differently from n8n's built-in HITL features.   Here's what happening:   I've been building automated workflows for clients, and when you're dealing with sensitive operations - payment processing, customer communications, data modifications - you may need that human verification step.   That's where Velatir comes in. It's a human-in-the-loop platform that adds approval checkpoints to any automation.   Example 1: Payment Processing Automation • Refund request comes in • If above a certain threshold, Velatir pauses the workflow • I get instant notification via email/Slack/Teams • I approve or reject with one click • Workflow continues or stops based on my decision   Example 2: Automated Email Responses • Email arrives from customer • AI drafts response • Velatir shows me the draft before sending • I verify it's appropriate and accurate • Email sends only after approval   What makes this different from basic approval systems:   → Customizable rules, timeouts, and escalation paths → One integration point, no need to duplicate HITL logic across workflows → Full logging and audit trails (exportable, non-proprietary) → Compliance-ready workflows out of the box → Support for external frameworks if you want to standardize HITL beyond n8n   The setup took about 5 minutes - sign up, get API key, add to your n8n workflow.   One interface, one source of truth, no matter where your workflows live.   Question for my network: What's the riskiest automation you're running without human oversight?