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Demos fail in production. Meibel delivers complete context, predictable execution, and scored outputs. Booth 313 at AI Summit NYC. See it live.

The AI Summit NY demo that will transform how you build AI. Meet your new all-in-one AI orchestration platform. Book a demo: https://lnkd.in/eGFcHfx3

AI can write like a strategist. But thinking like one takes the right structure. Toffler Associates, a future-focused strategic advisory firm, set out to make their consulting discipline live in a client-facing software. The result is SINE, a foresight and scenario platform that turns decades of expertise into a measurable, scalable system. Built on Meibel's dependable AI infrastructure, Sinebeacon captures Toffler’s Think Like a Futurist® methodology in a governed, transparent environment structured reasoning, human oversight, and data-driven feedback to generate insight that’s explainable and traceable. What began as a question “Can we make foresight reproducible?”, became a product that helps Toffler’s clients plan ahead with clarity and confidence. Full case study in first comment. #DependableAI #Foresight #AIInfrastructure #AIStrategy

What’s Meibel bringing to the Venture Atlanta stage? One idea: the first try looks almost right. Then errors compound. That’s why AI stays an assistant in companies that run on documents. Meibel is built to change that. Documents become data. Data becomes agents. All on one platform, with every answer scored and traced to its source. Quality compounds. Kevin McGrath presents at Venture Atlanta, October 14–15. #VentureAtlanta #AIAgents #EnterpriseAI #Meibel

This Thursday at 1 PM EST: Kevin McGrath and Aaron Aguillard go live with Beyond Prompts: How to Build Reliable AI Workflows in Production webinar. The session covers what most AI content skips: context engineering, workflow control, and confidence scoring – the three things that determine whether outputs can be trusted without constant human review. You'll learn about: ✔️ Context assembly: preserving structure so tables stay tables and references resolve ✔️ Workflow orchestration: controlled execution with validation and governance ✔️ Confidence thresholds: systems that escalate or block outputs automatically Platform: Zoom Date: April 9, 1 PM ET / 10 AM PT Duration: 45 min + Q&A ➡️ Save your spot here: https://hubs.ly/Q049Tjr20

An AI that's 95% right on your medical records still needs a person checking every page. Entire industries still run on documents and unstructured data. Healthcare, construction, chemicals, pharma, legal. The information the business depends on lives in records, contracts, manuals and spec books. Construction teams price bids from spec books hundreds of pages long. Federal contractors spend weeks on a single 300-page RFP. Maintenance teams type thousand-page manuals into their systems by hand. Every one of these industries wants agents doing this work. None of them can let an agent act on data that's almost right. I've spent my career building automation that companies rely on without someone watching it. Agents need the same foundation, and it starts with the data. Documents become data: every page read the way an expert reads it, tables and footnotes included. Data becomes agents: stored so an agent works from exactly what it needs, joined with your systems. Agents do the work: inside guardrails, with every answer traced to the page it came from. Most tools handle one step, and errors creep in at the handoffs. We built all three as one platform. SpecBooks: bid volume up 400%, no new engineers. Tetheree: 300-page federal RFP responses in days instead of weeks. SMS: thousand-page manuals into maintenance data, 100% accurate on most of their own tests and 90%+ overall, up from 70–95%. I'm on stage at Venture Atlanta on October 14. Come find me.