LANSING – Michigan company says its new AI platform can help Tier 2 automotive suppliers and other manufacturers accomplish more with existing employees by securely connecting artificial intelligence to real business data instead of relying on educated guesses.
Artificial intelligence has become remarkably good at answering questions, writing reports and generating computer code. But inside Michigan manufacturing plants and engineering offices, business leaders are asking a different question: Can AI actually help employees make better business decisions?
Supported Intelligence believes the answer is yes.
The Michigan technology company has developed a platform built around the emerging Model Context Protocol (MCP), an open standard that allows modern AI assistants—including ChatGPT, Claude, Gemini, Microsoft Copilot and other large language models—to securely connect with business databases, supplier information and specialized decision-making software.
Instead of relying solely on information learned during training, the AI retrieves current company data, hands complex analytical work to Supported Intelligence’s proprietary decision engine, and returns recommendations that can be explained and audited.
The result, according to Dan Lipsy, president of Supported Intelligence, is artificial intelligence that moves beyond conversation and begins solving real business problems.
“We’re helping companies put AI to work,” Lipsy said. “MCP is becoming like USB-C for the AI industry—a universal connection point. Or think of it like the App Store: a standard way for AI to securely access the tools and data it needs to make better decisions.”
“The future of AI isn’t simply answering questions,” Lipsy said. “It’s helping people make better decisions using the information their companies already own.” For Michigan manufacturers facing skilled labor shortages, increasing global competition and relentless pressure to improve productivity, that future is already here.
Beyond Chatbots
Most people think of AI as a sophisticated chatbot.
Ask it to summarize a report, write an email or explain a technical concept, and the results are often impressive.
But ask it to answer a six-figure business question using information it has never seen, and the limitations become apparent. Traditional AI models can confidently provide answers that sound correct but are based on incomplete or outdated information because they cannot access a company’s live business systems. Supported Intelligence says MCP changes that equation.
AI Talks. The Decision Engine Calculates.
At the center of Supported Intelligence’s platform is its proprietary Rapid Recursive Toolbox, a decision engine designed to solve complex business problems.
Employees ask questions in plain English.
The AI manages the conversation.
The Rapid Recursive Toolbox performs the calculations and analysis.
The results are then returned to the employee along with the reasoning behind each recommendation.
That transparency is especially important for businesses making expensive purchasing, maintenance or supply chain decisions where executives need to understand not only the answer, but how the conclusion was reached.
From Pickup Trucks to Production Equipment
Dan Lipsy uses two examples that demonstrate how the technology works.
The first is something many vehicle owners eventually face.
Should you keep your pickup truck for another year or sell it today?
Rather than offering a generic opinion, the AI gathers information about mileage, maintenance costs, financing, repair history and resale value before passing those facts to Supported Intelligence’s analytical engine, which calculates the financially optimal decision and explains why.The same approach applies inside manufacturing facilities.
A plant manager might ask whether an aging CNC machine should be repaired, rebuilt or replaced.
Instead of relying solely on experience or intuition, the system analyzes maintenance history, operating hours, downtime, replacement costs and production schedules before recommending the most cost-effective course of action.
Already in the Field
Supported Intelligence’s technology is already live and operating in real manufacturing environments. A fastener company in West Michigan is currently using the platform to improve the accuracy of its operational decision metrics, from supplier selection to inventory management.
Rather than replacing employees, Lipsy envisions AI becoming another member of the team—helping purchasing professionals locate supplier information, assisting engineers in searching technical documentation, analyzing production data and helping managers make faster, better-informed decisions. The objective is simple: enable existing employees to accomplish more work without requiring companies to continually add staff.
Talking to Your Supply Chain
Supported Intelligence also sees significant opportunities through its SupplyBase platform.
Instead of manually searching supplier catalogs or engineering databases, employees can simply ask questions in everyday language.
Need to locate a specific fastener from an approved supplier?
The AI searches the appropriate databases.
Need to compare vendors or analyze a supplier catalog provided as a PDF?
The AI retrieves the information, performs the analysis and returns a documented answer in seconds.
The goal is to let employees interact with complex business systems through natural conversation instead of forcing them to navigate multiple software applications.
The Next Stage of Enterprise AI
As Model Context Protocol rapidly gains acceptance across the artificial intelligence industry, Lipsy believes businesses that begin connecting their internal systems today will be better positioned to take advantage of the next generation of AI.
