Business Intelligence

askyourbusinessaquestion.getarealanswerinseconds.

Your CRM knows about deals. Your PM tool knows about timelines. Your accounting system knows about cash. Your email knows about commitments. Nobody knows everything — until now.

thescavengerhunt.

Pulling a cross-platform answer takes hours of tab-switching and manual correlation. Your data is trapped in silos across 5-10 different SaaS tools, and the only person who can connect the dots is a senior leader who doesn't have time.

Hours spent tab-switching between CRM, PM, accounting, and email to build a single report
Senior leaders answering basic status questions because nobody else has the full picture
Decisions delayed because gathering the data takes longer than analyzing it
No single source of truth across your business operations

theoracle.

A queryable AI layer across every platform your business runs on.

Company Oracle

A centralized AI layer that connects across CRM, project management, email, and accounting. Ask "What's the status of the Henderson project?" and get a real answer in seconds — not a scavenger hunt across five platforms.

MCP-based connectors

Each system gets connected one at a time via Model Context Protocol, each expanding what the AI can see and answer. Structured data mapping, security boundaries, and read-only access patterns throughout.

Plain language queries

"Which sales leads from last month haven't been assigned to drafting?" / "What did the contract with that vendor say about pricing?" — leadership prompts in plain English that return actual answers.

Incremental deployment

Start with one system. Add another. Each connection expands the AI's view of your business. No big-bang integration — controlled, sequential, measurable expansion.

thebiggestcompaniesarebuildingthis.

Coinbase built an internal AI query layer for exactly this problem. So did the other companies with the engineering budget to do it in-house. Rockwell brings the same capability to mid-market companies — the ones running 3-10 SaaS tools with no unified view, making decisions based on incomplete information because pulling the full picture takes too long.

theteam.

brings CPA, CFA, and CAMS credentials to AI strategy — he understands the business problems before reaching for the technology. brings deep engineering experience in production AI systems. Together, that’s the full stack: someone who knows what to build and someone who knows how to build it.

Luke ThibodeauCPA · CFA · CAMSFounder and CEO

Luke is a finance and compliance operator who works hands-on with bitcoin-native companies, fintechs, and MSBs as a fractional CFO and CCO through Rockwell Advisory Group. As former CFO & CCO of Bitcoin Well (TSXV:BTCW), he built and ran the finance, compliance, and governance functions across a publicly listed, multi-entity crypto company from the ground up.

Today he brings that same operational depth to clients navigating treasury management, FINTRAC compliance, financial reporting, and corporate governance. Whether it's standing up a compliance program for a new MSB, managing multi-entity consolidations, or advising on AI strategy through Rockwell AI, Luke operates as an embedded member of the team rather than an outside advisor. He also founded Comply+, a RegTech platform automating FINTRAC reporting for Canadian MSBs, born directly from the pain points he encountered building compliance workflows by hand.

Daniel FrazeeHead of Integration

Daniel is a technologist and operations leader serving as Head of Integration at Rockwell AI, helping companies turn AI strategy into working systems. As COO of Próspera, he built and scaled operations across a complex, multi-jurisdictional organization, managing everything from employment infrastructure to day-to-day execution across distributed teams.

Before that, he spent four years at Chevron as an IT professional, working inside the kind of large-scale enterprise systems where reliability and process discipline aren't optional. That combination of big-company engineering rigor and startup-stage operational ownership shapes how he approaches integration: grounded in real constraints, focused on outcomes, and built to hold up in production. Daniel holds a B.S. in Computer Science from Texas A&M University, with deep experience across software development, machine learning, and operations management.

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