The hard part isn't the AI. It's staying in control of it.
Modern AI can already search your documents, answer questions, and run agents. That part is becoming a commodity. The hard part, the part that decides whether AI is safe to use in a regulated, sensitive, or sovereign business, is everything around it: who is allowed to see what, what your AI is allowed to do, what it costs, and where it all runs. That is what InsightMesh is built for.
1. It governs everything with one policy
Most tools govern login. InsightMesh governs every request. A single attribute-based access control (ABAC) model decides who can read which document, run which agent, and take which action. That model is evaluated on every query, for every user, in every tenant. And because the platform refuses to run any capability that isn't governed, a permission gap can't quietly ship.
How governance works →
2. It accounts for what your AI costs
AI spend is the budget question every leader is now asking, and almost no platform answers honestly. InsightMesh keeps a precise, tamper-resistant ledger of every call, attributed by team, user, model, and project. Joined with your cloud spend, it gives you one clear answer to what your AI is really costing you, and where you can cut it.
Cost governance →
3. It runs where you need it, even on your own hardware
SaaS, private cloud, or fully on-premise from day one: your choice, per deployment. For the most sensitive work, InsightMesh can run a local AI model, so your prompts and data never leave your perimeter and no outside AI provider is ever called.
Deployment & data control →