Fogoarai runs AI agents inside your company's network. Your data never leaves, your IT team controls what each one does, and every action is recorded.
Most AI today sits outside the company. It can't see internal systems, can't be governed, and can't safely handle the data that matters. For a regulated business, that means it stays at the edges instead of doing real work.
Most enterprise AI work doesn't need the most expensive model. Companies that route to smaller specialized models save 50–70% on cost.
Contracts, customer records, financials, tickets, internal documents. None of this can go to OpenAI, Google, or Anthropic without breaking compliance.
Real work needs the AI to read from CRM, ERP, databases, documents, and approval flows, not just chat.
Without controls, audit logs, and approvals, AI can't get past a security review at a regulated company.
Most AI infrastructure gives you one of three: governance, cost-optimized routing, or private deployment. Fogoarai is the only runtime that ships all three at once, inside your own infrastructure. That combination is the product.
Access control, approvals, and a full audit trail are part of how every action runs, not a separate tool you buy and wire up later.
Small specialized models handle routine work locally; frontier models step in only when the task needs them. Every routing decision is policy-driven and recorded.
Built to run with zero external egress. On-prem, dedicated VPC, or private cloud are relaxations of that baseline, not features added on top.
The full picture, in three: how the platform works, the governance a regulated business assumes, and what every license includes.
The seven-layer runtime, cost-optimized routing, the control plane, and private deployment.
GOVERNANCERBAC, approvals, audit, redaction — and why no one else combines all three in one runtime.
PLANUnlimited RAG and database-to-LLM in your license. You scale by governed agents.
Two real use cases, in production, in regulated industries. In both, the data could not be sent to OpenAI, Google, or Anthropic, so the AI runs inside their own systems instead.
An AI agent that reads competitor disclosures and filings, builds side-by-side comparisons across coverage, pricing, and policy terms, and points out gaps for the company's analysts.
An AI agent that connects the engineers to their archive of mining experiments, surfacing prior findings and outcomes so teams can use relevant past work instead of repeating expensive studies.
Pick one workflow that matters. Connect it to the right internal systems. Add the approvals and audit a regulated business needs. Measure the result inside the first 90 days.