Seven layers turn a single AI request into a governed action the company can trust: from who asked, to which model answered, to which system was touched, to who approved it, to what got logged.
A person, a ticket, a schedule, or another system kicks off the work, with the user's role and the request's context attached.
Before any work begins, the company's rules decide what this user, this agent, and this workflow are allowed to do.
The agent plans the steps, remembers context across them, and uses the right tools to complete the task end to end.
Routine work goes to smaller, cheaper specialized models. Harder work escalates to a frontier model. The company sees what was chosen and why.
CRM, ERP, databases, documents, ticketing, email, internal APIs. The agent reads and writes only what policy allows.
Sensitive or irreversible actions stop and wait for the right person to approve before anything is committed.
Every input, model choice, tool call, approval, and output is recorded: searchable, exportable, and built for security and compliance review.
Most of the AI work inside a company is narrow and repeatable: classify a ticket, pull data out of a document, validate a field, summarize a report. That work belongs on smaller, cheaper, specialized models. Frontier models only step in when the task actually needs them.
The target cost reduction on high-volume workflows when routine work runs on smaller specialized models, with quality protected by validation and confidence-based escalation.
Design target · varies by workflow · not a universal guaranteeThe router runs inside the customer's environment: small specialized models by default (served locally via Ollama, air-gap capable) with frontier models on escalation. Every routing decision is policy-driven, versioned, and audited. A natural-language-to-SQL workflow already runs on a fine-tuned local model in production.
Most AI tools can tell you what they answered. Fogoarai shows you why: which model ran, what it cost, what data it touched, who approved it, and the policy that was in force, for every action. That full record is what turns AI from a black box into something your security, risk, and compliance teams can actually sign off on.
Fogoarai is built for companies that can't send sensitive work to an outside black box. It runs inside the company's own cloud, dedicated VPC, or on-prem environment, with the company in control of where data sits, which models are used, what gets logged, and what each agent is allowed to do.
| Topology | External egress | Model serving | Best for |
|---|---|---|---|
| Air-gapped | none | local SLMs only | highest-sensitivity / sovereign data |
| On-prem | policy-gated | local + frontier on escalation | regulated, own data center |
| Dedicated VPC | policy-gated | local + frontier on escalation | cloud-native, data-residency bound |
| Private (single-tenant) SaaS | policy-gated | frontier + routed | fastest start, still isolated |