Multi-Tenant AI Agent Platform
A multi-tenant platform for provisioning, running, and governing AI agents. Invoice parsing, booking assistants, and intelligent routing at scale.
Agent runs / month
1.2M+
p95 latency
0.8s
Production agents
12
The challenge
A team needed to deploy AI agents across departments; early experiments showed unpredictable costs ($0.02–$0.40 per run), 2–8s latency variance, and zero auditability. They needed cost predictability, sub-second latency, and full traceability without vendor lock-in.
What we built
We built a multi-tenant control plane where every agent is provisioned, versioned, and governed. All model calls route through one gateway that owns timeouts, retries, a token ceiling, and a per-tenant cost kill-switch, with providers swappable behind the same interface.
The outcome
Twelve agents run in production at 1.2M+ runs a month and a 0.8s p95, with self-hosted model options for sensitive tenants and full per-call usage tracking.
Stack
AI component
The platform IS the AI layer: RAG-grounded assistants, an OCR + LLM invoice pipeline, and multi-step automation agents, each observable, rate-limited, and cost-capped.
Building something like this?
We'll review scope, architecture, and where AI fits, and reply within one business day.
Start a projectHow it's built
Agents are provisioned per tenant with isolated state and role-based access (owner / admin / member).
One model gateway owns timeouts, retries, token ceilings, and a cost kill-switch. Providers (OpenAI, Groq, Ollama) are swappable.
Anything writing to a system of record surfaces low-confidence output for human review. The model removes typing, not accountability.
More case studies
Have a system that has to be right?
Tell us what you're building. We'll review scope, architecture, and where AI fits, and reply within one business day.