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.

1.2M+

Agent runs / month

0.8s

p95 latency

12

Production agents

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.

The solution

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.

Architecture

01

Agents are provisioned per tenant with isolated state and role-based access (owner / admin / member).

02

One model gateway owns timeouts, retries, token ceilings, and a cost kill-switch. Providers (OpenAI, Groq, Ollama) are swappable.

03

Anything writing to a system of record surfaces low-confidence output for human review. The model removes typing, not accountability.

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.

Industry

AI & Automation


Results

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.


Tech stack

TypeScript
Node.js
PostgreSQL
Redis
OpenAI
Groq
Ollama

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