Decide what your AI is allowed to do.
Prove it.
Existing tools tell you what your AI did. Azoth decides what it is allowed to do, blocks what it shouldn't, and exports the evidence — every call, every workspace, every regulator. The audit trail the EU AI Act now requires.
No credit card. No code changes. Connects in 5 minutes.
Modelled on a reference customer-support workload — not yet measured against a live customer. Full stack: IAE + Semantic Cache + CCE + Green Routing. How we compute these →
AI costs compound.
Most teams don't see it until it's critical.
One runtime layer changes all of this.
One runtime. Three governance acts.
Azoth sits between your application and your AI providers. Every call flows through the runtime — evaluated against your policies, blocked when they fail, and traced so you can prove what happened.
Decide
The Policy Engine scores every request against the rules you set — sovereignty, budget, connector approval, data category. Compliant routes through. Non-compliant gets the next card.
Sub-millisecond evaluationBlock
When a rule fails, the runtime refuses the call before any token is spent. No provider hit. No PII pushed. Your auditor sees a refusal, not a leak.
Zero token cost on blockProve
Every decision — allowed or blocked — produces a signed audit-evidence bundle. Hand it to a regulator. Diff it across releases. Replay it offline. The trace is the contract.
Signed audit trail per callGovernance across every major provider
Runtime governance for AI applications
The four modules that carry the ROI. One SDK, zero pipeline rewrites.
Intelligent Model Arbiter
Every request scored across cost, quality, and latency. The Arbiter routes to the cheapest model that still meets your SLA — in real time, at every call.
- Cost-optimal model selection
- Latency p50/p99 enforcement
- Quality drift protection
- Fallback chain management
- Multi-provider arbitration
Margin Engine
Hard budget caps per team, agent, and billing period — enforced at the runtime layer. When spend approaches limits, Azoth acts. Not alerts. Action.
- Hard limits per team and agent
- Real-time consumption tracking
- Automatic cost-mode throttling
- Slack + PagerDuty alerting
- Period-end forecasting
Semantic Cache Layer
Identical questions rarely arrive identically phrased. We match semantically equivalent queries to cached responses — eliminating redundant model calls.
- Intent-level matching
- 30% avg elimination rate
- TTL + invalidation control
- Per-agent cache policies
- Vector similarity scoring
AI FinOps Command Center
Full cost attribution by agent, model, team, and workflow. Real-time spend, anomaly detection, and 90-day economic forecasting. Finance and engineering, unified.
- Real-time execution stream
- Attribution by team and agent
- Economic forecasting engine
- 90-day cost modeling
- Warehouse export (S3, Parquet)
Projected/modelled figures based on a reference enterprise workload. How we compute these →
Simple pricing. Immediate ROI.
Pro teams recover their annual subscription cost in the first 30 days — on average. Guaranteed or we'll show you exactly why.
Sovereign deployment · OVH · Scaleway · SAML SSO · SOC 2 · HIPAA · Dedicated AI engineer
Govern, route and prove a single team’s AI.
Start 14-day trial- 100K AI operations / month
- 5 provider connectors
- 10 agents
- Full decision audit trail
- Budget enforcement & caps
- Prompt Intelligence Engine
- Semantic cache layer
- AI FinOps command center
- 90-day trace retention
- Email support
Multi-model governance, quality gates and full audit for AI teams.
Start 14-day trial- 5M AI operations / month
- Unlimited connectors & agents
- Everything in Starter
- SSO (OIDC) + RBAC
- Golden-dataset regression tests
- AI quality scoring
- Custom routing & governance policies
- Full signed audit trail
- 365-day retention
- Priority SLA
AI is the most powerful technology ever deployed at scale. It is also the most expensive.
In the beginning, the cost was invisible. A prototype. A demo. A proof of concept. The tokens were cheap. The bill was abstract. Then the models got better. And the products got real. And the agents started running — autonomously, continuously, at scale. And the costs became material.
We built Azoth because we saw what was coming. Not a monitoring problem. Not a dashboard problem. A structural problem — economic and now regulatory — built into the architecture of AI itself. When AI makes decisions at scale, efficiency and auditability stop being separate concerns. The EU AI Act turns the second one into law.
Every token spent without optimization is a fraction of a margin. At a million calls per day, those fractions become hundreds of thousands of euros. Compounding. Silent. Inevitable.
The alchemists believed in a universal substance — something that could transmute any material into its highest form. They called it Azoth. We believe AI infrastructure has a highest form too. Not the most expensive. The most efficient. The most economically precise.
The companies that define the next decade of technology will not just be the most intelligent. They will be the most economically indestructible. We exist to make that possible.
Your AI is making decisions you can't audit.
Take them back.
One SDK. Five minutes. Wire your policies — Azoth enforces them, traces every call, and exports the evidence.
npm install @azoth/sdkNo credit card. No code changes. Connects in 5 minutes.