Microsoft dropped the DELEGATE-52 benchmark this month. The result: AI agents lose significant content quality across extended task chains. Only Python programming passed the readiness threshold after 20+ delegated interactions.
Anthropic responded with evaluator models. Honeycomb launched Agent Timeline. Palo Alto Networks is acquiring Portkey for agent security.
But nobody has built the actual monitoring layer that sits between your agent and the world, checking every output. So I built it.
Agent Reliability Monitor
A proxy layer that wraps your agent API endpoints and checks every interaction against 6 quality dimensions:
- Completeness — did the agent drop any instructions?
- Consistency — does the output match the input requirements?
- Hallucination — did the agent invent facts?
- Compliance — does it follow your business rules?
- Sentiment drift — is tone shifting over time?
- Task completion — did it actually finish the job?
Pricing (3 tiers)
| Plan | Price | Endpoints |
|---|---|---|
| Starter | £49/mo | 1 |
| Growth | £149/mo | 5 |
| Enterprise | £399/mo | Unlimited |
All tiers include daily drift reports and Slack alerts. Enterprise adds SOC 2 compliance reporting.
The Bigger Picture
We are deploying AI agents into production faster than we can monitor them. Every major research paper this quarter proves the same thing: agents drift. The tooling layer between "agent runs" and "agent works reliably" is where the next $10B companies get built.
This is my bet on that layer.
Try it at theaisuite.pages.dev/reliability — 7-day free trial, no credit card.
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