Try for Free

Built for teams shipping AI agents

See the business tasks your agents run. Catch and fix the ones going wrong in hours.

Autonomous Reliability Loop for AI Agents

Lumoz pinpoints where your business tasks fail … automatically.
Finds anomalies & drifts nobody defined.
No evals to set up.
Fix your agentic workflows in hours.

Try for Free →
Business task health card for Cancel Pending Order: success rate 74%, down 9 points over the last 24 hours across 1,284 runs; top signal Context Amnesia with 38 occurrences; average latency 1.8 seconds and average cost $0.12. Labelled failure detected, fix recommended, and eval generated.
Why Lumoz

Telemetry In. Fixes and Evals Out.

Traditional tools need evals and datasets before they can tell you anything.
Lumoz starts with the telemetry you already have and works in the opposite direction.

The usual direction

Build datasets→ Write evals→ Sample traffic→ Run tests→ Answers weeks to the first fix

The Lumoz loop

The Lumoz loop: the customer's production agent sends telemetry to Lumoz, which ingests it, identifies business tasks, detects problems with root causes, and recommends fixes and evals - handed to the customer's coding agent via Lumoz MCP and Skills, which deploys the fix back to the production agent. Autonomous loop, hours to the first fix.
01 · Business Task

Lumoz discovers Business Tasks your agents perform.

Inferred from your telemetry: goal, trajectory, and outcome - then monitored for failures on every run.

Journeys view: business tasks flowing through agents, tools, and models to outcomes, with failure signals highlighted
02 · Detect

Signals built in.
Drifts and Anomalies learned.

  • Built-in signals: quality, tool usage, loops, RAG, orchestration, operational
  • Agentic security, aligned to OWASP: sensitive leakage, excessive agency
  • Anomalies, drifts, and cohort shifts, learned from your traffic
  • Custom signals, written in plain language
Signal catalog: one-agent signals for quality, safety, RAG, tool usage, and conversation; multi-agent signals for reasoning, loops, orchestration, and cascading failures; learned anomalies and drifts; custom signals in plain language
03 · Resolve

From hundreds of signals
to one root cause.

  • Collapses related failures into a single problem
  • Traces causality across agents, tools, and models
  • Shows the root cause per problem, with its evidence
Root cause analysis for the Cancel Pending Order task: the agent loses complaint context in long sessions, so users repeat themselves and cancellations fail or escalate. The root cause is conversation history being truncated after 12 turns.
04 · Recommend

Fixes and evals,
recommended and delivered.

  • Recommends the fix, grounded in the telemetry that found it
  • Generates evals from the real failure, in your eval tool of choice
  • Handed to your coding agent over Lumoz MCP & Skills
Recommendation card for the Cancel Pending Order task: the recommended fix is to pin the complaint summary to agent memory and cap serialized history at 32k tokens; a generated eval replays the failing sessions against the fix and guards the regression on every release; delivered to your coding agent over Lumoz MCP and Skills.

Lumoz MCP & Skills close the loop - from detection to a deployed fix.

Popular agent frameworks are supported.

Customers

“The future of agentic AI will be defined not just by intelligence, but by trust, security and reliability. Lumoz is helping us turn this vision into reality, transforming real-time insights into continuous improvement and building more resilient AI agents with every iteration. An exceptional team with deep expertise in agentic AI.”

CEO, Tabhi

Writing

Notes from the founders.

Medium

AI Agent Reliability in Production: A Fraud-Detection Mindset

Find production failures the way fraud teams find fraud.

LinkedIn

Out of Stealth: Building Lumoz AI

Why I've been in stealth, and what I've been building.
Try for Free

Try Lumoz.

We will only use this to get back to you.