AI Agent Rescue: Results
What a AI Agent Rescue engagement delivers
AI Agent Rescue is a remediation engagement for AI agents that stall between pilot and production. We instrument the agent with tracing, reproduce the failures, and produce a root-cause report covering tool errors, memory/state issues, unhandled edge cases, and context debt — then harden the architecture with retries, state recovery, human-in-the-loop gates, and an evaluation harness. A diagnostic runs 1–3 weeks, followed by fixed-scope remediation.
Diagnostic to a runtime-evidence root-cause report
Failure modes targeted: tool errors, state/memory, edge cases
Fixes backed by traces and evals — not guesses
Representative outcomes based on typical engagements and published industry benchmarks. Figures illustrate what a well-scoped engagement targets, not a guarantee.
Be our first published AI Agent Rescue
We're selecting a launch engagement to document as a full public case study — with your results, your name, and your logo (with your permission). Early partners get priority scheduling and preferred pricing.
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Instrument & Reproduce
We add distributed tracing and reproduce the failures instead of guessing — no fix without runtime evidence.
Root-Cause Analysis
We pinpoint whether failures come from tool calls, memory/state, edge cases, or context debt, and quantify each.
Stabilize & Harden
We add error-recovery logic, state management, guardrails, and human-in-the-loop gates at the points that actually break.
Eval Harness & Handover
A regression-catching evaluation suite plus dashboards and documentation so the agent stays healthy in production.
Want results like these?
Typical timeline: 1–3 week diagnostic, then fixed-scope remediation. Let's scope your engagement in a free call.
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