Enterprise AI Reliability
Make enterprise AI agents safe enough to scale.
Independent production-readiness reviews for copilots, RAG systems, customer-service agents, analytics agents, and workflow automation tools.
Enterprise agents fail differently in production.
Demos usually test ideal prompts. Production exposes ambiguity, missing context, tool failures, permission boundaries, escalation gaps, and model regressions.
Customer-facing agents giving unsupported answers
Internal copilots retrieving the wrong policy or document
Analytics agents explaining KPIs with incorrect assumptions
Workflow agents calling tools with bad parameters
Agents failing silently when APIs or retrieval systems degrade
No clear ownership when an AI system behaves incorrectly
What we test
Production readiness across the workflow, not just the prompt.
Task success
Grounding and factuality
Retrieval quality
Tool/API behaviour
Permission boundaries
Prompt-injection resistance
Escalation and handoff paths
Regression across prompt/model changes
Monitoring and incident readiness
Offer
AI Agent Reliability Audit
A fixed-scope review that turns vague production risk into concrete evidence, test scenarios, and risk-ranked recommendations.
Deliverables
- Workflow review
- Failure-mode map
- Scenario test pack
- Eval and regression recommendations
- Observability gap assessment
- Risk-ranked findings
- Production-readiness scorecard
- Executive readout
Best fit
Heads of AI, CIOs, Chief Data Officers, AI transformation leads, and enterprise teams deploying agents internally or to customers.
Request a reliability auditEnterprise reliability review
Can your agent be trusted in production?
Tell us what you are building, evaluating, analysing, or trying to automate. We will help choose the right service path.
Prefer email? drew@agent-reliability.com