AI Production Readiness
Move from a promising AI prototype to a production system your team can observe, operate, secure, and improve without uncontrolled cost or risk.
Readiness score across product, data, model, infrastructure, security, and operations
Concrete launch blockers, risk owners, and a prioritized remediation roadmap
Evaluation, monitoring, rollback, and cost-control plan for production AI systems
Scope
Production readiness reviews for AI agents, RAG pipelines, LLM features, and internal AI tools, covering evals, guardrails, observability, costs, and incident readiness.
Use-case fit, success metrics, escalation paths, and human-in-the-loop boundaries
Prompt, tool, and retrieval evaluation coverage with regression fixtures
RAG quality, source freshness, data contracts, and hallucination failure modes
Model gateway design, rate limits, fallback models, token budgets, and cost telemetry
Tracing, audit logs, drift signals, red-team cases, and incident response runbooks
Privacy, data retention, access control, and vendor boundary review
Discovery call and architecture walkthrough
Hands-on review of prompts, pipelines, telemetry, deployment, and security controls
Findings workshop with prioritized fixes and ownership
Optional implementation sprint for the highest-risk gaps
Risk Signals
AI features that work in demos but lack measurable quality gates
RAG pipelines with no retrieval diagnostics or source-quality feedback loop
Token costs and latency that are invisible until traffic grows
No safe rollback path when a model, prompt, or provider behavior changes
Short answers before the discovery call.
No. The review is useful for LLM applications, agents, RAG systems, ML-backed workflows, and AI-assisted internal tools where reliability and governance matter.
Yes. The first engagement can be an assessment only, or it can continue into a focused implementation sprint for evals, observability, deployment, or security controls.
Usually architecture diagrams, code or pipeline access, prompts or system instructions, model gateway configuration, telemetry, and a walkthrough with the owning engineers.
Useful next pages if you are comparing scope.
