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AI PRODUCTION READINESS REVIEW

Find out why your AI pilot is not ready for production.

A paid, bounded technical and operating review for organizations with a prototype, agent, AI application or internal pilot that must become secure, testable and supportable.

Bring the existing pilot, intended users and operating context. The review identifies material gaps and a prioritized path; it does not certify the system or promise that every pilot should proceed.

Discuss your AI opportunity Compare IFDS engagement paths
THE BUYER'S QUESTION

What would fail, leak, drift or become unmanageable after launch?

A convincing demonstration rarely proves permissions, failure behavior, evaluation quality, data boundaries, observability or operational ownership. The review examines the real system boundary and the evidence required for a responsible production decision.

REVIEW SCOPE

Assess the production system, not only the model response.

01

Architecture & integration

System boundaries, APIs, data flows, dependencies, failure handling and deployment design.

02

Security & permissions

Identity, authorization, secrets, data boundaries, auditability and abuse or injection paths.

03

Evaluation & controls

Representative test cases, regressions, human escalation, error analysis and acceptance evidence.

04

Operations & ownership

Observability, cost, support, change control, rollback, incident handling and accountable owners.

WHEN TO USE THE REVIEW

The prototype works. The production decision is still exposed.

This review is designed for a system that already exists: an internal pilot, RAG assistant, AI-enabled application or agentic workflow. It is especially useful before a larger build, vendor commitment, security approval or launch decision.

Reliability is anecdotalThe demo looks good, but representative evaluations and regression evidence are missing.
Architecture grew around the pilotDependencies, failure modes, scaling limits or provider lock-in are not yet understood.
Controls are unresolvedPermissions, sensitive data, human oversight, audit trails or governance ownership remain unclear.
Operations have no ownerMonitoring, incident response, cost control, model changes and rollback are not production-ready.
ASSESSMENT DIMENSIONS

A senior review across engineering, AI behavior and enterprise control.

The emphasis follows the system and its risk. The review is not limited to a fixed checklist.

System engineering

Architecture, maintainability, scalability, latency, infrastructure, integrations, resilience and deployment.

AI quality

Evaluation design, hallucination risk, RAG quality, agent behavior, model dependencies and regression control.

Security & data

Identity, permissions, data handling, secrets, prompt-injection paths, auditability and vendor boundaries.

Operations & economics

Observability, cost drivers, support ownership, incident handling, change control and rollback.

Governance & oversight

Human review, escalation, accountability, acceptable use, evidence and decision authority.

Production acceptance

Launch criteria, residual risks, remediation dependencies and the evidence required for approval.

PRODUCTION READINESS REPORT

A prioritized decision package, not a generic checklist.

  • Current-state architecture and evidence summary
  • Launch blockers, material risks and missing controls
  • Prioritized remediation roadmap with dependencies
  • Production acceptance and operational-readiness criteria
  • Proceed, remediate, redesign or stop recommendation
WHAT HAPPENS NEXT

The review creates a controlled next commercial decision.

  1. RemediateClose bounded blockers in the existing system.
  2. BuildMove into an IFDS production engagement when redesign or implementation is justified.
  3. ExpandCoordinate broader workstreams or an IFDS-managed Delivery Pod only when the scope requires it.
A CONTROLLED NEXT STEP

Turn production uncertainty into an owned remediation decision.

The output separates launch blockers, important improvements and accepted residual risks, then defines whether IFDS production delivery is an appropriate next engagement.