AI READINESS AUDITAI Readiness AuditKnow What to Build, Before You Spend a Dollar Building It
A 4-week diagnostic that maps AI opportunity across your workflows, identifies compliance exposure, and tells you exactly what to build first.
Sound Familiar?
Board mandate for AI. Three vendor proposals on your desk.
Two internal pilots that worked in demo, and stalled before production.
Compliance officer asking questions nobody can answer yet.
Engineering team capable and ready, pointed in three different directions.
This is not a technology problem. It is a sequencing problem.
The question is not whether AI will change how your organization operates.
The question is which workflow to build first, and what needs to be true before that build begins.
WHAT GENERIC AI ASSESSMENTS MISS
Most Assessments Miss What Actually Kills AI Pilots
They measure culture, change appetite, and adoption maturity. What they miss is what actually kills pilots:
Data that looks clean in aggregate, and breaks on the edge cases that matter
Compliance constraints that only surface when the vendor contract hits legal
Model economics that looked fine in the sandbox, 3–5X more expensive at production volume
Eval gaps that let a system look correct in testing while failing silently in production
EPixelSoft's audit is built around these failure modes specifically.
How the Audit Runs, 4 Weeks, 6 Areas
Workflow Opportunity Mapping
Reviews 3–6 candidate workflows. Scores each on decision complexity, data availability, volume economics, compliance exposure, and cost of a wrong output. Output: ranked opportunity map with a primary recommendation.
Data Readiness Assessment
Not a general data quality audit. A targeted evaluation of whether the data for your nominated workflow is clean, accessible, and structurally compatible with the required AI pattern.
Model Economics Analysis
Token cost projections, latency modeling, and infrastructure cost estimates at production volume. Most organizations discover their vendor's proposed architecture costs 3–5x more than quoted when run against real query volumes.
Compliance & Security Posture Review
Coverage of HIPAA, SOX, GLBA, EU AI Act, and applicable state regulations. Identifies blocking constraints before the build, not after the first legal review.
Eval & Observability Gap Analysis
Assesses whether you have the infrastructure to know if your AI system is working after it ships. Most organizations do not. This section identifies what needs to be built before deployment.
Vendor & Architecture Review
Already in conversation with an AI vendor? EPixelSoft independently assesses the architecture, pricing model, and contract terms against what your workflow actually requires.
No system access required : The audit runs on documentation, stakeholder interviews, and working sessions.
What You Receive After 4 Weeks
Six presentation-grade deliverables, built for two audiences simultaneously.
AI Opportunity Map
Ranked workflow assessment, primary recommendation, sequenced backlog
CTO + Engineering Lead
Architecture Brief
Stack, retrieval pattern, agent design, eval approach. Scopeable immediately.
CTO + Engineering Lead
90–Day Implementation Roadmap
Phased plan from audit through first production deployment
Engineering Lead
Risk & Compliance Review
Regulatory exposure with architectural mitigations specified
Legal + Compliance
Quick-Win Pilot Recommendation
One workflow shippable in 6–10 weeks at contained scope
Product + Ops
Executive Briefing
8–12 slides: opportunity sizing, risk summary, investment framing
CFO + Board
The Executive Briefing is the document most clients use to get internal budget approved.
Where the Audit Has Surfaced Opportunity
Commercial Lending
Audit identified the specific decision nodes where AI would reduce underwriting cycle time and the two where human judgment was non-negotiable.
The subsequent Cognitive Workflow Re-Architecture engagement reduced underwriting time from
Funderial LLC, US. Named with permission
Clinical Operations
Audit evaluated three competing AI approaches for a prior authorization backlog.
Recommended Vertical RAGover a more sophisticated agentic approach that carried higher hallucination risk in a clinical context.
Build shipped to production within one quarter of audit completion.
Product Teams
Recurring audit findings :
LLM selected for demo quality over production cost
Eval infrastructure absent
Retrieval architecture degrading on real user queries
Surfaces these gaps before they become sunk costs
Is This the Right Starting Point?
GOOD FIT IF
Mid-market or enterprise in FinTech, HealthTech, InsurTech, LegalTech, or AI SaaS
You have workflows in mind but aren't certain which to prioritize
You've had a failed pilot and need a defensible path forward
You need board-level buy-in before committing engineering budget
NOT A FIT IF:
Early exploration mode with no specific workflow in mind
Looking for a vendor to validate a decision already made
The audit is a diagnostic. If findings point away from AI for a given workflow, that is what the report says.
Start the Audit
Begins with a 30-minute scoping call. Bring your AI initiatives, the workflows you're considering, and one stakeholder each from engineering and the business side.
Not ready for the full audit?