Fixed-scope diagnostics and retainer-ready operations, mapped to the Assess / Architect / Operate arc. Engagements scale from a two-week diagnostic to a full managed operations partnership — structured by where the business is in the adoption journey.
Structured self-evaluation that produces an AI Readiness Score and identifies the highest-leverage adoption starting points.
Fixed-scope 1–2 week evaluation of data completeness, consistency, and pipeline readiness before analytics or AI build work begins.
AI asset inventory, risk matrix, and framework mapping against NIST AI RMF, EU AI Act, and ISO/IEC 42001 — with a hardening roadmap.
Benchmark coverage matrix, tool-fit map, and remediation backlog across CIS and DISA STIG control sets. Primary entry point for compliance work.
Strategic and technical guidance on AI integration: tool selection, architecture decisions, and implementation roadmaps built for production, not proof of concept.
Replaces manual, fragmented reporting stacks with automated, audit-ready infrastructure across the tools already in use.
End-to-end pipeline design and build — extract, transform, load, validate — reducing manual data movement and keeping downstream systems current.
CIS/STIG-aligned remediation automation using Ansible, PowerShell, and Terraform; plus target-state architecture for continuous drift detection.
Production dashboards with custom DAX logic, slicers, and KPI frameworks — designed for the stakeholder who makes decisions from them, not just reviews them.
Ongoing QA frameworks and validation scripts that catch data accuracy and consistency failures before they reach reporting or compliance evidence.
Executive and board-level reporting packages that translate operational data into communicable intelligence without stripping out the context.
Monthly compliance engineering: reporting, triage, exception handling, remediation coordination, and benchmark version management.
Automated evidence packages, control narratives, and executive summaries that reduce audit prep from months to a repeatable workflow.
Fixed-scope, forward-deployed engagement that delivers a first working AI or automation workflow inside your environment — scoped, built, and documented for hand-off or continued partnership.
Engineers embedded inside your environment, building production AI applications against real workflows. The delivery pattern Anthropic, OpenAI, and the leading SIs use — scoped for regulated mid-market and PE-backed organizations.
Executive or team session on AI adoption, compliance engineering, or data strategy — structured for decision-makers, not just practitioners.
The AI Readiness Self-Assessment is a free, async diagnostic that produces a Readiness Score and identifies the highest-leverage adoption starting points for your business. Built for leaders who know AI matters but aren't sure what to do first.
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