Consulting

AI Readiness & Maturity Assessment

Time Needed: 2–4 weeks depending on org size.

Depth & Focus: Interviews with leadership + technical teams, review of policies and pipelines, maturity benchmarking against NIST AI RMF / ISO 42001 / EU AI Act.

Output/Value:

• Readiness report with maturity scores (Governance, Data, MLOps, Observability).
• Gap analysis + prioritized roadmap.
• Clear “next step” recommendations 

AI Governance & Compliance

Time Needed: 6–12 weeks.

Depth & Focus: Develop responsible AI frameworks, regulatory mapping, compliance risk assessment, and internal audit structures.

Output/Value:

• Custom AI governance framework aligned with regulations.
• Risk register + mitigation playbook.
• Draft AI policies and documentation templates.
• Executive buy-in on compliance program.

Data Governance for AI

Time Needed: 6–10 weeks.

Depth & Focus: Data lineage, cataloging, quality standards, privacy/bias checks, integration with existing governance tools.

Output/Value:

• Audit-ready data governance framework for AI.
• Metadata + lineage models tied to compliance requirements.
• Practical data quality dashboard.
• Reduced risk of biased/unreliable data fueling AI.

MLOps & LLMOps Governance

Time Needed: 8–12 weeks.

Depth & Focus: Design or refine pipelines, add governance and compliance controls, evaluate tooling, optimize cost vs. compliance.

Output/Value:

• Well-architected, compliant AI pipeline design (docs + workflows).
• Governance checkpoints in model lifecycle (training → validation → deployment).
• Lowered operational risk + improved efficiency.

AI Observability Programs

Time Needed: 6–8 weeks.

Depth & Focus: Build observability frameworks for post-deployment AI, including drift detection, bias monitoring, incident response, explainability dashboards.

Output/Value:

• Observability playbook (tools, processes, workflows).
• Bias/drift monitoring dashboard design.
• Continuous compliance reporting framework.