Capabilities

What it takes to get AI into production and keep it there.

Advisory, deployment, platform, trust and operations, held to one standard from first workshop to steady state.

Advisory

5 disciplines

  • AI Strategy

    Board-level AI thesis, value maps and a sequenced portfolio tied to P&L outcomes.

  • AI Transformation

    Operating-model redesign across people, process, platform and controls.

  • Executive Advisory

    Standing counsel for CEO, CIO, CISO and board AI committees.

  • Enterprise AI Readiness

    Quantified diagnostic across data, platform, talent, governance and risk.

  • Vendor Selection

    Model, platform and integrator evaluation with defensible scoring.

Deployment

3 disciplines

  • Forward Deployed Engineers

    Embedded engineers shipping production AI inside your environment.

  • Enterprise AI Office™

    A fully staffed AI deployment organization operated on your behalf.

  • AI Program Management

    Portfolio governance, stage gates, and executive reporting cadence.

Platform

5 disciplines

  • AI Architecture

    Reference architectures for retrieval, agents, evaluation and observability.

  • LLM Deployment

    Private model hosting, routing, caching and cost control at scale.

  • Custom AI Platforms

    Internal AI platforms with tenancy, policy, audit and self-service.

  • AI Integration

    Connecting AI to core systems: ERP, CRM, EHR, core banking, data mesh.

  • Agentic AI

    Tool-using agents with permissioning, human checkpoints and rollback.

Trust

5 disciplines

  • AI Security

    Threat modeling, red teaming, prompt-injection and data exfiltration defense.

  • AI Governance

    Policy, model registry, approval workflow and lifecycle accountability.

  • Responsible AI

    Fairness, transparency and human-oversight standards that survive audit.

  • Risk Assessments

    Model, vendor and use-case risk tiering aligned to enterprise risk frameworks.

  • AI Compliance

    EU AI Act, NIST AI RMF, ISO 42001 and sector regulator readiness.

Operations

5 disciplines

  • Model Evaluation

    Golden datasets, offline and online evals, regression gates before release.

  • Prompt Engineering

    Versioned prompt assets, testing harnesses and quality baselines.

  • AI Operations

    SLOs, drift detection, incident response and continuous evaluation.

  • Managed AI Services

    Run-state ownership of AI systems under contractual service levels.

  • AI Centers of Excellence

    Standards, enablement and reusable assets that compound across the firm.

Next step

Book a working session.

Sixty minutes with a Chief AI Advisor and a forward deployed engineer. We read your environment, name the blockers, and give you the shortest path to a system in production.