Services
Strategy first.
Depth when required.
Enterprise AI strategy for leaders already in the chair.
Flagship
C-suite advisory for the operating model.
AI in a funded, governed place in the business. This is the offer.
AI readiness in the operating model
Data, accountability, talent, culture. What the business can absorb. Not a maturity score.
Enterprise AI roadmap & vision
A multi-year view tied to the P&L. What to fund. What to sequence. What success looks like.
Use-case judgment & prioritization
Scored by impact, feasibility, risk, and fit. Including a recommendation to stop.
AI governance & ethics
Transparency, bias, agent guardrails, regulatory exposure. Owned by the executives accountable for them.
Change and adoption
Sponsorship, workflow redesign, the conditions under which adoption holds.
Supporting
Agents & automation
Autonomy when it is the right instrument. Design, boundaries, oversight.
Autonomous agent design
Agents that can reason through multi-step work. A clear statement of what they may and may not decide.
Multi-agent orchestration
Specialized agents that collaborate. Only when a single system would be the worse design.
Tool-integrated agents
MCP- and API-connected agents in enterprise systems. Access treated as a governance problem.
Workflow redesign
Adaptive workflows in place of brittle automation. Human checkpoints included.
Guardrails & evaluation
Testing, safety boundaries, monitoring. Autonomy stays inside a defined mandate.
Supporting
Implementation
Depth when strategy requires it. Data foundations to production. Not a delivery bench.
Custom AI/ML solutions
When a generic model will not carry the decision. Problem, data, training, optimization.
LLM & generative systems
RAG, generation pipelines, foundation-model integration against a stated business use. Not a demo.
Data & pipeline engineering
The production data path. Pipelines, feature stores, vector retrieval, streaming the model depends on.
Platform architecture
Vendor-agnostic AI platform. Cloud, hybrid, or on-premise. Scale and compliance as constraints.
Production & LLMOps
CI/CD for models and agents. Evaluation, drift, the cadence a team needs to own the system.
Start with the strategy question.
If you need a vendor bench, we are the wrong firm.