Overview
AI-native architecture, data platforms, and automation that produce real leverage — not pilot decks.
Most AI programs are stuck between proof-of-concept and production. The bottleneck is rarely the model; it is the data foundation, the workflow design, and the operating model around it.
We design and stand up the digital and AI layer that lets a business compound: clean data, agentic workflows, governance that scales, and a delivery cadence that ships rather than studies.
Capabilities
AI strategy & architecture
Where AI creates durable advantage, what to build vs. buy, and the reference architecture to support it.
Data platforms
Warehouses, lakehouses, semantic layers, and the identity graph that lets every team trust the same numbers.
Agentic workflows
Production automation across GTM, ops, and research — designed for reliability, observability, and human-in-the-loop control.
AI governance
Policy, risk, and assurance frameworks that meet regulator expectations without strangling delivery.
Engagements
- 01AI strategy and value-pool diagnostic
- 02Data foundation and platform reference design
- 03Agentic workflow build-outs (GTM, ops, research)
- 04AI governance and operating-model design
Questions we work on
- Where will AI compound advantage in our business — and where is it a distraction?
- What data do we need to own, and what is safe to rent?
- How do we move from pilots to production without a year of rebuild?
- What governance keeps us defensible without slowing the work?