How we work
How we engage.
A clear, sequenced path. Each phase produces a concrete deliverable and a decision point, so the work compounds and risk stays contained.
Engagement model
From assessment to scale.
- 01
Assess
4 to 8 weeks
Current-state assessment across capability, process, technology, and people. Pinpoint where AI compounds value and where governance is missing.
- 02
Design
4 to 8 weeks
Target-state architecture, governance model, and sequenced roadmap fit to your stack, compliance environment, and team maturity.
- 03
Build
Scoped to engagement
Deploy the orchestration, memory, and governance layers in your environment. Embed agents across the SDLC. Enable your teams.
- 04
Scale
Tailored to portfolio
Roll out across business units, carve-outs, or acquired entities. The standard you build once is replicable across the portfolio.
Governance built in
Compliance designed in, not bolted on.
Compliance and auditability are designed in from the first commit, mapped to SOC 2 and ISO 42001. Governance that gets adopted, not shelved at review.
Per-action approvals, immutable audit trails, and explainability. AI code passes the same controls as human code.
In-environment deployment
Your code never leaves your walls.
Deployed in your cloud and VPC, model-agnostic across Claude, Gemini, GPT, and more. Switch models when economics or capability change, with no rebuild.
In practice
What this looks like in practice.
One governed sequence. A memory hub feeds scoped context down to the agents and takes enriched context back up at each approved gate, so it compounds. A human gate sits between every stage, and the gate fires the next agent. Governed and measured throughout.
Same tickets. Same tools. Same pipeline. Same controls.
What changes: context assembles itself, governance is built in, every cycle compounds.
Run a 2-week discovery.
A short, scoped engagement that shows where the layer goes and what it changes.