Services
Plan, implement, monitor, improve.
Four stages that repeat. Start with any one; most clients begin with Plan.
Plan
Decide what to build, and what not to, before spending on it.
- AI readiness audit across governance, data, security, workflow, tooling and leadership.
- Use-case prioritization ranked by value, effort and risk.
- AI acceptable-use policy, data rules and human-review requirements.
- Reference architecture and a 30, 60 and 90 day roadmap.
Implement
Put AI into the systems you already run, securely.
- Agents, assistants and workflow automation integrated with ERP, CRM and internal data.
- Deployment on AWS, including AWS GovCloud for regulated workloads.
- Compliance controls built into the inference path, including content blocking with Claude inference hooks.
- Engineering support alongside your team, with documentation and handover.
Monitor
Know what your AI is doing, what it costs and whether it is safe.
- Cost attribution by team, application and model.
- Quality, safety and policy-violation tracking, with alerts.
- Audit logs suited to security and compliance review.
- Monthly health report for leadership.
Improve
Keep the investment compounding.
- Quarterly reviews that retire, tune or expand use cases.
- Prompt, model and architecture optimization based on monitoring data.
- Role-specific training for teams and managers.
- A standing roadmap for the next wave of use cases.
Every engagement is custom-built to your environment. We start with a fixed-scope audit, then scope projects and ongoing support from what we find.