Four ways we work
with you.
Each engagement starts where you are. Every one ends with something your team can use.
AI Opportunity Mapping
Find the right opportunities before you spend.
We review your workflows, find where time and money leak, and rank AI opportunities by business value and implementation effort. You leave with a prioritized list, quick wins, and a roadmap, before you spend anything on tools.
Risk-free: If we complete the audit and cannot identify one clear AI opportunity worth testing, you do not pay.
Includes
- Workflow and process review
- Opportunity ranking by value and effort
- Quick wins list
- Tool and vendor shortlist
- Roadmap and next steps
- Measurement plan
Implementation Sprints
Build the systems. Ship them fast.
Once the roadmap is set, we build in short, scoped cycles. Each sprint takes one prioritized opportunity from prototype to a working system your team can test in production. Defined deliverables, fixed timelines, no scope creep.
Includes
- Sprint scoping and planning
- Prototype and test cycle
- Integration with existing tools
- Team training and handoff documentation
- Post-launch review
Responsible AI Workflows
Governed from day one, not bolted on later.
We design oversight into every system from day one: who reviews AI outputs, how errors surface, what the escalation path looks like, and how decisions get documented for compliance. Governance built in, not bolted on.
Includes
- Human-in-the-loop design
- Audit trail and logging setup
- Data handling policy review
- Error escalation paths
- Compliance documentation
Team Enablement
Built for adoption, not just demonstration.
Most AI projects fail because the team stops using them after week two. We address adoption before launch with role-specific training, plain-language documentation, and a 30-day check-in to catch what breaks in real use.
Includes
- Role-specific training sessions
- Plain-language documentation
- Feedback and iteration cycle
- 30-day adoption check-in
- Ongoing advisory access