Construction-management discipline, applied to AI.
Disciplined projects don't get delivered by hope and a Gantt chart. Neither do AI rollouts. Our five-step process mirrors how good work actually gets built — scope, plan, build, measure, learn — with humans verifying every critical step. We specialize in CRE and construction, but the discipline applies wherever complex workflows need thoughtful AI.
- 01
Discover
Before we recommend a single tool, we listen. We meet the people doing the work, sit through the meetings, and read the actual artifacts — draws, change orders, lease packages, RFIs.
- Stakeholder interviews across leadership, ops, and field
- System and tooling inventory
- Existing AI and automation efforts review
- Strategic intent and constraint capture
- 02
Assess
We map the in-scope workflows end to end and score them against AI readiness — data, process, people. The output is a register of opportunities ranked by ROI, risk, and effort.
- Workflow and data flow mapping
- AI readiness scoring
- Quick-win identification (90-day plays)
- Foundational gap identification (data, process, governance)
- 03
Advise
We turn the assessment into a sequenced plan. Vendor evaluation is honest — we'll tell you when off-the-shelf fits and when it doesn't. Custom builds are scoped when the workflow demands it. Every plan includes human verification checkpoints and fail-safes where AI typically breaks down.
- Sequenced roadmap with build-vs-buy decisions
- Per-initiative ROI model
- Vendor evaluation, custom architecture, or both
- Human-in-the-loop workflow design
- Data, security, and governance plan
- 04
Deploy
Pilots are designed with the people who will use them. We build, integrate, or coordinate vendors as needed — then train the field, instrument adoption, and keep humans verifying every critical output before it moves downstream.
- Pilot design with success metrics and rollback criteria
- Custom build, integration, or vendor coordination
- Human-in-the-loop verification at critical steps
- Field training and change management
- Adoption telemetry and performance reporting
- 05
Iterate
Every quarter we review what's working, what isn't, and what's next. AI is moving fast — your roadmap should compound, not ossify.
- Quarterly business review against ROI baseline
- Adoption health check
- Roadmap re-sequencing as the market evolves
- Knowledge transfer to your internal team
Four lenses we apply to every engagement.
Data integrity first
AI is only as good as the data feeding it. We assess what you have, what you're missing, and what's worth fixing before you spend on tools or custom builds.
Fail-safes where AI breaks
We map where AI typically fails in each workflow — hallucinations, edge cases, stale data — and design checkpoints so those failures get caught before they cost you money.
Human in the loop, always
AI gets you 80–90% there fast. People verify, refine, and approve the rest. Every workflow we design assumes imperfect AI and builds in the human judgment that closes the gap to 100%.
ROI defended
Every initiative has a baseline, a target, and a measurement plan. Boards and lenders get numbers they can trust — not vanity metrics from a pilot that never scaled.
Ready to walk through your workflows?
The first call is a structured conversation about your operation, your goals, and whether we're the right partner. Direct, honest, no deck.