Applied Field Intelligence
Turn field data into decisions.
We build AI systems for field-based technical operations: over-the-air data collection, KPI analysis, and report generation, tied into managed projects with a full audit trail.
- Remote + on-site capture
- KPIs to compliance-grade reports
- Governed system of record
01 / The problem
The gap between the field and the decision is where programs stall.
Field-based technical work generates data faster than teams can turn it into answers. Measurements, telemetry, and notes arrive in a dozen formats; someone reconciles them by hand, keys them into a system, and rebuilds the same report every time.
Skilled hours vanish into transcription. Errors slip in exactly where they are hardest to catch.
02 / The method
One pipeline, from raw field data to a managed project.
Four stages, in order. Each one hands the next a clean input.
Collect
Capture from the field: over-the-air telemetry from connected devices and sensors, plus on-site measurements and notes. Every source, one intake.
Structure
Normalize heterogeneous inputs into a single schema and system of record. Nothing gets re-keyed by hand.
Analyze
Compute KPIs and reconcile measurements against targets and specifications; exceptions and pass/fail surface on their own.
Report & manage
Generate stakeholder-ready reports and roll the work up into tracked projects with status, risk, and a full audit trail.
Wrapped by governance: versioning, audit trail, and multi-interface access. That layer is what turns a report generator into a system of record.
03 / Built by practitioners
Built by people who have done the work.
Applied Field Intelligence comes out of real field operations, not a whiteboard. The hard parts are already solved: parsing proprietary instrument data, reconciling measurements to a governing spec, generating audience-specific reports, and holding it all in a governed system of record.
The result is faster turnaround, consistent quality, and deliverables that stand up to an audit. Expert judgment stays where it belongs, on the decisions; the pipeline carries everything around it.
04 / Where it applies
The same spine reads across field-based industries.
Anywhere teams visit a site, take measurements, and owe someone a report.
05 / How we work
We stress-test our own recommendations.
Rigor is the product. We red-team our own conclusions, verify the load-bearing facts, and would rather correct a thesis than defend it. What ships has survived that scrutiny.
Verify
Load-bearing facts get checked before they reach a recommendation.
Red-team
We attack our own conclusions first, while changing them is still cheap.
Correct
A thesis that fails review gets rewritten, not defended.
06 / Engage
Build your field-data system.
Three steps, smallest first. Each one is priced before it starts.
Discovery & fit
Map your site-visit-to-report loop end to end, then scope the build against what we find.
Pilot
One site to one compliant report. Prove the motion in weeks, with your own data.
Platform
Scale the pilot into a governed, multi-interface system of record for the whole operation.
Start with your worst reporting loop.
Describe one site visit and the report it owes. In 30 minutes we will tell you what the pipeline would look like and what it would cost.