Experiments

Narrow experiments tied to real workflow handoffs.

Each experiment targets a specific operational drag point and keeps the scope tight enough to stay reviewable.

Experiment

Photo-to-observation routing experiment

Test how little structured input is needed to turn field photo capture into a reviewable issue draft.

Boundary: Bounded to classification, location suggestion, and follow-up routing. It does not auto-close work or invent project facts.

Technical shape: Mobile-first intake, metadata extraction, rule-based enrichment, and operator review inside a narrow workflow lane.

Why it matters: Supports quality, safety, and progress workflows where speed matters but trust still has to be earned.

Experiment

Reduce the manual drag of sorting and checking closeout documentation before turnover.

Boundary: Targets extraction, checklist matching, and exception surfacing only. Final package approval remains human-owned.

Technical shape: Python document parsing, structured record creation, and a Next.js review queue tied to source documents.

Why it matters: Addresses a repetitive pain point with clear business value and visible review boundaries.

Experiment

Turn fragmented daily updates into a concise operational brief for PM and operations review.

Boundary: Summarizes supplied inputs and cites sources; it does not generate progress claims beyond available evidence.

Technical shape: Event intake, source-aware summarization, and publish-on-review outputs for email, dashboards, or customer updates.

Why it matters: Demonstrates AI as an operational assistant instead of a freeform chatbot.