Scope extraction
Read plans, RFPs, inspection notes, service requests, and photos to organize the work before estimating.
We build internal AI products for plan and RFP review, inspection-to-estimate workflows, technician and equipment scheduling, parts coordination, proposals, and invoicing.
We begin with the operating reality, then design the product around the people, decisions, rules, and evidence already in the work.
Read plans, RFPs, inspection notes, service requests, and photos to organize the work before estimating.
Apply your assemblies, labor assumptions, exclusions, and approval rules to a reviewable draft.
Coordinate technician skills, equipment availability, parts, location, and service priority.
Collect completion evidence, change details, recommendations, and customer approval before billing.
Not a standard product you have to work around. A focused operating layer that can connect the tools and data you already use.
Source documents, extracted scope, assumptions, and review checkpoints together.
The next best assignment based on urgency, skill, route, parts, and availability.
Mobile job context, evidence capture, customer communication, and recommended follow-up.
Surface missing scope, unresolved change work, and unbilled completion before margin disappears.
These are study results, not forecasts for your business. We use them to establish plausibility, then model your ROI from your own volume, time, labor cost, error rate, and throughput.
Average result in a real-world deployment across 5,179 customer-support agents; less-experienced workers saw gains up to 34%.
NBER field study ↗A Harvard/BCG field experiment also found more than 40% higher quality on knowledge-work tasks inside the AI capability frontier.
Harvard Business School / BCG ↗Average firm-level effect in a 2026 BIS/EIB study of more than 12,000 non-financial firms adopting AI with complementary investment.
BIS / EIB study ↗We’ll show you the internal AI product that can simplify it.
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