AI for the work between the engineer, the office, and the customer.
Site notes, service requests, schedules, evidence, and renewals move through different people and systems. We build the AI workflows that keep that work moving without replacing the tools your teams already depend on.
Where the hours go.
Slow survey-to-quote handoffs
Engineer notes, photos, parts, exclusions, and customer requirements arrive in different formats. Estimators spend valuable time reconstructing the job before they can price it.
Service requests scattered across channels
Requests arrive through shared inboxes, portals, calls, and messages. Teams manually identify urgency, contract coverage, asset context, and the right next action.
Scheduling depends on manual coordination
Skills, location, availability, parts, access windows, and SLA commitments all affect the schedule, but the decision is often assembled across several screens and phone calls.
Job evidence arrives incomplete
Photos, worksheets, readings, certificates, and customer sign-off are frequently chased after the visit, delaying invoicing and weakening the audit trail.
Maintenance renewals surface too late
Contract dates, asset histories, service issues, and customer conversations sit in separate systems, so renewal risk becomes visible only when the agreement is close to expiry.
Operational reporting is assembled by hand
Managers spend hours combining job, engineer, SLA, financial, and customer data before they can see where delivery or margin needs attention.
Where AI plugs in.
Quote Drafting Assistant
Structures survey notes, extracts scope and parts, checks required information, and prepares a first draft in the company template for estimator approval.
Service Request Triage
Classifies incoming requests, checks asset and contract context, drafts the work order, and flags urgency or SLA risk for the coordinator.
Engineer Scheduling Intelligence
Brings skills, geography, access, priority, and availability together to recommend a workable schedule while dispatch remains in control.
Job Pack & Evidence Automation
Builds the engineer pack before the visit, then checks returned photos, readings, certificates, and signatures before the job moves forward.
Maintenance Renewal Workflow
Identifies contracts approaching expiry, assembles account and asset history, highlights service issues, and prepares a structured follow-up queue.
Operational Performance Intelligence
Creates a governed view of job progress, SLA exposure, repeat visits, quote conversion, utilisation, and evidence gaps without another manual spreadsheet cycle.
Proof, not promises.
Start with one high-friction workflow and prove it in live operations.
A strong first engagement maps one workflow—such as survey-to-quote or inbox-to-work-order—against real examples, establishes the baseline, connects the required data, and keeps every consequential decision with the responsible team member.
Built to be trusted with your data.
Review the deployment
Confirm hosting, model, integration, retention, and deletion requirements for the proposed workload.
Define the data boundary
Agree the permitted documents, systems, users, and output paths before a workflow is deployed.
Keep evidence inspectable
Design the workflow so source provenance and human review remain part of the operating process.