Two things per industry: the numbers peers have already put up, and the same math with your figures in it.
AML triage, contract review, call handling — the most labor-dense desks in finance. Minutes per case, false-positive rate, the cost of a miss: the metrics already exist. Easy baseline, clean ledger.
Inspection reports, ticket triage, process tuning — the routine desks of asset-heavy industries. Volume is high and unit prices are clear; the first workflow usually produces acceptable, auditable numbers within four weeks.
Visual QA, defect analysis, supplier negotiation. How much of the inspection workload AI takes on, and where the miss rate lands — one sentence each.
Support cover, store forecasting, operations patrol — a 400-person company absorbed seven times the support volume without hiring, and a regional credit union saved $4.4M a year on one hotline. The thicker the payroll, the easier the math.
Taking your business abroad? That's its own line: Global — MEA market entry →
2–4 weeks on site: your chosen workflow running on your own data, an acceptance baseline signed by both sides. The steps, the pricing model and "when not to choose us" are all on one page.
Per-call audit trail, key expiry and source-IP allowlists, per-org budgets and policy blocks — all running in production today. Private and isolated-network deployment we have not delivered yet; it is on the roadmap, so raise any hard requirement with us up front.
The ledger is always open. Every weekly number traces back to individual calls. Net benefit is measured against the baseline both sides signed.
After each acceptance you decide whether to continue. The system, your data and the golden set belong to you.
Start with repetitive tasks that have clear inputs, outputs and a measurable baseline. Support, quality checks, ticket triage and contract review are candidates, not a promise that every role can be automated.
Explore pilot assessment →Assess the current systems, data permissions and available interfaces before defining integration scope. A pilot determines the changes needed; a model demo alone does not prove integration readiness.
See delivery steps →Agree on quality, workload, human review and cost definitions first. Compare the original and AI workflows on the same tasks. Treat a demo as evidence to test, not as final acceptance.
Use the acceptance baseline →