Questions buyers ask every week

AI workflow automation uses AI to complete steps in a business process that previously needed a person — reading a document, deciding how to classify it, and updating a system. Unlike a fixed script it handles messy inputs such as emails, PDFs, and free text, and escalates the cases it is not confident about instead of guessing.

RPA follows a fixed script and breaks when a screen, form, or file format changes. An AI agent works from the goal, reads unstructured input, chooses which tool or API to call, and adapts to variation. RPA suits stable, high-volume clicking; agents suit judgement-heavy work. Many real processes use both, and we will say which fits.

Pricing depends on scope, so we quote after the audit. The AI audit is a fixed price and stands alone. A pilot covering one process is quoted as a fixed price once scope is agreed, and ongoing operations run on a monthly retainer. You always have a firm written number before work starts.

The audit takes about two weeks. A first pilot goes live in four to eight weeks depending on how many systems it touches and how clean the data is. Scaling to further processes is faster because the integrations and access controls already exist. None of this requires a year-long programme.

Your data is processed through enterprise API endpoints with training on your inputs disabled, contracted in writing. Agents hold least-privilege, revocable access to only the systems they need, every action is logged, and changes to money or records require human approval. We hold no security certification and do not claim one.

We agree the metrics before the pilot starts — usually hours saved per week, cycle time, error or rework rate, and cost per transaction. The current baseline is measured during the audit and the same measurement is repeated after go-live. The comparison is against your own numbers, never an industry average.

In most cases, yes. We integrate through documented APIs where they exist and through database views, scheduled exports, or email intake where they do not. SAP, Oracle, Dynamics, Tally, Zoho, Salesforce, HubSpot, Freshdesk, Zendesk and similar systems are all workable. The audit confirms exactly how before you commit to a pilot.

Every automation has a confidence threshold and an exception queue. Below the threshold the work is routed to a person rather than completed. Errors that reach production are added to the evaluation set so the same mistake is caught by a test before the next release, and every automation has a documented rollback.

You need usable data, not perfect data. The audit includes a readiness check that tells you which processes are ready now and which need a data fix first, with the effort estimated. We would rather delay one process than build an automation on a source that cannot be trusted.

We select per task and stay portable. Model choice is an implementation detail behind our own interface, so a change of provider does not become a rebuild. Selection is driven by accuracy on your evaluation set, latency, data residency requirements, and cost per transaction.

The engagements we run remove repetitive keying and searching, not headcount decisions, which are yours. In practice the teams we work with move the recovered hours to exceptions, quality, and customer contact. We say this plainly because it is the first question staff ask, and the answer affects adoption.

You work with the engineers who build the system rather than a sales team followed by a rotating bench. Scope stays fixed, decisions happen in a day, and the pilot is small enough that stopping costs little. For a first agentic system, speed to a measured result matters more than the size of the vendor.