Automation suitability can be judged only from observed workflow records, volumes, controls, and exceptions, with disagreements left visible until the process owner accepts the map and next gate.

We examine how work moves through your team, including its decisions, volumes, controls, and exceptions. We then identify which opportunities merit further automation work and which do not.

Every row of the evidence-linked opportunity backlog tells your process owner to advance, gather more discovery, or stop, and names whoever owns that next decision.

Illustration of AI Process Discovery & Automation Assessment: a team redesigning a workflow around automated and human steps

Some of the 500+ brands we've worked with

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  • Amazon
  • Vitra
  • CHIP Online
  • Canbebe
  • Mudo
  • Karel

The assessment moves from observable workflow evidence to an owned decision about what should happen next.

  1. Assemble process evidence

    We collect representative workflow records, examples, current constraints, volumes, controls, and known exceptions from the people who run the work.

    AI assist
    Submitted workflow records are grouped by the model into likely steps so coverage gaps are easier to spot.
    Human gate
    Is the evidence representative enough to map the process? The process owner confirms which records count as representative.
  2. Map decisions and exceptions

    We trace the steps, handoffs, authority, dependencies, and failure paths, keeping disagreements and missing evidence visible.

    AI assist
    From the collected records, the model drafts a first process map for the team to correct.
    Human gate
    Does the map reflect how work happens, not only how it was designed? Domain experts confirm where the draft map differs from real practice.
  3. Assess automation suitability

    We compare opportunities against evidence, control needs, dependencies, and likely exception handling rather than scoring effort in isolation.

    AI assist
    The model scores candidate opportunities against the evidence and control criteria for a first ranking.
    Human gate
    Which opportunities have enough evidence to move forward? The process owner decides which ranked opportunities deserve a closer look.
  4. Record the next gates

    We review the backlog with your owner and document what advances, what needs more evidence, and who owns each next decision.

    AI assist
    The backlog write-up is drafted by the model and linked to the evidence behind each item.
    Human gate
    Does every selected item have an owner and next review point? The process owner assigns the next-gate owner for every advancing item.

The artifact set keeps the recommendation tied to the workflow evidence behind it.

  • Roadmap

    Observed workflow and automation opportunity backlog

    A map of the observed workflow alongside the opportunities, constraints, exceptions, and questions found during discovery.

  • Risk register

    Process sources, dependencies, and evidence-gap inventory

    The source material, open assumptions, system and team dependencies, and evidence gaps that shape the assessment.

  • Report

    Candidate opportunity findings and critical exceptions

    The comparison of candidate opportunities, including representative cases, critical exceptions, and reasons not to advance an item.

  • Decision record

    Accepted backlog paths, owners, and next-gate brief

    The accepted backlog decisions, conditions, owners, and next review points for opportunities that continue.

Teams often have automation ideas long before anyone has mapped how the work really moves, and that gap is where this assessment starts.

A good fit when

  • Different teams describe the same workflow differently, so nobody can tell which handoff or exception path reflects the process in use.
  • Workflow records exist, but the examples, volumes, controls, and people who know the work have never been brought into one process view.
  • A build is under discussion, yet the process owner lacks a prioritized opportunity backlog tied to operating evidence.
  • The workflow crosses decisions, handoffs, controls, and exceptions, but no current map shows where volume or responsibility actually changes.
  • Candidate automations sound plausible, yet their dependencies, assumptions, and suitability are not tied to representative evidence.
  • Opportunities have been ranked by effort, but failure cases and acceptance conditions have not been reviewed before the funding decision.
  • Selected opportunities have a next step, yet no handoff record names the owner, next gate, or evidence still required.

Better handled as other work when

  • You want a workshop account treated as the operating process. We use the discussion to locate the work, while representative records have to support the map.
  • You expect every mapped task to become an automation. The assessment can pause or reject an item when evidence, controls, or exception handling do not support it.
  • You need the selected automation built or operated now. This assessment prepares the backlog and next gates, while delivery requires a separate phase.

If one of these is closer to your situation, start here instead: View the parent service

  • Anthropic

    maps unstructured process documents and notes into decision steps

  • Airtable

    maintains the process inventory, suitability scores, and gate decisions

  • n8n

    prototypes candidate automation boundaries to test suitability quickly

  • Jupyter

    analyzes volume, exception rates, handling times, and value ranges

Point us to one process, the records you have, and the people who know its exceptions. We will turn that evidence into an actionable backlog.
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We look for workflow records, representative examples, current constraints, baseline evidence, volumes, controls, exceptions, accountable owners, and the person who will accept the assessment. Missing or contradictory evidence stays visible in the register.