Starts from natural language
The client does not need technical diagrams or complex documentation before the session.
AI Process Discovery
AI Readiness Assessment / Process Intelligence
Understand where to apply AI before implementing it: we turn your process description into an AS-IS map that reveals bottlenecks, manual work and operational priorities.
In a guided session, AI Process Discovery simulates queues, resources and backlog, generates a Human-in-the-Loop TO-BE scenario and closes with three realistic AI priorities for your SME.
SMEs do not struggle with AI because they lack tools. They struggle because real processes are informal, poorly measured and hard to translate into priorities.
Many operational flows live across email, phone calls, spreadsheets, partial ERPs and tacit knowledge held by key people. Before automating, the company needs to see how work really happens.
AI Process Discovery starts from natural language, requires minimal setup and produces a concrete basis for investment decisions: map, bottlenecks, future scenario and implementation next step.
PROBLEMS
The problem it solves
When the process is unclear, every AI initiative risks starting from the wrong point.
Processes described verbally, undocumented and dependent on tacit knowledge.
Exceptions, manual steps and hidden bottlenecks that are hard to measure.
Disconnected tools across email, spreadsheets, ERPs, phone calls and portals.
AI investments decided without knowing where operational impact will be highest.
PROCESS
How it works
A process-first session that turns operational chaos into map, evidence and decision.
Guided intake
Interview and natural-language process description, including actors, steps, exceptions, volumes and estimated times.
AS-IS map
Generation of a readable, validatable map shared between management and operations.
Operational simulation
Lightweight analysis of queues, WIP, backlog, resources and saturation to reveal where the flow slows down.
AI opportunities
Identification of automations, assistants, orchestrations and human checkpoints connected to real bottlenecks.
TO-BE scenario
Process redesign with AI assist, parallel flows and Human-in-the-Loop governance.
Commercial decision
Close with three implementation priorities, potential value and a recommended next step.
DIFFERENTIATORS
Why choose AI Process Discovery
Works on informal processes
It makes visible flows that currently live across people, disconnected tools and recurring exceptions.
Simulates before implementation
It highlights bottlenecks, queues, manual load and dependencies before selecting technology.
Connects AI to real constraints
Every AI opportunity comes from an operational friction, not from abstract recommendations.
Keeps human governance
AI prepares, simulates and proposes; people validate, decide and govern critical steps.
Opens a concrete pilot
The output becomes the basis for an assessment, pilot project or measurable implementation proposal.
USE CASES
High-potential use cases
The first ideal vertical is logistics, but the method works across repetitive operational processes with frequent exceptions.
Orders and customer requestsPickup and delivery planningDDT, POD and document checksExceptions, returns and non-conformitiesWarehouse, carriers and administrationOrder, invoice and system dataTickets, emails and manual requestsActivity reports and dashboards
Orders and customer requests
Pickup and delivery planning
DDT, POD and document checks
Exceptions, returns and non-conformities
Warehouse, carriers and administration
Order, invoice and system data
Tickets, emails and manual requests
Activity reports and dashboards
OUTPUTS
Outputs for decision makers
Validated AS-IS map
Priority bottlenecks
AI opportunities ordered by impact and feasibility
Human-in-the-Loop TO-BE scenario
Three implementation priorities
Recommended next step