Understands the case
Reads messages and documents, identifies intent, priority and missing information.
One process.
Real work performed by the system.
Within a few weeks, we design, build and launch one complete process in which an AI agent performs tasks, uses company tools and involves people only for decisions and exceptions.
Discuss this scopeDelivery4–8 weeks
Modelfixed implementation scope
OutcomeA live production process with a clearly defined outcome, autonomy boundary and accountability model.
The operating problem
Automation currently stops between systems.
The Sprint is for a process the business understands but still operates manually because it requires interpretation, tool switching and exception handling.
- 01
People re-key data and repeat the same decisions across multiple systems.
- 02
Simple integrations do not understand the context of a message, document or case.
- 03
The process works because of knowledge held by a few people rather than explicit rules.
- 04
Growing volume requires more people instead of more system capacity.
How the system works
The agent does not merely suggest. It carries the case to an outcome.
We combine content understanding, business rules and tool access in one controlled workflow.
Collects context
Retrieves data from CRM, ERP, commerce, inbox, spreadsheets and other business systems.
Takes action
Updates records, prepares responses, creates tasks and initiates the next process steps.
Handles exceptions
Recognises risk and gives a person the complete context with a recommended decision.
Creates an audit trail
Every decision, action and approval is visible, measurable and auditable.
What you receive
A complete capability.
Not a loose prototype.
Every delivery combines process logic, working technology and the control required for people to trust it.
Production workflow
A complete route from incoming case to outcome, running on real examples.
Agent and integrations
Tools, rules, data sources and secure operations across company systems.
Control interface
Case queue, exceptions, approvals, status and action history in one place.
Metrics and documentation
Time, quality and autonomy measurement with a guide for further development.
Delivery path
From operating reality
to a live process.
Close the scope
Select one process outcome, representative cases, systems and success measures.
Design the operation
Define logic, agent role, integrations, approvals and exception handling.
Build and test
Implement iteratively using real data and edge cases.
Launch with control
Go live with monitoring, measure the result and stabilise how the team works with the agent.
Qualification
Is this the right
scope for you?
A clear fit protects time, budget and trust on both sides. We will say directly when another starting point is more responsible.
A strong fit when
- The process has an owner and repeatable volume.
- A concrete outcome and quality measure can be defined.
- Examples, data and required system access are available.
- The company wants a live implementation rather than a demonstration.
Choose another path when
- The right process is not yet known — start with Process Zero.
- The challenge spans an entire operation and multiple roles — use an AI Operations System.
- There is no process owner or decision capacity on the client side.
02 / AI Automation Sprint
Choose one process and take it into production.
In the first conversation, we will check whether the scope is right for a Sprint and what data is needed for a responsible estimate.
Next step
Let's start with one
process that hurts today.
In our first conversation, we will identify the area with the greatest potential and test whether agentic automation makes business sense.
Book a process conversation