01 · Map
Process map
We document the work step by step: inputs, decisions, exceptions, durations.
Every decision point recorded
AI process transformation
We turn manual processes into systems that run themselves.
We embed in your most complex unit, learn the process exactly as it runs, and take a purpose-built agent architecture into production.
50+ projects40% average efficiency99.2% process accuracy3+ years
01 · Today
Scattered work
A process moving between dozens of files, messages and people. Nobody can see the whole of it.
02 · Agent layer
One decision engine
Rules, data and exceptions come together in one place. The agent decides and leaves its reasoning behind.
03 · Live
Autonomous flow
Work moves along a traceable, repeatable line. People only step in for exceptions.
System layers
Four layers we build in every transformation.
The same skeleton, rebuilt around each process. The goal is never a demo: it is an auditable system running in production.
02 · Agent
Decisions and tool use
The agent runs the process end to end and hands over to a person when needed.
Human approval at defined thresholds
03 · Bridge
Integration
ERP, WMS, accounting, e-mail, IoT. The agent sits on top of the systems you already run.
Runs on your existing stack
04 · Proof
Measurement and audit
Accuracy, duration, cost and exception rates are measured continuously.
End-to-end audit trail
Operations we work in
- Logistics
- Warehouse & WMS
- Manufacturing
- Retail
- Supply chain
01 — Where you are
If the process lives in someone's head, there is no system.
Most automation attempts stall in the pilot: the process was never written down, and the exceptions were never recorded anywhere.
Time goes into coordination
Spreadsheets, calls, mail, messages. Less of the work itself, more of keeping the work alive.
The cost of errors is invisible
A miscount, a skipped approval, a lost record. The bill arrives later, somewhere else.
The process depends on a person
When the key person leaves, work stops. Every new hire learns the process from zero.
02 — Method
From the floor to production, in four steps.
We do not hand over a report and walk away. We stay at the same table until it runs live and your team owns it.
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01
We go to the floor
We watch the real work inside the unit. Every decision point, exception and workaround gets recorded.
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02
We model the process
Inputs, rules, approvals, outputs. It becomes clear which step runs autonomously and which stays with a person.
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03
We build the agent
An agent architecture that connects to your systems, logs its reasoning, and works inside defined limits.
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04
We hand it over
Metrics, monitoring, rollback scenarios and documentation. The process now depends on the system.
03 — Cases
Measured outcomes, from units that ran manually.
Each one started with a spreadsheet and one person in charge.
35% lower inventory cost, 99.2% accuracy
A system that learns demand forecasting and the ordering decision replaced manual stock planning.
- Before
- Weekly spreadsheet plan, person-dependent forecast
- After
- Daily autonomous order proposal, approved exceptions
Inventory optimisation Python · TensorFlow · PostgreSQL 6 months
Digital warehouse across 50+ locations
Warehouse operations running on paper and word of mouth moved to real-time tracking and automated workflows.
40% efficiency Node.js · React Native · IoT
25% fuel savings
The route decision a planner rebuilt by hand every morning moved to the agent.
1000+ routes Python · Maps API
90% of unplanned downtime prevented
A system reading failure signals from IoT data catches the stop before it happens.
200+ machines Azure IoT
10M+ data points, instant insight
One continuously flowing panel instead of weekly manual reporting.
Supply chain Kafka · D3.js
40%
average efficiency gain
99.2%
process accuracy
50+
projects delivered
95%
client satisfaction
04 — Trust
Autonomous, not unsupervised.
Handing an operation to a system takes trust. That is why every agent runs with defined limits, a full record and a way back.
Human approval layer
Amount, risk and exception thresholds fall to a person exactly where you set them.
Audit trail
Which data, which rule, what time. Every decision can be read back afterwards.
Rollback scenario
Every step can return to the manual flow. If the system goes down, the operation does not.
Deployment on your side
Cloud, your own servers or hybrid. Data stays wherever it has to stay.
Day zero
Which process should we start with?
Pick one unit. We map the process together, mark the part that can run autonomously, and put a number on the expected impact.