Readiness assessment
We map your workflows, data and tools, then identify where agents will pay off first — and where they won’t.
You geta prioritised automation roadmap
Agentic AI consulting · the Netherlands
AI agents handle the busywork. Your people make the calls.
Agentic Express designs and builds intelligent agents that work inside your daily operations — reading inboxes, processing documents, preparing plans and reports — always under your team’s control.
Agent run · inbox triage
Running
“Can we move Thursday’s delivery to Friday morning?” — incoming customer email
-
Read & classify
Intent: reschedule delivery · order #2189
-
Check the systems
Order found · two open slots Friday
-
Draft the response
Reply written · planning update prepared
-
Human approval
Operations lead reviews and signs off
-
Done
Reply sent · planning updated · run logged
Agents take on work such as inbox triage, document extraction, reply drafting, order entry, delivery scheduling, demand forecasting, reporting, quote preparation, invoice checks and internal policy questions.
From first assessment to running systems.
Engagements are sized to the decision you need to make next — never an open-ended programme. Start small, see evidence, then choose.
Proof-of-concept pilot
A narrow agent built on one real workflow, with guardrails and success measures agreed up front.
You geta working pilot and a clear scale-or-stop call
Implementation & integration
Pilots that prove out grow into production systems, embedded in the tools your team already uses.
You getagents in production, with controls documented
Support & advisory
Monitoring, refinements and a standing line for new opportunities as your operation evolves.
You getsystems that keep improving after launch
Not a chatbot project. A workflow, redesigned.
Good agents don’t start with a model — they start with a recurring bottleneck, a clear owner and a measurable before-and-after.
-
Map the work
We sit with the people who do the job and trace one workflow end to end — inputs, decisions, exceptions, handoffs. Together we agree what an agent may do, what people approve, and what gets logged.
-
Build the agent
A working system on your real examples — not a slide deck. It runs behind approval gates from day one and is measured against the way the work is done today.
-
Embed & measure
We connect the agent to your daily tools, train the team, document the controls and track the results — so the decision to scale, refine or stop is made with evidence.
Where agents earn their keep.
The biggest gains hide in the everyday: full inboxes, paper-shaped data, planning puzzles and questions that interrupt your best people.
Triage requests before the queue grows
Classify incoming messages, extract what’s being asked, draft replies and route exceptions to the right person — before anyone opens the inbox.
Turn PDFs and forms into clean data
Read delivery notes, invoices, claims and contracts, then prepare structured, checkable data for review or straight-through processing.
Support scheduling and forecasting
Summarise constraints, surface conflicts, forecast demand and propose next-best actions — so planners decide faster, with better context.
Answer from your own procedures
Internal assistants that answer questions from your policies, SOPs and operational records — with the source shown, every time.
Automation should make work calmer, not riskier.
Approval gates
Nothing customer-facing or irreversible happens without sign-off where you want it. You set the line; the agent respects it.
Full audit trail
What the agent saw, what it did and why — logged and reviewable, so trust is built on records rather than promises.
Data boundaries
Your data serves your project only. Tooling, access and retention are agreed before anything is built — never patched in later.
Regulation-aware
Every design is made with the GDPR and the EU AI Act in view from day one, so what we build belongs in a European business.
Fair questions, straight answers.
The concerns that usually come up before a first conversation.
What makes this different from using ChatGPT?
ChatGPT is a general tool you have to drive yourself. We build agents for one specific workflow: connected to your data and systems, bound by rules you set, with review points where they matter. The agent does the work; your team steers.
Do we need perfect data before starting?
No. Most operations run on messy inboxes, PDFs and spreadsheets — that is exactly where agents help. The assessment maps what you have, and the first pilot is scoped to work with it safely.
Will our data be used to train public AI models?
No. Your data is used for your project only. Tooling choices, access and data boundaries are agreed before anything is built, and we favour configurations where your data is not used for model training.
How quickly can we see something working?
A scoped pilot typically shows a working agent on your own examples within a few weeks, depending on workflow complexity and data access. We deliberately keep the first build narrow so you can judge it quickly.
What does an engagement cost?
Every engagement is scoped and priced up front — no open-ended billing. Pilots are deliberately small, so the first investment is sized to answer one question: is this workflow worth automating? You decide what happens next with evidence in hand.
Do we need our own AI team to keep it running?
No. Every build is handed over with documentation and training so your team can own it. If you would rather not, a support retainer covers monitoring, improvements and new automation opportunities.
Bring one workflow. Leave with a sharper path.
Tell us where work piles up — an inbox, a stack of documents, the weekly planning, a report nobody enjoys making. We’ll tell you, honestly, whether an agent is the right answer and what a first step would look like.
- hello@agenticexpress.nl
- Based in
- Rotterdam, the Netherlands