01
The pilot that never shipped
You tried building AI yourself or with a freelancer. It demoed well, then quietly died.
Ship AI agents your team actually uses.
Scoped, built, and live in weeks. You own the code.
Our clients
The AI challenge
Six places teams quietly lose time and money
Most teams have at least one. The problem is rarely that AI is hard. It's that the right AI isn't working for you yet.
02
Hours lost to copy-paste
Your team burns 25+ hours a week moving the same data between systems by hand.
03
Subscriptions, no results
You're paying for AI tools nobody can prove are actually doing anything.
04
Paying too much for software
A bloated software bill is up for renewal, and a custom agent would cost a fraction.
Who we are
Custom AI agents for your team. First one live in 2 weeks. Owned by your team.
It starts with a 2-hour session on your biggest operational win.
2 Weeks
concept → live
Owned by your team
Full source + docs handed over.
The proof
AI isn't magic, it's engineering. The numbers below are what that buys you.
01/ 03
95%
of AI pilots never reach production
We're built to be the 5%. Every agent we build runs in production.
02/ 03
2 wks
First call to live
From scoping your biggest win to a live agent you own, in about two weeks.
03/ 03
100%
Owned by your team
Full source, docs, and a trained team at handover. No lock-in, no black box.
Trusted by teams shipping AI in production
What we do
Our services
Five ways to work with us, matched to your ambition and budget. Any industry, any region.
001/ 005
AI Agents
Custom agents that take real work off your team. Scoped, built, shipped to production. You own the result.
What you get
Let's build agents - Development
- Automations
- Efficiency
wn-cli · agent
▋002/ 005
AI Automations
We connect your tools and remove the copy-paste tax, automating the workflows that quietly eat hours every week.
What you get
Let's automate - Integrations
- Workflows
- Throughput
Pipeline · Intake → Close
IngestEnrichClassifyRouteAct
128 items / min · 94% auto-resolved
6% escalated · avg 0.6s per step
Connected · Hubspot · Snowflake · Slack
003/ 005
AI Development
Bespoke AI software built like real engineering, tested, maintainable, and made to last beyond the demo.
What you get
Let's talk - Architecture
- Testing
- Delivery
agent.py · productionEdit
# ops agent, graph w/ handoff
from wn.agents import Graph, Memory
g = Graph(state=OpsState, llm="sonnet")
g.add("intake", ingest, tools=[Zendesk])
g.add("retrieve", lookup, memory=Memory.vector)
g.add("reason", classify, retries=2)
g.add("handoff", page_human, when=conf < 0.82)
await g.run(on="new_ticket")004/ 005
AI Strategy & Consulting
A clear, prioritised plan for where AI pays off first, grounded in your operations and your numbers.
What you get
Get a roadmap - Roadmap
- Prioritisation
- ROI
Roadmap · Q3 → Q14 milestones
Discovery workshop · ops + data leadsWk 01
3 pilot agents · scoped + estimatedWk 03
Agent #1 live · ticket triageWk 06
Measurement · EBITDA impact reviewWk 12
005/ 005
Data Strategy
Data that's structured, governed, and compliant by design, so every agent has solid ground to stand on.
What you get
Talk strategy - Foundations
- Governance
- Coverage
Knowledge base · Coverage+12% / mo
Product docs92%
Sales conversations76%
Support tickets88%
Ops runbooks54%
Contracts & legal31%
(6) Cases
Real agents, in production.
A look at the agents and automations we have shipped, and the numbers they moved.
435
qualified leads from one run, pre-scored against ICP
€1/day
to run the full engine, continuously
What clients say
What differentiates them is not only their technical expertise, but their deep understanding of AI governance and its pitfalls. This is not a one-off project, but a long-term partnership built on trust, professionalism, and measurable outcomes.
Stefano Teatini
General Manager, CIRFOOD
FAQ
Questions, answered.
What is an AI agent?
An AI agent is software that does not just answer, it acts. It reads a request, looks things up in your systems, and completes the task end to end, like booking the appointment or resolving the support ticket. Where a chatbot stops at a reply, an agent does the actual work inside your existing tools.
How is an AI agent different from a chatbot?
A chatbot matches questions to canned answers and hands everything else to a human. An AI agent reads the real request, takes action in your CRM, ERP or helpdesk, and resolves it. The difference is outcomes: a chatbot deflects, an agent completes the work and only escalates the genuinely complex cases.
What does an AI agency actually do?
We scope your highest-ROI use case, build a production-grade AI agent or automation around your real tools and data, and hand it over so your team owns it. The focus is shipping something live and measurable, not slide decks or endless pilots.
How long does it take to go live?
Most agents and automations are live in 2–4 weeks, and larger custom builds run 8–16 weeks. We ship a working first solution quickly and then iterate with you, rather than disappearing for a quarter and hoping it lands.
Do we own what you build?
Yes, entirely. You receive the full source code, documentation and access, with no lock-in and no licensing strings. Your own engineers or another vendor can run and extend everything. We build it to be handed over cleanly, not to keep you dependent on us.
Is it secure and GDPR-compliant?
Yes. We build on EU-friendly infrastructure, your data is never used to train foundation models, and a Data Processing Agreement is available. Access is least-privilege with logging, alerting and a human in the loop wherever a mistake would matter.
Get in touch
Talk to our AI experts
We turn your AI questions into something live and measurable.
- A clear roadmap from AI question to working solution
- Compliant, production-ready agents built by senior experts
- A partner who stays after launch, not just for the pitch
Insights
Read all insights→Latest trends and insights from our team.
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Multi-Agent Orchestration: When It Helps and When It's Hype
Sakana's Fugu reignited the multi-agent orchestration debate. Here is what it actually solves, when it earns its complexity, and when a single model wins.
Read→Jun 1, 2026Claude Opus 4.8: What Actually Changed and Why It Matters for Your Business
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Read→Insights