01 · Services
AI implementation
Workflows, agents, retrieval, evals — built into the tools your team already uses.
Flows · in plain English
One operating system, many flows.
Every business has the same boring loops — invoices, replies, offers, follow-ups. We turn each one into a reliable flow that runs without you. Pick a flow to see it move.
- 01
Manual invoice
You used to type
- 02
Bookkeeping
Auto-coded
- 03
Email paper trail
Sent to file
- 04
Accountant approval
One-click sign-off
What you get
Deliverables, not decks.
- Use-case discovery & ROI scoring
- Custom GPT / Claude / agent builds
- RAG pipelines on your data
- Eval harness so quality doesn't drift
Same day, different shape
Two people, same backlog — one chips, the other ships.
Same fifty-item inbox at 9am. By 5pm, one of them is still on email. The other walked the dog at 11.
Manual workflow
At desk · 9:00 → 17:00
- Triage 38 unread emails
- Approve 12 invoices
- Draft 3 client proposals
- Update CRM after calls
- Review pull requests
- Compose follow-ups
- Schedule next-week meetings
- File expense reports
- Reply to Slack threads
- Compile Friday report
2 of 10 done · 8 spilled into tomorrow
With Mediseo · 1000× faster
In the discovery call
- Triage 38 unread emails
- Approve 12 invoices
- Draft 3 client proposals
- Update CRM after calls
- Review pull requests
- Compose follow-ups
- Schedule next-week meetings
- File expense reports
- Reply to Slack threads
- Compile Friday report
10 of 10 · before second coffee
How it works
From use case to production in 6 weeks.
We don’t do "AI strategy" decks. We pick one workflow, ship it, evaluate it, then pick the next one. Most engagements have something live in week 4.
- 01
Use-case scoring
We sit with your team and score candidate workflows on impact, complexity, and risk. You leave with a numbered list.
- 02
Build & wire
Agents, RAG, custom GPTs, plus the integration into your existing stack. Slack, HubSpot, Zendesk — wherever the work happens.
- 03
Evals & tuning
A persistent eval harness so quality doesn’t drift. Weekly review against the baseline, with a written analyst note.
- 04
Roll & repeat
Workflow #2 starts when #1 is in production and stable. Compounding, not sprawling.
What we ship
Workflows you can have running this quarter.
Concrete examples of what we build. Most are live in 4–6 weeks. We pick the highest-leverage one for you and ship that first.
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Customer-support copilot — in production
Real screenshot of this workflow running. Annotate the magic moment with one warm-orange hand-drawn arrow.
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Customer-support copilot
Reads your knowledge base, your past tickets, and your tone. Drafts replies your team approves with one click. Cuts time-to-first-response by 60–80%.
Claude · RAG · Zendesk / FrontImage placeholder
Sales-research agent — in production
Real screenshot of this workflow running. Annotate the magic moment with one warm-orange hand-drawn arrow.
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Sales-research agent
Pre-call briefs in 30 seconds: company news, signals, who to mention. Plugs into your CRM so reps walk in informed, not blind.
Claude · web search · HubSpotImage placeholder
Document QA · contracts & SOPs — in production
Real screenshot of this workflow running. Annotate the magic moment with one warm-orange hand-drawn arrow.
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Document QA · contracts & SOPs
Ask your contracts and runbooks in plain English. Cite-back so legal trusts the answer. Self-serve where lawyers used to bottleneck.
Claude · vector store · permissionsImage placeholder
Inbox triage & smart reply — in production
Real screenshot of this workflow running. Annotate the magic moment with one warm-orange hand-drawn arrow.
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Inbox triage & smart reply
Sorts incoming emails by intent, drafts replies for the boring 70%, escalates the rest with full context. Two hours back per person, per day.
Gmail / Outlook · n8n · ClaudeImage placeholder
Creative + content engine — in production
Real screenshot of this workflow running. Annotate the magic moment with one warm-orange hand-drawn arrow.
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Creative + content engine
Long-form drafts, ad variants, lifecycle email — written in your voice from your past wins. Humans edit, never start from blank.
Claude · brand profile · CMSImage placeholder
Custom internal copilot — in production
Real screenshot of this workflow running. Annotate the magic moment with one warm-orange hand-drawn arrow.
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Custom internal copilot
Your data, your tools, one chat. Pulls the report, books the meeting, files the JIRA. The thing every department asks for and nobody has time to build.
Claude · MCP tools · SSO
Featured outcome
“It’s the first piece of AI that didn’t make us spend more time training it than working.”
— Head of Customer Experience, TM Rental
Common questions
The objections we usually meet — and how we answer them.
Will the AI be accurate enough for our work?
We don’t deploy and pray. Every workflow ships with a persistent eval harness — a fixed test set we run weekly to catch regressions. If quality drifts, we know before you do. For high-stakes outputs (legal, financial, medical) we add a human-in-the-loop gate by default.
How is our data handled?
Your data stays in your stack unless you opt otherwise. We use enterprise tiers (Claude on Anthropic, Azure OpenAI, AWS Bedrock) with zero-retention contracts. Sensitive workflows can run entirely on infrastructure you control. We sign DPAs.
What if it doesn’t stick after you leave?
Most engagements have something live in week 4 and a second workflow by week 10. The code is yours, the docs are yours, the eval set is yours. We can keep running it on a part-time retainer, or train your team and hand off — your call.
How is this different from "AI strategy" consulting?
We don’t do strategy decks. The first deliverable is a working workflow in production. We pick one high-leverage use case, build it, evaluate it, then pick the next one — instead of mapping a 24-month roadmap that goes stale in 8.
What does it cost?
AI implementation engagements start at €4,500 for a single workflow shipped end-to-end. Larger programmes (3+ workflows, custom apps, ongoing tuning) are scoped against expected savings or revenue, with a fixed delivery price.
Which models do you use?
Whatever fits the job. Claude for reasoning and writing, GPT for breadth, Llama / Qwen for cost-sensitive workloads, custom fine-tunes when the data warrants it. Model-agnostic by design — if a better one ships, you switch in a config change, not a rebuild.
Leave with a number, not a deck.
Thirty-minute call. We listen, we name the loops you'd hand off first, we name a price. No deck, no roadshow, no twelve-month programme — just the next concrete thing to ship.