We don’t sell AI strategy. We build the agents, wire them into your stack, and stay on the hook for the number they move. Live in 14 days — inside your infrastructure, with your keys.
Plugged into the stack you already run
Almost every brand we meet has an AI strategy. Very few have anything running in production. The distance between those two states is where the entire advantage sits — and it is an engineering distance, not a thinking one.
So we start where the work actually is: your ticket queue, your ad approvals, your Monday report. We instrument it, automate the 80% that is genuinely mechanical, and give your people back the part that needs a human.
We don't produce an AI roadmap. We ship working systems into production and hand you the repo.
Strategy, engineering, integration, training and operations sit in the same room. No handoff tax.
Each agent feeds the next. Support data trains retention. Retention data sharpens ads. The gap widens.
We run our own agency on the systems we sell. If it doesn't survive our operation, we don't ship it.
Where's my order?
WISMO · live tracking
Refund — wrong size
Policy check · Shopify
Subscription pause
Save offer · Recharge
25,000 tickets a month, by hand. Now handled by agents trained on your tone and your edge cases. You keep the exceptions. The rest runs.
Scanning
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No distorted logos. No wrong patterns. Agents trained on your brand and your offers — shipping the output you used to fix by hand at night.
Flows, follow-ups and segmentation across your existing stack (Klaviyo, Shopify). Nothing slips because one person didn't get to it.
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Data that lives in 8 places, in one owned view: Mission Control. You watch the operation run instead of reconstructing it afterwards.
Every engagement ends the same way: something is running that wasn’t before, and a number moved.
Agents that do the repeated work end to end — triage, resolution, QA, reconciliation — inside the tools your team already uses.
Research, enrichment, qualification and follow-up wired into your CRM so pipeline stops depending on who had time this week.
When nothing off-the-shelf fits: retrieval over your own corpus, fine-tuned classifiers, internal copilots, evaluation harnesses.
One warehouse, one definition of every metric, one dashboard leadership trusts. The foundation every agent reads from.
We redesign the workflow before we automate it. Most processes don't need an agent — they need deleting first.
Your people become the operators. Hands-on training on your own agents, your own data, your own edge cases.
No six-month discovery. No pilot that never leaves staging. A fixed, four-stage sequence we’ve run 60 times.
We sit in your tools for three days. Ticket volumes, approval loops, where the week actually goes. You get a ranked map of every automatable workflow with hours and euros attached — yours to keep whether or not you hire us.
Automation map + business case
We pick the top three by leverage, not by novelty, and write the spec: inputs, decision boundaries, escalation rules, what the agent must never do, and the metric it will be judged on.
Signed agent spec + eval set
We build inside your infrastructure — your cloud, your keys, your repo. Retrieval over your real data, evals before launch, a shadow run against live traffic before anything touches a customer.
Agent live in production
Agents drift when your business changes. We monitor accuracy, review escalations weekly, retrain against new edge cases, and report the number in the same format every month.
Monthly performance report
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Tickets auto-resolved
median, live deployments
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Days to first agent
signed spec → production
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Return on agent spend
hours + revenue recovered
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Agents in production
across 60 brands
Three engagements, anonymised at the client’s request. Numbers are measured, not modelled.
Triage, WISMO and returns agents took 71% of volume in the first six weeks. The team stopped hiring seasonally and moved two people onto retention.
The save agent diagnoses the real cancellation reason and offers the path finance approved. Retention flows rebuilt against cohort-specific lapse points.
Nine sources into one warehouse, one definition per metric, one dashboard. The anomaly agent found a broken checkout variant on day four.
We'd been quoted six months and a seven-figure number by a consultancy. AIMAGENTIC had the triage agent answering live tickets in eleven days, and it was better than our macro library on day one.
The part I didn't expect: the audit alone was worth the fee. They showed us two workflows we should just delete rather than automate. Nobody selling AI tells you that.
Everything runs in our AWS account under our keys. Our security team signed it off in a week, which has never happened with a vendor before.
Monday used to cost me six hours of pulling numbers. It now costs me the time it takes to read one page. That's my whole review of the engagement.
Fourteen days from signed spec to production for a first agent. Days 0–3 are the audit, days 4–7 the spec and eval set, days 8–14 the build, shadow run and launch. Complex retrieval or bespoke integrations can add a week — we tell you that before you sign, not after.
You do. Full ownership of the repository, the infrastructure, the prompts, the eval sets and the documentation. Everything runs in your cloud accounts under your API keys. If you end the engagement tomorrow, the agents keep running and your team can maintain them.
Whichever wins the eval for that specific task. We route per step — a cheap fast model for classification, a frontier model for anything customer-facing or judgement-heavy — and re-benchmark quarterly. You are never locked to a single provider, and switching costs you a config change rather than a rebuild.
Three things. Retrieval grounded in your own systems, so answers are drawn from live order and policy data rather than model memory. Hard decision boundaries, so the agent can only take actions on an allow-list. And a confidence threshold that hands off to a human with a written summary rather than guessing.
It replaces the part of their week that they hate. In every deployment we've run, headcount held and the work changed: support leads move onto retention and product feedback, marketers move from asset QA onto strategy. We'll tell you honestly during the audit if a role is genuinely at risk.
A fixed fee per agent, scoped after the audit, plus an optional monthly run-and-improve retainer. The audit itself is a flat €2,500 and is credited in full against the first build. No per-seat licence, no percentage of savings.
Everything runs inside your infrastructure and your data never trains a third-party model. We work under a DPA, apply data minimisation at the retrieval layer, log every agent action for audit, and can deploy fully within the EU. Our own operation is ISO 27001 aligned and SOC 2 Type II is in progress.
The spec names the metric and the threshold before we build. If a launched agent misses its threshold at the 30-day review, we fix it at our cost until it clears or we refund the build fee. That's why the audit exists — we only take work we're confident we can hit.
No think-pieces. Implementation detail from agents running in production right now.
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