01 Featured
Tier-1 support agent
Deflects 30 — 40% of inbound tickets. Escalates the hard ones with context.
Most-shipped piece
Service · AI Solutions
Your data already has the answers.
We make it talk.
Years of customer data, orders, and documentation sitting idle. We turn it into real-time decisions — who is about to churn, what to recommend, which question to answer — automatically. Pilots that turn into operations, not the other way around.
What we deliver
Six agents for support, forecasting, and content.
Right when you need them.
No theoretical slides, no empty promises. These are real, live solutions we operate and develop for Bauhof and Aatrium today.
02
Forecasting agent
Predict next-month demand by SKU. Replenishment alerts before stockouts.
03
Content agent
Product copy, category descriptions, meta. Brand voice locked in, draft-only by default.
04
Decision tooling
Internal copilot for merch teams. Answer "should we discount?" with data, not vibes.
05
Voice / chat surfaces
Connect agents to web chat, Slack, email, Teams. One brain, many surfaces.
06
Observability
Every conversation logged, scored, and reviewable. Your compliance team will sleep at night.
How we work
4 stages. No surprises.
A single statement of work, weekly demos, and the same engineers in every meeting. Re-scopes happen in writing.
- 01 Week 1
Use-case analysis & metrics
We pick the critical business process with the highest automation potential. We set the baseline and agree on concrete success metrics (KPIs).
- 02 Week 2 — 4
Pilot build
We build a working AI agent against an isolated copy of live data. Initial testing runs with internal users in a controlled environment.
- 03 Week 4 — 6
Tuning & validation
Iterative optimisation based on feedback. We push the agent's accuracy and reliability past the agreed threshold, ensuring a stable process.
- 04 Week 6 — ∞
Operations & monitoring
Full system management and proactive monitoring on our side. You watch results through real-time telemetry; we keep the agent running flawlessly.
Who this is for
Three perspectives.
Same fixed-deadline contract.
Risk-reversal in plain English — what your board, your marketers, and your engineers each get out of the same project.
01
For business leaders
Model-agnostic systems on top-tier foundation models. Cost-to-performance ratio held in writing.
- Pilot to production in four weeks
- Vendor independence (OpenAI · Claude · Llama 3)
- Measurable lift, not demo-stage promises
02
For support & sales
Answer 80 % of inbound questions instantly. Zero extra headcount, 24 / 7 coverage, your tone of voice.
- Semantic search over your knowledge base
- Citations, not hallucinations
- Escalates to a human with full context
03
For IT & security
Your data stays yours. SOC 2 baseline, private model option, audit trails on every call.
- Never enters vendor training pipelines
- PII redaction at the audit step
- Containerised endpoints, rate-limited, cached
Our toolchain
Boring tech.
On purpose.
Boring infrastructure with sharp AI on top. The infrastructure is what makes the AI useful.
01 Tooling
Claude 4
02 Tooling
GPT-5
03 Tooling
Gemini 3
04 AI
Letta
05 Tooling
Pgvector
06 Tooling
BM25
07 Tooling
Apache AGE
08 Workflow
Temporal
09 Tooling
Langfuse
10 Observability
Sentry
10 pieces · one runbook $ kubectl get pods — all Running
Plays nice with
The systems
you already run.
Integrates with your existing stack — Magento, your CMS, payments, ERP, analytics. We connect what you already run, not replace it.
OpenAI
Claude
Llama 3
Mistral
Pgvector
Pinecone
Letta
Langfuse
Case spotlight
Zaproo internal · 2024
A four-week pilot deflecting 38% of inbound tickets.
A Claude-based agent answering tier-1 product questions on the back of our knowledge base.
Tickets deflected
38%
Time to live
4 wks
Common questions
The four answers
we send back most.
If yours is here, you can skip the form. If not, the brief on /contact takes two minutes.
How do you keep our data out of vendor training?
We use OpenAI / Claude API tiers with training-opt-out by default. For data that cannot leave at all, we run Llama 3 or Mistral on a private endpoint inside your cloud — your customer data never crosses an external boundary.
Why model-agnostic instead of locked to OpenAI?
Models change every six months. Locking in costs you the upgrade. We benchmark Claude / GPT / Llama on your data, pick the best cost-to-performance ratio, and re-evaluate quarterly.
How is this different from a chatbot demo?
Most AI projects stall at the demo stage. We engineer the semantic search pipeline, the eval harness, the regression tests, and the deployment story — the work that turns a demo into something on call at 02:00.
How fast does a pilot take?
A four-week pilot. Week 1 data audit, week 2 model selection, week 3 evaluation, week 4 deployment with rate-limiting and caching. You get a measurable outcome, not a slide deck.
A 30-minute call · No deck · No follow-ups
Ready for AI
that ships?
Book a call
or just hit the phone +372 656 0066