01 Featured
Customer-support AI agents
Reduce support load and speed up response times. Our agents resolve up to 40% of routine enquiries on their own and escalate the harder cases to your team with full context.
Most-shipped piece
Service · AI Solutions
Your data already has the answers.
We make it talk.
Your customer data, orders and documentation are already sitting in your stack. We turn them into live AI workflows — pilots that grow into operations, not the other way around.
What we deliver
Six example AI agents.
Far from the only ones.
No theoretical slides, no empty promises. These are real, live solutions we operate and develop for Bauhof and Aatrium today.
02
Demand-forecasting agents
Eliminate stockouts and optimise working capital. AI-driven demand forecasting at SKU level lets you anticipate stock running out and automate replenishment planning.
03
Autonomous content generation
Scale your assortment without a content bottleneck. AI agents generate technically accurate product copy and metadata, strictly following your brand voice and quality standards.
04
Strategic decision tooling
Make data-driven business decisions in real time. An AI copilot analyses sales data and market conditions, offering precise recommendations for pricing and campaign planning — replacing gut feel with facts.
05
Omnichannel integration
A single layer of intelligence across all your channels. Connect AI agents to web chat, email, Slack or Teams, ensuring consistent, high-quality information at every touchpoint.
06
Observability & security
Ensure full control and regulatory compliance. Every AI-agent action and conversation is logged, analysed and auditable, giving you confidence that data is handled securely.
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
Evaluation, tuning & validation
We measure answer quality, reliability and business impact, then tune the system until it clears the agreed production threshold.
- 04 Week 6 — ∞
Operations & monitoring
We move the agent into day-to-day operation with telemetry, rate limiting, audit trails and ongoing performance monitoring.
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 a large share of inbound questions instantly — 24/7 coverage in your tone of voice, with exceptions escalated to a human with full context.
- 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. A standard, production-grade stack keeps your agents portable, observable and supportable as models, teams and traffic change.
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
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. The result came from a scoped use case, a controlled rollout, retrieval grounded on a real knowledge base, and continuous monitoring after launch.
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 typical pilot takes four weeks: data audit, model selection, evaluation and deployment. The goal is not a demo but a measurable operational outcome.
A 30-minute call · No deck · A clear next step
Ready for AI
that ships?
Book a call
or just hit the phone +372 656 0066