AI engineering lab · Riga, Latvia

AI that works in production, not just in the demo.

We design and build AI agents, RAG systems and the software around them — from first prototype to a product your team can run and trust.

Tell us about your project What we do
$ stlabs run support-agent
● retrievepolicies.pdf, faq.md
● reasonplan → 3 steps
● toolcrm.create_ticket ✓
● guardPII check ✓
● evalanswer grounded ✓
→ reply sent · ticket opened · logged
AI agentsRAG & dataMVPsTeam augmentation

What we do

AI engineering, end to end.

Models are the easy part. We build the retrieval, tools, guardrails, evaluation and plain software and evaluation that make them useful.

01

AI agents & automation

Agents that read, decide and act inside your systems — support, back office, sales ops — with a human in the loop where it matters.

02

RAG & your data

Search and assistantsAssistants grounded in your documents and databases, with answers that cite their sources and respectciting sources and respecting access rights.

03

MVPs & products

From idea to a live product: backend, web and mobile, cloud, mobile and CI/CD — built to grow beyond version one.

04

Audit & team augmentation

Architecture and AI-readiness reviews, and senior engineers who join your team to ship alongside it.ship alongside your team.

How we work

Small steps you can see.

  1. 1

    Discovery

    We map the process, the data and what success looks like. You get a short written plan and an honest estimate.

  2. 2

    Prototype

    A working slice on your real data, measured against agreed test cases — so we know it works before we scale it.

  3. 3

    Production

    Integrations, security, monitoring and CI/CD. Weekly demos, every change in your repository.

  4. 4

    Support & growth

    We keep improving quality and cost, or hand over to your team with documentationdocs and training.

Selected work

Built, shipped, running.

  • [INDUSTRY]

    [Case study title]

    [Problem, what we built, measurable outcome.]

  • [INDUSTRY]

    [Case study title]

    [Problem, what we built, measurable outcome.]

  • “[Client testimonial, one or two sentences.]”
    [Name], [Role], [Company]

Stack

Proven tools, picked per project.

We are model-agnostic and chooseModel-agnostic: we choose what fits your data, budget and compliance needs.

Models & AI

  • Claude
  • OpenAI
  • Open-source LLMs
  • MCP & tool use
  • pgvector
  • Evals

Engineering

  • .NET
  • Python
  • TypeScript
  • React
  • Next.js
  • PostgreSQL
  • AWS
  • Docker
  • OpenTelemetry

Questions we get

Is our data safe? Where does it go?

We design for GDPR from day one: EU hosting where required, no training on your data, access controls and audit logs. We sign a DPA before touching personal data.

How long does a first version take?

Discovery takes [X] weeks; a working prototype usually follows within [X] weeks. You get a concrete timeline after discovery.

How do you price projects?

[Fixed price for discovery and prototype, then monthly or time & materials — adjust to your model.]

Who owns the code?

You do. Everything lives in your repositories and cloud accounts from the first commit.

What if AI is not the right answer?

Then we will say so. Sometimes a rule, a form or a report solves the problem better — and we build that instead.

Got a process that should run itself?

Tell us what you are trying to do. We reply within one business day with questions or a first idea — no sales script.

Start a project