Services · How an engagement runs
One workflow at a time.
We help businesses decide what is worth building with AI, build it, and run it after launch. Every engagement starts with one workflow and a fixed-fee discovery week. If AI pays off there, we build it, deploy it against real users, and stay to run it.
What we build
Five things, one stack
AI Implementation
Production AI systems built end-to-end and operated after launch. Discovery, build, deploy, run, with shared accountability for the system working.
RAG & Document AI
Retrieval systems that cite their sources: hybrid search, reranking, refusal on weak context, and per-query cost tracing. No LangChain: code we own.
AI Agents
Agents with guardrails you can audit: typed tools over live systems, deterministic caps and kill switches, eval harnesses before production.
Regulated Industries
AI that survives an audit, proven in EASA-regulated aviation: page-level citations, audit-trailed review workflows, regulatory change monitoring.
Process Automation
Multi-step manual workflows handled end-to-end, with humans on exceptions. Connected systems, one click where there were ten.
The engagement
Discovery, build, deploy, run
Discovery ends in a written recommendation: build, do not build, or build something smaller. Most workflows we look at do not survive it, and that written no is the most useful thing we sell. Build is estimated line by line from discovery, fixed-price where the scope supports it.
Define
One week, fixed fee. Which workflows pay off and which do not, in writing, with a roadmap you can act on.
Build
The system end-to-end, with tests, an evaluation set from your own documents, and cost measured per query.
Deploy
Cut over against real users and real data, integrated with the systems you already run.
Run
We stay after launch: evaluations guard every release, costs are tracked, the system grows with the work.
Where it runs
EU infrastructure, audit trails by design
Our own products run on EU infrastructure and monitor European aviation regulation for European operators, so data residency and audit trails are things we build, not appendices we attach.
| Production hosting | Frankfurt (EU) |
| Team on every engagement | Senior engineers only, no handoffs |
| Working from | Sarajevo, remote-first across Europe |
| Working language | English |
| Stack defaults | Postgres + pgvector, Python, React |
| After launch | We stay and operate, or hand over documented |
Questions we get
Straight answers
What is an AI implementation partner?
A team that takes shared accountability for an AI system from discovery through production operation. A strategy firm delivers recommendations; a development shop delivers a proof of concept and exits. The test is simple: who is watching the system's cost, quality, and failures three months after launch?
How is starmo different from a large consultancy?
Choose a large consultancy if you need hundreds of people, 24-hour global coverage, or a brand your board already knows. Choose starmo if you want the people who build the system in the room from day one: senior engineers, production-grade defaults, and per-query costs measured rather than estimated. Everything on our work page was built by the people you would talk to.
What does it cost?
Discovery week is a fixed fee and ends with an itemized estimate for your specific workflow, before you commit to anything. Builds are scoped from that estimate, fixed-price where discovery supports it. Reference points from our own systems: a production retrieval assistant with 630 backend tests and a 100-case eval set is a multi-month build; a regulatory monitoring module costs about $0.02 per weekly run to operate; retrieval queries run at $0.006 to $0.02 each, measured by per-query tracing.
Do you work with existing in-house teams?
Yes. Embedded is the default: we work in your repositories and your tools, and the system is documented and handed over so your team can operate it. When our aviation engagement reached handover, the client received written documentation and a first-30-days operations guide.
What happens after delivery? Are we dependent on you?
No. Handover documentation, an operations guide, and deliberately mainstream technology choices (Postgres, FastAPI, React) mean any competent team can run what we build. Ongoing operation by us is an option many clients take. It is never a requirement.
Do you handle GDPR and data residency?
Yes, as an architecture input rather than a checkbox. Our production deployments run in Frankfurt, and retrieval systems can be designed so source documents and embeddings never leave EU-hosted databases. For model calls we choose provider terms to match your data classification, with EU endpoints where required. We assess where your use case lands under the EU AI Act during discovery.
When should we NOT hire starmo?
If you need a large delivery bench, formal 24/7 support coverage, on-site presence outside Europe, or certifications such as ISO 27001 as a hard procurement gate. We are not that firm yet, and pretending otherwise would waste your time. We say so in the first call if it applies.
What if we only want to know whether our plan is realistic?
That is the free audit: a 30-minute call on one concrete workflow and a written one-to-two-page answer on whether it is worth building and roughly what it takes. If it is not a fit, we say so in the first five minutes.