We build the AI feature and ship it to production
Our custom AI development services take a scoped feature or product and turn it into software running in your environment, with evals, guardrails and a cost ceiling. Working code every week, not demos.
Unlocking Tech is an AI engineering company based in Lisbon, Portugal, providing custom AI development services for SMEs and scale-ups — typically companies of 10 to 200 people. An engagement takes a scoped feature, product or agent and ships it as software running in your environment: senior engineers only, working code demoed every Friday, evals running in CI from day one, prompts in version control, and a cost ceiling enforced in code. Projects are fixed-price and scoped before any production code is written — most start between €15k and €50k and reach production in weeks, not quarters. You leave with code in your repo, a runbook and one agreed metric, and you own all of it.
Everything you need.Shipped to production.
No notebooks. No demos as deliverables. Just software running in your environment, with evals, guardrails and a cost ceiling you agreed up front.
A documented model choice
Frontier vs open-weight per task, with the cost, latency and quality trade-off written down against your data. Not a vendor default you can't argue with.
Evals running in CI from day one
A labelled test set scored on every change. A prompt or model swap that regresses quality fails the build, before it reaches a user.
Prompts and config in version control
Prompts live in the repo, are diffable and reviewed in PRs, with the model version pinned. No silent changes in a console nobody can trace.
A cost ceiling enforced in code
Per-request and per-tenant budgets, model-tier routing, caching and alerts before you hit the number. Agreed up front, not discovered on the invoice.
Guardrails on the user-facing path
Schema-constrained outputs, PII handling, injection and jailbreak mitigation, sane refusals on out-of-scope asks. It survives real users, not just the happy path.
Software you own, with the metric
Code in your repo, a runbook, and a dashboard tracking the one number we agreed to move. A clean handover your team can run without us.
Five steps.To production, fast.
From a thirty-minute call to a deployed feature with an owned metric, broken into milestones you sign off on.
Thirty minutes with an engineer on the call. You describe the feature, the data you have, latency tolerance and budget shape. We tell you honestly whether this is a build, an integration, or something you don't need us for.
Architecture, model choice with the trade-off written down, the eval set and target metric defined together with you, cost ceiling, milestones and price in writing. The metric is agreed here, not retrofitted at the end.
Senior engineers ship to a real environment on a weekly cadence, with a demo every Friday against the eval set. Prompts and config in version control from the first commit; evals running in CI.
Once the core path works: injection and abuse handling, cost-ceiling enforcement, observability, load behaviour and edge cases. The thing holds up under real traffic.
Production deploy, dashboard live, tuned until the agreed number holds. Then a clean handover with runbook and docs, or we stay on for Support & Scale if you want it.
We're not for everyone.We’re for the teams ready to ship it.
If any of these sound familiar, we should talk.
Founder with a stuck prototype
A GPT or Claude demo that won't survive production
- Hallucinations on real data
- Unpredictable inference costs
- No way to tell if a change helped or hurt
Outcome: A prototype that becomes software you can ship and trust.
Product or engineering lead
Adding an AI feature to a real codebase
- No in-house LLM, RAG or agent depth
- Real users and a real quality bar to meet
- Don't want to hire a permanent AI team for one initiative
Outcome: The feature shipped to your standard, then handed back clean.
CTO burned by an AI agency
Paid for a POC that was a notebook
- No tests, prompts edited live in a console
- Costs nobody could explain
- A team that says yes to everything
Outcome: Production software you own, and honest answers when AI is wrong.
Senior engineers. No handovers. No fluff.
What does an AI software development company do?
An AI software development company builds custom software with AI inside it — features and products designed for one company's use case and shipped to production, not sold off the shelf. Unlocking Tech is an AI software development company that builds those AI features and products for your specific problem, with evals, guardrails, and a cost ceiling enforced in code. Unlike most artificial intelligence software development companies, we keep prompts and config in version control and hand you the code and one agreed metric — you own both.
Custom and bespoke software development
We are a software development company that builds custom software end to end, including SaaS products, with AI added only where it pays off. Custom software development here means engineers scope the build with you and ship working code, not configure a generic tool to almost fit. As a bespoke software development company, we design each system around your data, your workflow, and the metric you care about — then run it to production standards.
Our AI software development service
Our AI software development service is a scoped build run by senior engineers: we agree the problem and the metric, ship working code weekly, and hold it to production standards with evals, guardrails, and version-controlled config. Where most generative AI development companies stop at a demo, we ship customized AI solutions you can put real load on — and you own the code. Engagements are project-based, typically €15k–€50k and up.
A machine learning development company that ships models to production
As a machine learning development company, we build and train models that make predictions or decisions on your data, then run them as a live part of your product. Most machine learning companies stop at a notebook. We build the model, the evals that prove it works, and the monitoring that catches drift after launch. You get production code you own, not a demo that breaks the first time real data hits it. Among machine learning development companies, that is the line we hold: versioned data, reproducible training, and a clear path from prototype to the thing your users actually touch. That is how a serious machine learning business has to run.
Data engineering: the pipelines your models run on
As a data engineering company, we build the plumbing that gets data from where it lives to where your models and analytics can use it: ingestion pipelines, warehouses, and feature stores. A model is only as good as the data feeding it. So before we train anything, we build the pipelines, schemas, and feature stores that keep that data clean, fresh, and queryable. Unlike data engineering companies that hand you a diagram and leave, we ship the running pipelines and the code behind them, instrumented so you can see the moment something breaks.
How do you choose a custom AI development company?
Choose a custom AI development company on evidence of production discipline, not portfolio screenshots. Ask three things: how quality is measured before launch — the answer should be an eval set built on your data; how changes are controlled — prompts and config in version control, reviewed like code; and what happens when the model is wrong — escalation to a person, not silence. A vendor who answers those in writing is selling engineering. One who answers with a demo is selling the demo.
What should artificial intelligence development services include?
Artificial intelligence development services should cover the full path to production: scoping the problem to one metric, choosing and justifying the model, building the feature with evals running in CI, hardening it with guardrails and a cost ceiling, and handing over code you own with a runbook. Many offerings stop at the prototype and leave the reliability work — the part that decides whether the system survives real use — to you. Price the whole path, not the demo.
Red flags when buying AI development services
The red flags repeat: a proposal without a metric or an eval plan; pricing that rewards time spent instead of a result; prompts edited live in a console nobody can audit; ownership of code and models left vague in the contract; and a yes to every idea. Buyers often come to us after an AI tool nobody trusted enough to keep using — usually because nobody defined what working meant before the build started. Define it first. It is the cheapest part of the project.
Custom AI development vs the alternatives
Where custom AI development services fit against buying an off-the-shelf tool or hiring in-house — and where they don't.
Custom AI development What we build | Off-the-shelf AI tool | In-house AI hire | |
|---|---|---|---|
| Fits your workflow and data | ✓ | If your process matches the tool's | Yes, over time |
| Time to production | Weeks, in milestones | Days to configure | Months — hiring comes first |
| Quality measured on your data (evals) | ✓ | — | If you build the discipline |
| Running cost | Ceiling enforced in code | Per-seat licence that grows with the team | Salaries, fixed |
| Who owns the code and the models | You | The vendor | You |
| When the vendor changes course | Code, runbook and docs are yours | You migrate | Not applicable |
| Best for | A feature or product with a metric to move | A generic job the tool already does well | AI as your core product, long term |
Start your deployment.
Talk directly to a principal engineer.
No sales team.
No discovery workshops.
No procurement circus.
We scope, build and ship.
- Reply within 24h
- Engineer-led assessment
- Written proposal
- Portugal / EU timezone
No commitment. Just an engineer.