Trusted by 40+ businesses

We work with startups and enterprises to design, build, and scale AI-powered systems that automate processes, support decision making, and integrate with existing software.

What we do

Build. Automate. Ship. AI that earns its keep.

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AI & Data

Complex AI systems and the data foundations underneath. Strategy, agents, GenAI, ML, data platforms, and the MLOps to run it.

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Intelligent Automation

AI agents and pipelines that automate operations at scale. No manual bottlenecks, no brittle scripts.

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Products & Platforms

Senior engineering teams shipping products that use AI where it matters. From MVP to mature platform, with cloud architecture built in.

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Pete Willcox
Pete WillcoxVP ProductRecast
All members of the Codino team fit seamlessly into our delivery teams, building excellent relationships and always willing to go the extra mile to deliver on our Roadmap in a timely and efficient way. We have built extremely good relationships with them and they feel just like part of the team

A happy client who has worked with us for over 5 years, building and scaling their core platform together.

Describe Your Project

How we work together

The same path on every project: prove the value on real data early, then harden what works into production. No big-bang launches, no surprises at handover.

  1. 01

    Discovery and data check

    A workshop to map the real problem, the decision it should support, and the data you actually have. AI projects live or die on data readiness, so we check it first, not after.

  2. 02

    Define what good means

    We agree the success metric, the baseline and the acceptable trade-offs before building. So at handover we can prove value, not argue about it.

  3. 03

    Prototype on real data

    A narrow, working version wired to your real data and systems, usually in three to four weeks. You see whether the value is real before scaling the investment.

  4. 04

    Harden for production

    Evaluation, guardrails, monitoring, integration and the security review. The system runs unattended on a slice of real traffic before it carries the full load.

  5. 05

    Run and improve

    Live monitoring catches drift before your users do. We retrain and refine as the data shifts, hand over the runbooks, and step out with your team owning it.

What Clients say about us

Marcin Walaszczyk

Marcin Walaszczyk

CTO

"The expertise of the leaders, coupled with the diverse skill sets of their teams, truly sets them apart. Their vast expe..."

ZipZero

Peter Holc

Peter Holc

CTO

"The team showcased best practices in code quality and architecture, leading to scalable and maintainable solutions. The..."

Nextbike Polska

Todd Gibson

Todd Gibson

VP of Product

"Working with Codino has been exceptional. Their dedication to our project's success was unparalleled. From meticulous at..."

Pathship

Tomasz Naumowicz

Tomasz Naumowicz

CEO

"Codino seamlessly integrated into the client's team and delivered high-quality work, achieving a successful launch and g..."

Alpaqa Studio

Zach Walker

Zach Walker

CEO

"Maciek and his team are amazing. We went to them with our project, wireframes, and deadlines and not only did they stay..."

Illumie

Łukasz Królak

Łukasz Królak

Head of Product

"The greatest value of working with Codino was their professionalism and the ability to search for and suggest the best s..."

MAM

Vishnu Kaura

Vishnu Kaura

Assistant VP Product & Strategy

"Codino is working on creating a product for our company, they have a keen understanding of technology and do not just en..."

Axisrooms

Frequently asked questions

We deliver complex AI systems from strategy and use-case discovery, through agentic systems, RAG and custom ML, to MLOps and the operations that keep them running. Our team of 30+ engineers has shipped these systems for clients across several countries, in engagements that run from a few months to five years. Our Clutch reviews come from CTOs, product owners and software strategists, based on interviews conducted by independent researchers, not testimonials we wrote ourselves. The fastest way to tell if we fit is a short, private consultation. It is free.
We design for privacy from day one. We pick models that can run in your VPC or in EU regions, remove personal data before retrieval, isolate each customer's data, and work within your data-protection assessment. As an EU-based partner, GDPR compliance is part of the default, not a checkbox added later. For sensitive use cases we deploy on private infrastructure or dedicated tenants, and we avoid sending data to third-party model providers when local or self-hosted models meet the bar.
Before launch, we build evaluation harnesses with golden datasets, automated grading and human checks. After launch, live monitoring with drift detection. Without explicit measurement, AI quietly degrades and you only find out when customers complain. Every engagement includes a measurement plan tied to business outcomes: accuracy, latency, cost per task, and whichever KPI matters for the use case.
Both, where each makes sense. We start with prompt engineering and RAG because they are cheaper and faster to iterate. We move to fine-tuning when retrieval cannot reach the accuracy or consistency you need, or when prompt size becomes a cost or latency problem. For most enterprise cases like knowledge search, document automation and customer support, RAG is enough. For specialised domains or production agents on tight latency budgets, fine-tuned models often win.
You find out early and cheaply, by design. We prove the value on a narrow slice of real data in the first few weeks, against the success metric we agreed up front. If the data is not there or the value is not real, we tell you, and you have spent weeks, not a year. We would rather lose a phase than watch a project fail in month nine. And when something does not clear the bar, you still keep the data audit, the architecture decisions and an honest read on what is feasible.
Two ways. First, your team owns what we build: the documentation, runbooks, evaluation setup and the code, designed so your engineers can run and extend it after we leave. Second, we stay model- and vendor-independent. We have no partnerships that bias the choice, and we keep the architecture portable so you can swap models or clouds as prices and capabilities change. No long lock-in on our side either.
A proof of concept shows the value is real on a narrow slice. Production is the part most AI projects skip: evaluation that catches regressions, guardrails, monitoring and drift detection, integration with your systems, access controls and a security review, plus the operations to keep it running as data changes. A demo that works once is not the same as a system you can rely on every day. We build the second.
We offer the following engagement models: Dedicated Team A team of specialists for long-term collaboration. Pricing is based on the time required to complete the agreed work. Time and Material Developers at a set rate, with the final cost determined by the hours and materials spent on your project. Fixed-Price Our team joins for a fixed price based on an agreed scope, budget and timeline.

Let's Talk About Your Project

Get In Touch
Maciej Roman|CEO & Co-founder