Data & AI in practice
AI that works in production. Starting from the data.
Built on data you can trust. We turn data scattered across your systems into AI your teams use every day.
20+ delivered Data & AI projects · 60+ engineers and consultants · Wrocław, Poland
Trusted by
Results from our deployments, measured at the client
Global manufacturers and a telecom operator, with numbers checked against the situation before the project.
fewer defective parts on welding lines
Case study · Global automotive parts manufacturer
fewer complaints after visual kit inspection
Case study · Global manufacturer of industrial equipment
lower operating costs of a telecom data platform
Case study · Telecommunications company
per quote, down from 4 to 6 hours
Case study · Manufacturing company
How Sofixit works
From the first question. To a working solution.
Goal
Process and metric
Data
Consistent sources
Analytics and AI
Model and tests
Deployment
Application and integrations
Maintenance
Monitoring and growth
Goal
Process and metric
Data
Consistent sources
Analytics and AI
Model and tests
Deployment
Application and integrations
Maintenance
Monitoring and growth
Data foundation
Business question and measurable goal
One process, one metric, today's baseline. Without it nobody can say later whether AI helped.
Data foundation
Data readiness and governance
We map sources, align definitions, fix quality and show lineage, so analysts know what they compare.
Data foundation
Architecture and proof of concept
A platform that fits your constraints: your data centre, the cloud or hybrid, also without internet access.
AI engineering into production
Engineering and evaluation
Models and agents tested against your history and expert decisions before anyone relies on them.
AI engineering into production
Staged rollout in shadow mode
The system works next to people first. It takes over only after it reaches the agreed accuracy.
AI engineering into production
Observability and continuous improvement
We monitor quality, costs and drift, and keep the solution running after go-live.
Three services, one goal: AI that pays off
Pick the part you need. Most clients start with data and grow into AI engineering.
Data foundation for AI
Data platforms, quality and governance that AI can rely on. On-premise, cloud or hybrid, also without internet access.
See the serviceAI engineering into production
Computer vision, forecasting, anomaly detection and GenAI agents, tested on your history and rolled out in shadow mode.
See the serviceData & AI teams
Data engineers, ML engineers and architects who join your team or deliver as a complete Scrum team.
See the serviceNot sure where to start? Start small, with a fixed scope and price
Each first step has a defined result, duration and price, so you can decide with numbers on the table.
Pilot on your data
One use case, your real data, a success metric agreed up front. The model works in shadow mode next to people before anyone relies on it.
from €10,500 net6 to 8 weeks
Data platform cost review
Where your data platform burns money, what can be fixed now, and what a migration off expensive licences would save.
from €4,200 net2 weeks
Case studies
Measured results from manufacturing, telecom, logistics, finance, retail and healthcare. Anonymised at our clients' request.
fewer defective parts
Weld quality AI: 86% fewer defective parts
Global automotive parts manufacturer
Read the case studyKit inspection with computer vision: 63% fewer complaints
Global manufacturer of industrial equipment · Industrial equipment manufacturing
GenAI quoting agent: from 4 to 6 hours to 15 minutes
Manufacturing company · Manufacturing
Logistics control tower: 37.6k containers tracked in real time
Global logistics provider, 30,000+ active shipping containers · Logistics
Telecom data platform: 2× faster, 60% lower operating costs
Telecommunications company · Telecommunications
Mental health data platform: 30× more patient data, every day
Digital mental health company · Healthcare
Industries we know from the inside
Seven industries, one approach: data first, then AI that people can trust and check.
- Manufacturing86%fewer defective parts in welding
- Telecommunications2×faster data processing, 60% lower operating costs
- Banking and finance1 dayfor a compliance report instead of 5
- Retail and e-commerce30 minfor a report instead of 2 hours
- Healthcare30×more frequent patient data
- Logistics37.6kcontainers tracked in real time
- Digital services<1 sfrom event to signal, instead of minutes
A team of 60+ engineers who put AI into production
Sofixit started with data platforms built on open-source technologies: Spark, Kafka, Trino, Iceberg. Today we use the same foundation to put AI into production. We are big enough to staff a full team and small enough that the people you meet are the engineers who will build your solution.
- engineers and consultants
- engineers and consultants
- delivery teams + R&D teams
- delivery teams + R&D teams
- Data & AI projects delivered
- Data & AI projects delivered
- technology stacks in production
- technology stacks in production
Questions buyers ask before the first call
What does Sofixit do?
We implement AI in companies, starting from the data it runs on: data platforms, data quality and governance, computer vision, forecasting, anomaly detection and GenAI agents with human approval. We mostly work with manufacturing and telecom companies.
How much does an AI project cost?
It depends on the data and the scope, so we sell the first step with a fixed price: the AI readiness assessment, a pilot on your data or a data platform cost review. Prices "from" are on each offer page. After the first step you get a quote for the full project with every line item justified.
Can it run in our own data centre, without internet access?
Yes. In our telecom platform project everything, including the models, runs in the client's data centre with no internet access. We also work in the cloud and in hybrid setups.
How do we know the AI works before we rely on it?
We test models against your historical data and against decisions of your experts, then run them in shadow mode next to people. The system takes over only after it reaches the accuracy agreed up front.
Is it worth it for a mid-sized company?
Yes, if there is one process with a measurable loss: scrap, complaints, downtime, slow quotes or platform costs. A narrow, measurable first project is better than a company-wide AI programme.
Where is your team and who will we work with?
Our engineers are based in Poland, headquartered in Wrocław. You work directly with the architects and engineers who build the solution.
Let's talk about your project
Which of your processes is worth improving?
Pick one problem.
Show us the data you have.
Let's agree a measurable goal.
Pick one problem, tell us what data you have, and we will propose a measurable goal and a first step.
We reply within one business day.