Fragmented data
The data can't be trusted
Data sits in several data warehouses, legacy systems and spreadsheets. Reports show different numbers, and every new request means starting the clean-up all over again.
Data & AI Engineering
Data & AI engineering for complex enterprise environments
Turn enterprise data
Turn enterprise data
into working AI.
We build reliable data platforms, bring AI into day-to-day operations, and write the software that connects them. Our experienced engineers work together with your team and take what we start through to production.
Work with usTechnologies we work with
Data
- Databricks
- Snowflake
- BigQuery
AI
- Azure OpenAI
- Vertex AI
- Google ADK
Applications
- Java
- .NET
- React
Cloud
- Azure
- AWS
- Kubernetes
What we do
We turn your existing data and systems into applications and automated workflows that run in production – together with your own team.
40+engineers, data and AI specialists
3areas in one team: data, AI, software
2018the year we started with our longest-standing client
ISO9001 and ISO/IEC 27001 certified
Where do projects get stuck?
Does any of this sound familiar?
Most of our work together starts from one of these.
Stalled AI
The AI pilot never reaches production
The demo works well, but not on real data. Access control, quality measurement and integration with existing systems are missing.
AI Applications & IntegrationComplex systems
Nobody knows what a change affects
Systems are connected in so many ways that it is hard to say which reports and processes will break when a field or pipeline changes.
Product Engineering & Modernization
Services
Data platforms, AI applications and the software that connects them – from one team, built on the systems you already have.
01 /
Data & AI Engineering
We provide reliable data for reports, applications and AI.
Data platforms, data modelling, pipelines, migration, data quality, performance and cost optimisation.
Details 02 /AI Applications & Integration
We bring AI built on your enterprise knowledge and data into day-to-day operations.
RAG (answers grounded in your own sources), knowledge search, impact analysis, process automation, system integration.
Details 03 /Product Engineering & Modernization
We build and develop the applications your business runs on.
Web applications, backend, APIs, modernisation of legacy systems, testing and release.
DetailsCase studies
Hungarian commercial bank
Data & AI Engineering
Data warehouse migration to a Databricks lakehouse
Our role: 4-person data engineering team · technical delivery of the migration with the bank's data team
DetailsHungarian retail chain
Data & AI Engineering
Unified data model and Snowflake cost optimisation
Our role: 2 data engineers · alongside the internal BI team
DetailsHungarian subsidiary of an international insurance group
AI Applications & Integration
RAG-based knowledge search for claims handlers
Our role: End-to-end delivery · from ingestion to integration into the claims application
DetailsHungarian energy supplier
AI Applications & Integration
AI-based impact analysis for data warehouse changes
Our role: Joint delivery with the client's data team · knowledge graph and query interface
DetailsInternational logistics company
Product Engineering & Modernization
Gradual replacement of a monolithic transport management system
Our role: Dedicated 6-person team with a technical lead · with the client's IT team
DetailsAutomotive supplier
Product Engineering & Modernization
Web-based production planning app built on the data platform
Our role: End-to-end application development · integration with the client's data platform
DetailsThe case descriptions are sample texts for this concept site. On the final site they will be replaced with real projects approved by our clients.
How we work
Experienced engineers work on the project, it is always clear who is responsible for what, and we review the results together.
01 — Who you talk to
Directly with the engineers
You talk to the people who build the system – there is no layer of project managers or sales people in between.
02 — Working together
Together with your team
We work with your tools, in your codebase and to your processes, so your team can carry the work forward.
03 — Review
Faster with AI, checked by people
We use AI for design, development and testing, but an engineer reviews every change.
04 — Handover
Handed over so you can take it forward
We agree in advance when the work is done. At the end you get documentation and training.
Ways to work together
There are three ways we can work together, and in each one it is clear who is responsible for what.
A —
Team extension
Our experienced engineers join your existing team, under your direction and to your processes.
When it fits: You have an in-house team and leadership, but lack capacity or specialist knowledge.
Who leads: Your team; we are responsible for professional quality.
Billing: Based on effort.
B —
Dedicated team
An established SCALER team with its own technical lead, for one product or area, working closely with your team.
When it fits: A whole area or product needs ongoing development.
Who leads: Jointly; we provide the technical leadership.
Billing: Based on effort, monthly.
C —
Scoped project
We take on a pipeline, integration or AI feature in full, with handover criteria agreed in advance.
When it fits: The goal is well defined, and you are looking for a team that will see it through.
Who leads: We do; we are responsible for both delivery and handover.
Billing: Based on effort or a fixed price.
How are we different?
When does it make sense to choose us over a large systems integrator, a staffing agency or hiring in-house?
| SCALER | Large international systems integrator | Staffing agency | Hiring in-house | |
|---|---|---|---|---|
| How soon does the work start? | a few weeks | 1–3 months (tender, contract) | a few weeks | 3–6 months |
| Data, AI and software in one team | ✓ | ✓ | ✕ | partly |
| Who is responsible for the outcome? | we are, for the work we take on | the systems integrator | you – you only get people | you |
| Who do you talk to during the project? | the engineers doing the work | project managers, account managers | the agency and the specialist | your own team |
| Fits into your existing systems and processes | ✓ | partly | ✓ | ✓ |
| The knowledge stays with you after the project | ✓ | partly | partly | ✓ |
| Can be scaled up or down flexibly | ✓ | partly | ✓ | ✕ |
| Cost level | medium | high | low–medium | long-term fixed cost |
What our clients say
Clients work with us because our engineers fit into the team and see through what they take on.
4.9
average client rating
We have been working with the SCALER team since 2018, and over the years our collaboration has become closer thanks to their positive and proactive attitude, and their understanding of business challenges.
Their team was really focused on making sure the matching algorithm worked really well.
They met all milestones and delivered the project within the agreed-upon timeline.
They are really deeply digging into the details to make the best shape of each part of the product.
The first step
Work with us
Bring a specific data or AI problem.
In 30 minutes, one of our experienced engineers talks through the situation with you and what it would take to solve it. Not a sales pitch.
Data platform and AI feasibility assessment
For one selected business need, we look at which data and integrations are needed, what is missing, and in what steps it makes sense to deliver it.
Enterprise knowledge search or impact analysis
We deliver one well-defined use case, with data sources, access rights and quality expectations agreed in advance.