APPLIED AI · DATA ENGINEERING

/ VIENNA · AT

The signal is already in your data.

3 project spots open for 2026

We build the data foundation and the AI that runs on it: retrieval, agents, and private models on your own infrastructure. Designed, built, and maintained by the same people.

Book a call See what we build

Most companies sit on years of data their AI can't touch. It's scattered across file shares, databases, wikis, and inboxes, and off-the-shelf tools don't know any of it. We build the layer in between: systems that retrieve, reason over, and act on what your business already knows, without handing your data to anyone else's cloud. And when the foundation isn't there yet, we build that too: the pipelines, the models, and the data platform underneath.

SERVICES · 4 LAYERS

What we
build

Four layers, in the order most projects run: build the data foundation and turn it into answers, make it findable, put AI to work on it, and keep all of it inside your walls. We start from whatever you have, an existing platform or a blank slate.

Field notes

Data Foundation & Analytics

PIPELINES · ANALYTICS · GOVERNANCE

The groundwork everything else runs on, and the analytics on top of it: data that is clean, modeled, governed, and turned into decisions.

Data pipelines and ELT, batch and streaming, orchestrated and version-controlled
Warehouses, lakehouses, and the storage and compute architecture underneath
Data modeling, schemas, and data contracts that keep sources consistent
Metadata, catalog, and lineage so teams can find and trust what they have
Data quality, testing, and observability, with monitoring and clear SLAs
Access control, PII handling, and encryption, so ownership stays with you
Migration off legacy systems, re-platformed and tuned for cost and performance
Metrics layers and semantic models so the whole company measures the same thing
BI and dashboards built on definitions people trust, not one-off spreadsheets
Forecasting and statistical modeling where it changes a decision

Retrieval & Knowledge

INGESTION · RETRIEVAL · RAG

Your data, searchable and reasoned over, not just stored.

Ingestion and data pipelines that turn scattered sources into a clean, queryable corpus
Semantic search across documents, databases, and mixed-format archives
Retrieval-augmented generation tuned to your corpus: hybrid, graph, and BM25 with vector, never a one-size-fits-all pipeline
Knowledge frameworks that turn a plain file system into a queryable knowledge base
Embedding pipelines and vector infrastructure that keep up as your data changes
Structured extraction from messy, unstructured, and multi-format sources

Agents & Automation

AGENTS · WORKFLOWS · INTEGRATION

Systems that act on your data, not just answer questions about it.

Autonomous and multi-agent systems with real tool use and orchestration
Workflow automation that connects AI to the stack you already run
Pipelines that let non-technical teams do data-engineering work in plain language: no scripts, no waiting on an engineer
Clean integrations between your data sources and the AI layer
Evaluation and observability, so the systems stay reliable in production

Private & Owned

ON-PREM · FINE-TUNING · PRIVATE BY DESIGN

Models that run inside your network. Your data never leaves it.

Local and on-prem LLM deployment that runs on your infrastructure, inside your intranet
Fine-tuning and training on your own data, for your own domain
Private-by-design architecture for teams that can't send data to a public API
Prompt engineering and system design that gets real work out of the models you own

PROCESS

How it
works

00
Meet
We come to you: two hours on-site and in person, walking through your data and systems and figuring out the requirements, timelines, and expectations. Afterward you get it in writing: what's possible and what to expect, plus a full implementation plan. All of it free, no pitch, no obligation.
01
Map
We refine the implementation plan together and go deeper: the architecture, data contracts, and the exact systems to build, scoped and sequenced so the work that pays off first comes first.
02
Build
We build it: the data pipelines and platform, the retrieval, agents, or models, and the analytics on top. Architecture, code, and deployment, one team end to end.
03
Ship & run
It goes live in your environment, documented and owned by you. Then we stay on: maintaining the pipelines and models, watching them in production, and extending the system as your data and needs change.

WHO YOU'RE WORKING WITH

VIENNA · AT
SMALL ON PURPOSE
END-TO-END
A FEW CLIENTS AT A TIME

We're a small AI and data engineering studio in Vienna, small on purpose. You work directly with the people who design the architecture, write the code, and keep it running. No account managers, no handoffs, no juniors learning on your project.

We take on a handful of clients at a time and go deep on each one. We build the system, deploy it in your environment, and stay for the part most firms skip: keeping it working. This is hands-on engineering, not advice. You walk away with production systems you own, not a strategy deck. And we work from both ends, putting the data you already have to work or building the data platform from scratch.

If your data is complex and your requirements are real, that's the work we want.

FAQ

Questions we get

Where does our data live? Does it leave our network?

It stays inside your network. We deploy retrieval, agents, and models on your own infrastructure, on-prem or in your intranet, so your data never goes to a public API or anyone else's cloud.

Do you only work with data we already have, or can you build from scratch?

Both. We put the data you already have to work, and when the foundation isn't there yet we build it: the pipelines, the platform, and the models underneath.

Is data engineering and analytics part of this, or just AI?

Both. We build the data foundation and the analytics on top, pipelines, platform, governance, metrics, and BI, alongside the retrieval, agents, and private models.

Is the first visit really free?

Yes. Two hours on-site, then a written read on what's possible and a full implementation plan. It's free and yours to keep, even if we never work together.

What happens after it ships?

We stay on. We maintain the pipelines and models, watch them in production, and extend the system as your data and needs change. Keeping it working is the part most firms skip, and the part we do.

Who actually does the work?

The people who design the architecture and write the code. No account managers, no handoffs, no juniors learning on your project. We take on a handful of clients at a time and go deep on each one.

What does a project cost?

It depends on scope. The free visit ends with a plan that lays out scope, sequence, and effort, so you see the number before you commit to anything.

THE FIRST STEP · FREE · ON-SITE

The first two hours are on us.

We come to you: two hours on-site and in person, walking through your data, your systems, and what's worth building. Then you get it in writing: what's possible and what to expect, plus a full implementation plan of what to build, in what order, and what it takes to run. It's free, and yours to keep, even if we never work together.

Book the walk-through

2 HOURSOn-site walk-through of your data and systems
IN WRITINGWhat's possible, what to expect, and a full implementation plan
€0Yours to keep, no cost, no obligation, no lock-in

Have data your AI can't use yet?

Tell us what you're sitting on. We'll give you a straight technical read on what's possible. No pitch.

Book a call or email hello@rushb.co