Two reasons people call us.
Some know exactly which integrations are costing them. Others only know that a simple question about their own business does not have a simple answer. The fundamental work needed underneath is the same. What we deliver is not.
Custom integrations are eating your roadmap.
Every connector your customers ask for becomes another service somebody has to operate. We build them and we run them, so your engineers stay on your product.
It's time to run your business smarter.
The figures are already in systems you pay for. We read them and hand back one weekly list of what needs your attention, plus an assistant that answers from your own numbers.
Your first insight dashboard is free.
Your systems, connected once.
We read what you already run, turn it into data that agrees with itself, and put it where your people actually work.
- On-premise systems
- Cloud APIs
- Databases
- Files & SFTP
- Answers in chat
- Live dashboards
- Data warehouse
- ERP imports
- Your application
Learn more about how the Beetl platform works.
Your AI can only answer as well as the data behind it.
Once your systems are connected, cleaned and linked, the questions nobody could answer get an answer where your team already works, and every number shows the query and rows behind it. Ask once, then turn the answer into a check that runs every week.
BeetlBeetlMonday 08:00Weekly checkYour business, written down where your AI can read it.
What cost to serve means for you, when a delivery counts as late, which customers belong together. Beetl Brain records your definitions and rules with the evidence behind them, so answers use your meaning rather than a guess. It grows as your team asks questions, and anything uncertain waits for someone authorized to confirm it.
Cost to serve
Fulfillment, freight and support time per account, set against net revenue after discounts.
Run Beetl from the AI you already use.
Claude, ChatGPT, Copilot or a model you host yourself connects through Beetl's MCP server. One request becomes a connection, a pipeline, a dashboard, a weekly check and a new rule in Beetl Brain. Every step is logged, and deploys and new rules wait for a person to approve them.
We built this once, for ourselves.
The Beetl founding team rebuilt the data platform behind a programmatic job ads product at an HR tech company. The architecture we landed on is the architecture Beetl runs on today.
The problem was never the pipeline. It was proving the pipeline was wrong.
An HR tech company of 1,200 people. 6 data engineers ran the pipeline behind a programmatic job ads platform processing billions of events a day. Most of their capacity went into one loop: is this number actually wrong, or is the metric behaving exactly as designed? Days to reproduce it. Days more to backfill it.
We started with fixing ingestion. One source, done properly.
Everything downstream depends on what comes in, so nothing further along the pipeline can rescue bad data. Starting with the highest impact fix is still the shape of a first engagement with Beetl.
Then we rebuilt the floor underneath it.
Declarative SQL pipelines on a Rust runtime, reading and writing files in object storage instead of a database. With lower infrastructure costs and higher reliability, debugging stopped eating valuable team capacity, which could now go into data products the platform had never been able to offer.
That company was not a Beetl customer. Beetl did not exist yet. These are numbers we measured on a system the three of us built and operated ourselves, and they are the reason Beetl is built the way it is.
Tell us what you run.
Name the systems and what has to come out of them. We will tell you what we can connect, what it would take, and honestly if it is not a fit.
Start with the one that costs you the most.
Tell us what breaks, what it feeds, and who notices when it goes wrong. We hit this problem ourselves over and over again throughout our careers, which is why Beetl exists. Vienna-based, hosted in the EU.