Data Engineering
How much of your pipeline work is maintenance?
Agents build and maintain the data layer. You govern it. Full traceability, real code, no hallucinations.
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Sound familiar?
Data engineers are expected to move fast and build reliably, but most of the time goes to maintenance, not innovation.
Maintenance burden
44–90% of data engineering time goes to maintaining existing pipelines. Schema changes, broken dependencies, and silent failures eat your week.
Schema changes break everything
A field gets renamed upstream. Three pipelines break. Nobody notices until the dashboard goes blank Monday morning.
Tool sprawl
Fivetran for ingestion, dbt for transforms, Airflow for orchestration, Snowflake for storage. Every tool needs its own setup and maintenance.
Lost in translation
Business says ‘revenue.’ You build a model. Turns out they meant something different. The translation layer between business and code is where errors hide. Ronja detects where teams define terms differently and surfaces the evidence, so your data team can resolve it before the board meeting does.
From maintaining to governing
Ronja’s AI agents build and maintain the data layer, writing real, versioned code. Your team shifts from executing to governing: setting rules, reviewing logic, and endorsing definitions.
- Agents write transformation code: real SQL, versioned and auditable
- No more pipeline babysitting. Agents detect and repair breaks
- Import existing dbt models and Looker definitions
- Your team governs quality, not queues
- Full data lineage from source to dashboard
How Ronja works
Every source connected. Automatically.
Salesforce, HubSpot, your ERP, databases, APIs. Ronja connects to 100+ sources and keeps the data flowing. One unified view, always up to date.
Ask the questions that actually matter.
Ronja joins marketing data with CRM and revenue data automatically. Ask anything in plain language and get answers traced to source.
Your data has structure. Endorsed definitions give it meaning.
Endorsed definitions store your transformation rules, metric calculations, and business logic. Define it once. Agents apply the right context to every question. No more conflicting pipeline definitions. Define them once, agents enforce them everywhere.
What Ronja does for data engineering teams
Pipeline Automation
Agents build, schedule, and maintain data pipelines. When schemas change or sources break, agents detect and repair automatically.
Data Modeling
Agents write transformation code: real SQL, versioned, auditable. Import existing dbt models or build from scratch.
Data Quality
Continuous data quality monitoring. Agents flag anomalies, missing data, and schema drift before they reach dashboards.
Self-Serve Analytics
Business users get answers without filing tickets. Your team governs the logic, not the request queue.
Just ask
The questions everyone asks. Answered instantly, traced to source.
Ask in plain language. Get answers traced to source. No analysts, no dashboards, no waiting.
Every answer in Ronja is traceable to source. No hallucinations, no black boxes. Real code, auditable and reproducible.
How Ronja compares
Not another tool in the stack
| Ronja | Internal data stack | |
|---|---|---|
| Time to first insight | Minutes | Weeks of scoping |
| Who does the work | Agents handle routine work. Your team governs. | Data engineering team |
| When sources change | Agents flag changes and propose fixes. Your team approves. | Manual pipeline rebuilds |
| Reporting | Always up to date | Depends on pipeline schedule |
| Accuracy | Traceable to source | Depends on who built it |