Source connections
Authorized ingestion from the agreed systems, files and event streams.
AI Data Engineering
Your AI needs data. Your data is everywhere.
Build the data paths your AI needs, from enterprise systems to large-scale pipelines.
How it fits together
- Source systems
- Working pipelines
- Usable data
What changes.
We connect the required sources and build batch or event-driven pipelines, including large data volumes and recoverable processing.
Yours to put to work.
- Scope and acceptance criteria agreed together.
Working data pipelines
Transformations, incremental updates, backfills and failure recovery.
A maintainable data service
Schemas, lineage, freshness monitoring and an operating handoff.
See an example engagement
An example scope, adapted to your environment.
- The starting point: An agent needs current operational data from several disconnected systems.
- The work: Connect the sources, normalize the records and implement incremental updates.
- The handoff: A monitored pipeline, usable data contracts and recovery procedures.
How we evaluate the result
- Required data arrives at the agreed freshness and volume.
- Backfills, duplicate events and interrupted jobs are handled correctly.
- Data lineage and pipeline failures are visible to operators.
A useful place to start
Let’s work through your specific problem.
Start with AI Data Engineering, scoped to your environment.