Data pipelines and storage on hardware you own.
Pipelines, storage and the operations around them, on infrastructure you own. Most of the cost in a data platform falls not on compute but on per-call APIs for data available locally, on egress for storage you have already paid for, and on fetching the same records twice because nothing checked before the download.
The problem it solves
Data arrives from sources that do not agree with each other, at a rate nobody controls, and the bill grows in proportion to volume rather than to value. The main sources of overspend: a paid API in place of a public dataset with the same answer; egress on files that should never leave the perimeter; duplicates stored because the check sits after the download instead of before it. Each is fixed once and paid for continuously.
What it covers
- An audit of the sources and what they currently cost
- A single pipeline across heterogeneous sources
- Resumable collection that survives a dropped connection
- Deduplication and quality checks before load
- Dataset partitioning and versioning
- Paid APIs replaced by local data where applicable
- S3-compatible storage on your own infrastructure
- Backup and restore, with the restore procedure verified
- Cost monitoring with early warning as the bill rises
- Runbooks and handover of operations to your team
You get
Your data inside your own perimeter, a storage and processing cost you can predict, and no line item for moving your own files around.
Most often bought by media and e-commerce operations paying egress on their own files, and by teams whose per-call API bill has grown faster than the value it returns.
Book an architecture review →Evidence
Sometimes the data you need lives on someone else's platform: marketplaces, directories, booking sites, public registries. You need it on a schedule rather than once, and the engineering problem is not fetching a page. It is staying correct while the far side changes its format, rate-limits you, or drops the connection halfway through.
- Several platforms at once, each with its own shape
- Resumes where it stopped, not from the beginning
- Outbound address rotation against rate limits
- Deduplication before download, so nothing is paid for twice
- The same item across platforms reconciled into one record
- Scheduling, and a record of what appeared or changed
- Per-platform parsing tests, so the test breaks before production does
Said plainly, before anything is built: collecting from platforms you do not own is bounded by their terms of use and by law. What is collected, in what volume and how often is agreed at the start of the work, not discovered at the end of it.