Training data pipelines for data scientists — done for you
Using LLMs in a publishing pipeline where they help, and refusing them where they hallucinate. Scoped as a standalone workstream or folded into a full data scientists build.
from $1,500 as a standalone workstream · included in the Data Scientists Build tier
- Fact generation
- Not permitted
- Deliverables
- 4
- Runs with
- Python / pandas
What we actually do here
Language models are excellent at normalising and summarising known facts and dangerous at supplying unknown ones. We run this as a fixed-scope workstream: 4 defined deliverables, one named approver, and a written handover at the end. It attaches to an existing data scientists engagement or stands alone if that is the only piece you are missing.
- 1Audit
Permitted uses: normalisation, summarisation, classification, extraction
- 2Design
Forbidden uses: fact generation, statistic invention, source fabrication
- 3Build
Human-verified sampling rates per task type
- 4Hand over
Evaluation harness for output quality drift over time
- Usage policy per task type
- Prompt and evaluation harness in the repo
- Sampling and review protocol
- Drift monitoring on model output
What the first weeks look like
- Week 1
Scoping call and data review
We look at what data scientists already hold — systems, exports, APIs — and score each axis for demand and defensibility.
- Weeks 3–4
Contract and template design
The data contract is written and the first template is designed against real rows, not placeholders.
- Weeks 5–8
First tranche live
4,500–10,500 URLs published with schema, internal links, sitemap entries and IndexNow.
- Weeks 9–14
Read, widen, hand over
Indexation and impression data decides what widens and what gets cut. Templates, gates and runbook transfer to you.
Training data pipelines — questions before you buy
Start at 5% per template family per batch, and raise it whenever the error rate exceeds your accepted threshold.
Programmatic SEO builds for other seats
Want the training data pipelines for data scientists surface scoped before you build it?
We'll audit the data source, size the first batch, set the performance budget and tell you honestly if programmatic is the wrong tool for your category.
