Skip to content

Use case · enterprise AI teams

Domain corpora from sources you are allowed to use

Most enterprise AI data work is a permissions problem before it is a modelling problem. Whose data is it, what may it be used for, and who reviews the result.

01

Where teams usually are when they call

your situation

Each one points at a different product — the decision helper below turns the symptom into a starting point.

situation 01

Private or customer-owned data

The data exists inside your organisation and cannot leave it casually. Isolation and policy come before pipelines.

situation 02

A taxonomy nobody else uses

Your labels, your hierarchy, your definitions — and nothing off the shelf maps onto them cleanly.

situation 03

It goes stale

A one-off delivery is obsolete in a quarter. What you need is a release cadence.

02

The products that answer them

what we build for this

Custom Dataset Development

Your sources, taxonomy, schema and delivery channel, built as a repeatable pipeline.

  • your schema
  • your cadence
Custom development →

Monolingual Corpora

Domain-scoped public text to sit alongside your private data.

  • domain
  • freshness
Monolingual corpora →

LLM Training Data

Behaviour data built on your domain: instructions, preferences, evaluation.

  • SFT
  • evaluation
LLM training data →
03

Start from the symptom, not the catalogue

decision helper
Start from the symptom, not the catalogue
If you needStart hereWhy
To use data you already ownCustom dataset developmentTransformation under your policy, inside an agreed boundary
To add public domain textMonolingual corporaSource registry with include / exclude / review decisions
Your own taxonomy appliedCustom dataset developmentImported as given, versioned, never silently normalised
Domain-expert judgement in the loopCustom dataset developmentReview levels chosen per class, with adjudication
A quarterly refreshCustom dataset developmentDelta releases with a changelog and a split manifest
04

What we measure on this kind of project

quality controls that matter here

Project isolation

Where the data lives and who can reach it during the project.

how measured · agreed per project, stated in contract

Domain-expert agreement

Agreement between reviewers on labels that matter to you.

how measured · inter-annotator agreement, per class

Provenance completeness

Records carrying a full, resolvable lineage chain.

how measured · manifest validation

Refresh integrity

What changed between two releases, and why.

how measured · changelog + delta manifest

Quality & Provenance →

Bring us a language, a domain or a schema.

We will help define a feasible pilot, quality criteria and a delivery format for your model.