Solutions

From small models to enterprise scale.

Whether you're fine-tuning a small language model or building an enterprise-scale AI solution, the constraint is the same: data you can trust. Here's how teams put Pureset to work.

Use cases

Five jobs clean data does better.

Use case 01

Fine-tuning small language models

The problem

Small models have no capacity to waste. Noisy or duplicated examples teach the wrong habits, and synthetic instruction data narrows what they can do.

What Pureset provides
  • Instruction and preference sets written or verified by experts
  • Domain slices sized for focused models
  • Deduplicated against public benchmarks so evals stay honest
The outcome

Faster convergence and better generalization per parameter — smaller models that punch above their weight.

Use case 02

Pretraining foundation models

The problem

At trillion-token scale, synthetic contamination and duplication compound. Once model output is in the corpus, it can't be audited back out.

What Pureset provides
  • Petabyte-scale, human-authored corpora across domains
  • Sealed lineage per record and per shard
  • Versioned releases with deprecation notices
The outcome

A foundation with measurable diversity — and provenance that survives due diligence.

Use case 03

Enterprise & domain AI

The problem

Regulated industries need to know where training data came from, who owns it and what it contains — before a model ships.

What Pureset provides
  • Domain collections for finance, health, legal and public sector
  • Rights clearance and indemnification
  • PII scrubbing with audit evidence
The outcome

Models your legal, risk and compliance teams can sign off on.

Use case 04

Evaluation & benchmarking

The problem

Public benchmarks leak into training corpora. Scores inflate and stop meaning anything.

What Pureset provides
  • Held-out, never-published evaluation sets
  • Contamination screening of your training data against them
  • Domain-specific suites built with your team
The outcome

Evaluations that measure capability, not memorization.

Use case 05

Retrieval & knowledge bases

The problem

Retrieval-augmented systems repeat whatever is in the index — duplicates, stale copies and unlicensed content included.

What Pureset provides
  • Deduplicated, licensed reference corpora
  • Document-precise dates and source metadata for citations
  • Update feeds with changelogs
The outcome

Grounded answers with sources you're allowed to cite.

Industries

Built for teams that have to answer for their data.

Financial services

Filings, research and correspondence with rights and lineage you can document to regulators.

Healthcare & life sciences

Scientific literature and de-identified domain text, with PII audit evidence for every release.

Legal & compliance

Statutes, regulatory text and legal writing, with licensing your counsel can review line by line.

Public sector & research

Provenance-documented corpora built to pass procurement and research-ethics review.

Software & developer tools

License-tagged, human-authored code for coding assistants and code models.

Publishers & archives

Own a collection? License it through Pureset, with attribution, usage controls and a verifiable audit trail.

Ways to work with Pureset

License it, commission it — or clean what you have.

License

Off-the-shelf collections under an enterprise license — the fastest path to training.

Browse datasets

Custom collection

We source, commission and curate to your spec: domains, languages, eras and formats.

Scope a collection

Data audit

Run your own corpus through our pipeline. Get duplication, bias, contamination and PII reports, cleaned shards and a remediation plan.

Request an audit

Data partnership

Ongoing releases, refreshes and new domains as your model roadmap grows.

Talk to us

Not sure where to start?

Tell us what you're training and at what scale. A data specialist will recommend a starting slice — or an audit of what you already have.

Schedule a consultation