The Problem RegTechs Hit at Scale

Regulatory content is rarely “available” in a form a platform can rely on.

In practice, it is:

  • Fragmented across publishers and formats
  • Inconsistent in structure and terminology
  • Difficult to evidence and trace back to source
  • Expensive to maintain as jurisdictions, versions, and interpretations evolve

The result: teams spend disproportionate time building and maintaining data plumbing, instead of shipping product.

The Trap: “We’ll just crawl it”

t’s tempting to start with crawling and extraction, especially when expanding coverage.

But crawling is the smallest part of the problem.

Once you ingest content, you still need:

  • Standardisation across publishers
  • Stable identifiers
  • Structures that hold across jurisdictions
  • Provenance and change history
  • Defensible versioning over time

Without this, scale creates instability, not product advantage.

Build what differentiates your platform:

  • Workflow logic and customer experience
  • Risk/compliance reasoning and outputs
  • Analytics, reporting, and product intelligence
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Buy what is critical, but infrastructure:

  • Regulatory acquisition and monitoring at scale
  • Normalisation and consistent structures across jurisdictions
  • Long-term maintenance as publishers and formats change
  • Machine-consumable data designed for AI and automation

What “good” regulatory data must do

Whether you build or buy, a usable regulatory data layer must support:

Consistency

Comparable structures across jurisdictions and publishers

Traceability

Requirements can be evidenced back to source

Change handling

Updates, replacements, revocations, effective dates

Scalability

Expand coverage without rewriting your model

Machine consumption

Reliable input for AI, automation, and analytics

If any one of these fails, your downstream product inherits the fragility.

What you’re really buying

Buying the data layer isn’t outsourcing your product – it’s removing infrastructure overhead, enabling:

Time for faster coverage expansion

Certainty which requires less rework, fewer edge-case failures

Trust for auditability and provenance

Focus so engineering time stays on differentiated product value

 REGGENOME: YOUR DATA PARTNER

Power your regulatory solutions with AI-optimised data

Deliver faster, smarter compliance solutions with structured, scalable, machine-readable regulatory data built for AI, automation and scale.

 

why reggenome

Founded at the University of Cambridge. Trusted by regulators.

RegGenome data is built for trust.

Born out of University of Cambridge research and as a founding member of the Regulatory Genome Project, our information structures are reviewed with regulators, mapped to standards, and structured with standard-setting bodies.

This strengthens provenance, interoperability, and trust – giving you confidence in the accuracy and reliability of the information you access.

collaboration with the university of cambridge

What RegGenome data gives RegTechs

RegGenome provides regulatory content as structured data, designed to plug into RegTech platforms reliably

Core characteristics:

  • Jurisdiction-agnostic structures so your product doesn’t fracture by market

  • Consistent IDs so you can reference, map, and track

  • Provenance so outputs are explainable and defensible

  • Versioning and change history so you can manage regulatory evolution without manual patching

Want to sanity-check your Build vs Buy decision?

If you’re scaling a RegTech platform, the decision is rarely “build or buy”.

It’s usually:

  • Build what differentiates your platform
  • Buy the regulatory data infrastructure so your team can move faster with fewer surprises

Talk to our experts about your coverage goals, integration approach, and what “current and defensible” needs to mean for your customers.