RegGenome Launches GenAI-Powered Regulatory Repository Service

A compliance risk study conducted by Accenture reveals that while 93% of compliance leaders believe new technologies like AI simplify compliance, 90% expect compliance costs to increase by up to 30% over the next two years.

This is due to manual, labour-intensive, and time-consuming approaches to regulatory workflows. Despite organisations dedicating substantial resources to stay on top of regulations and manage risk, the rapid pace of regulatory change and continuous expansion of firms' needs have magnified these challenges, making traditional approaches increasingly unsustainable. The introduction of new regulatory technologies is only as good as the data that powers them.

RegGenome's GenAI-Optimised Regulatory Repository Service offers a solution.

By leveraging deep learning technology, the Cambridge-based regulatory data provider offers a jurisdiction-agnostic repository of rich, descriptive, and inferential metadata, optimised for GenAI algorithms. This metadata enables applications and AI solutions to identify, interrogate, present, and manage pertinent regulations.

"Our GenAI-optimised data is vital for any firm investing in modernising its data infrastructure and adopting AI. As a data-only provider, we can facilitate the creation of a central regulatory data set that can feed multiple internal use cases. By adopting our data, organisations are well-positioned to leverage the transformative potential of AI." – Chief Operating Officer, Mark Johnston

Using a universal information structure to organise and standardise regulations, RegGenome's approach operationalises documentation from any authority, in any language, enabling efficient and accurate access to relevant regulations.

These information structures are built on provenance and anchored to regulatory standards reviewed by regulatory experts convened by the University of Cambridge. This ensures that the metadata used by RegGenome is linked to the original source documents, delivering assurance of its integrity, reliability, and relevancy.

Optimised for GenAI, RegGenome's data empowers organisations to build standards-based solutions that harness foundational LLMs. This enables reliable GenAI solutions to manage regulatory changes, assess policy impacts, retrieve specific information, address queries, and generate document summaries. The capabilities of LLMs are enhanced through retrieval-augmented generation, delivering more accurate, efficient, and sustainable regulatory analysis.

With these advantages, organisations can perform granular searches to surface only relevant regulations quickly. Enhanced navigation via custom alerts allows users to find pertinent documents and receive timely updates. They can also identify common regulatory obligations across jurisdictions and publishers, routing regulations to teams based on relevance.

"With flexible delivery methods, our data integrates into any existing application or tool, maintaining continuity with current business operations. We meet you where you are, and that is the type of freedom customers get from a pure data-only provider." – Head of Product, Jonny Scurr

As AI adoption accelerates, integrating RegGenome's GenAI-Optimised data is crucial for firms modernising their digital infrastructure. This foundational dataset enhances existing systems and prepares organisations for the evolving regulatory environment.

Discover how RegGenome's robust, high-quality data can transform your regulatory solutions and drive your organisation's digital transformation. Visit www.reg-genome.com to schedule a meeting with our team of experts.

Media Contact:
Mary Macauley
Communications Manager
RegGenome
[email protected] 

About RegGenome:
RegGenome is a leader in the field of computational regulation, changing how the world produces and consumes regulatory information. As a regulatory data provider, we process the world's regulation using AI to transform what is human-readable into machine-readable and machine-consumable data. Our data is processed according to information structures developed and reviewed with regulatory experts and anchored to regulatory standards in conjunction with the University of Cambridge, Regulatory Genome Project. 

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