Powering data platforms with structured company intelligence.
mnAi provides the data and technology layer behind modern data platforms - enabling data providers to enhance coverage, improve consistency, and deliver decision-ready outputs at scale.
The Challenge
Data & information service providers operate at scale - and are expected to deliver:
- High coverage across company populations
- Consistent and comparable data outputs
- Real-time or near real-time updates
- Reliable data for downstream applications
However, in practice, they face:
- Gaps in coverage across key attributes
- Inconsistencies across datasets and sources
- Challenges maintaining data quality at scale
- Increasing demand for new data types (e.g. ESG, classification, derived metrics)
This limits the ability to deliver consistent, scalable data products and slows the development of new, data-driven services.
As customer expectations increase, data providers are under pressure to expand coverage, improve accuracy, and introduce new datasets - while maintaining consistency across millions of records and multiple delivery channels.
To support this, data must be structured, standardised, and designed for integration - enabling it to be applied consistently across platforms, products, and customer environments.
How mnAi Supports Data Providers
An underlying data and technology layer
mnAi acts as an underlying data and technology layer, designed to integrate with and enhance existing data platforms.
Rather than replacing existing datasets, mnAi:
- Extends coverage across key attributes
- Enhances data consistency and structure
- Introduces new, derived datasets
- Supports scalable integration into platforms
The result:
This enables data providers to improve their offering without rebuilding their core systems.
What This Enables
Capabilities that transform your data offering
Expanded Data Coverage
- Fill gaps across company-level datasets
- Extend coverage across populations
- Introduce new attributes at scale
Enhanced Data Products
- Add new data domains (e.g. ESG, classification, derived metrics)
- Improve the depth of existing products
- Deliver richer insights to customers
Platform Integration
- Embed mnAi data via API or data warehouse
- Deliver consistent outputs across systems
- Power customer-facing products
Faster Product Development
- Reduce time required to build new data-driven features
- Leverage existing structured datasets
- Focus internal resources on product innovation
Core Capabilities in Practice
Data providers typically apply mnAi across several key areas
Embedded Data for Platforms
Powering data platforms with structured, integration-ready datasets.
Data Creation & Enhancement
Generating new attributes and enhancing existing datasets.
Entity & Relationship Intelligence
Providing structured, connected views of companies and individuals.
Industry Classification
Delivering accurate, activity-based classification at scale.
Why mnAi
Data providers choose mnAi because it is built for:
Scale
Billions of data points across company populations. 450+ structured variables per company.
Structure
Standardised, consistent data across datasets. Designed for system integration and platform use.
Flexibility
API, Snowflake, and flat file delivery. Integration into existing data architectures.
Complementary
Enhances existing datasets rather than replace them.
Outcome
A scalable, structured data layer that enhances data platforms - enabling providers to deliver richer, more consistent, and more valuable data products.
Speak to our team about Data & Information Services
Learn how mnAi can support your organisation.