Sharper sourcing and diligence
Clean company, ownership and transaction data for origination, screening and portfolio monitoring.
For private markets, consulting, research and executive search
One trusted feedinstead of ten messy ones
Clean, connected, traceable data for private markets firms, consultants, researchers and headhunters, ready to use the day it arrives.
Your sources today41 records
1
ok
2
ok
3
alias → merged
4
ok
5
ok
6
format change → re-read
Private equity firm
ready to use
Northgate Ridge Partners
dq:firm:N4R8TB
Portfolio
11 current · 7 realised [1·2·6]
Latest exit
Corvel Systems · 2025 [3]
Portfolio management
38 executives [4]
Fund team
14 · 6 departed [2·5]
Sources
on every field [1-6]
6 sources · 41 records in · 1 trusted record outIllustrative example
The problem
The real work starts late.After the cleaning is done.
Your team spends hours reconciling inconsistent sources, chasing duplicates and checking whether numbers can be trusted, before any real work starts.
DataQrata does that work once, properly, and keeps doing it. You get one feed you can rely on, with every figure traceable to where it came from.
Who it's for
Built for teams that live on data.And can't afford to doubt it.
How it works
Five steps between messy sourcesand data you can use.
-
Source
We gather data from licensed providers, public registries and the web, and only use what we have the right to use.
Under the hood: managed connectors and crawlers, licence and terms tracking at source level, change detection for updates.
-
Capture
Everything is stored exactly as received, so nothing is lost and any figure can be checked against its original.
Under the hood: immutable, append-only raw layer on open table formats (Apache Iceberg), full history and point-in-time recall.
-
Clean and connect
We standardise formats, remove duplicates, tag every record consistently and resolve it to the correct company, person or asset, so "Acme Ltd" and "ACME Limited" become one.
Under the hood: schema enforcement, a semantic layer with a shared taxonomy of sectors, geographies and entity types, entity resolution against global identifiers (LEI, company registry numbers), golden-record survivorship rules.
-
Curate and assure
Clean data is shaped into finished datasets built for a specific use, each tested before release.
Under the hood: versioned data products with data contracts, automated quality tests on accuracy, completeness and timeliness, end-to-end lineage.
-
Deliver
You receive data the way your team already works: a spreadsheet-friendly file, a live feed into your systems, or direct access for AI tools.
Under the hood: REST API, zero-copy sharing to Snowflake and Databricks, scheduled bulk delivery, MCP server for AI agents, per-client entitlements and usage metering.
An example
A private equity firm.Every field traceable.
Its portfolio first, current and realised, then the management teams running each company, then the fund team, then what press and social media are saying. Each value shows its source and when it was last checked.
Delivered into Excel, your CRM, your data platform or your AI tools.
Every figure traceable
Click through from any number to the source it came from, and when it was checked.
Clear promises
Each dataset comes with a data contract: what it covers, how fresh it is and the quality you can expect.
Where you already work
Delivered into Excel, your CRM, your data platform or your AI tools.
Works with
- Excel
- Affinity
- DealCloud
- Salesforce
- HubSpot
- Microsoft Dynamics 365
- Power BI
- Tableau
- Snowflake
- Databricks
- Microsoft Fabric
- Claude
- ChatGPT
Permissioned access with full audit logs, encryption throughout, and source and licence tracked on every field. SOC 2 and ISO 27001 in preparation.
See it withyour own data needs.
Tell us what your team works on. We'll show you a live demo built around it, or send you a sample dataset.
hello@dataqrata.com
Selling data rather than buying it? DataQrata for data providers