Unrivalled coverage and reliability
Starting from best-in-class private companies, deals and financials dataset.
The definitive private company dataset and virtual analyst
Private company data is fragmented across providers, with no single source of truth. CapData unifies it into one reconciled, AI-ready foundation.
How CapData works
From raw sources to one trusted dataset
Raw data sources
Orbis
FactSet
News
Web Select
Normalize
Reconcile
Enrich
Trusted dataset
Consume our data
PlatformWeb Application
AI AssistantAsk Anything
ExcelExports
APIREST / GraphQL</>
Your SystemsCRM, DWH, Models
Scroll the diagram sideways →
Why CapData
What sets CapData apart
AI-based sector intelligence
Proprietary taxonomy, AI-powered sector allocation and intelligent search surface the companies that truly fit.
One reconciled dataset
Companies (financials & valuations), deals, advisors, GPs, sectors, news and people. All linked.
Cleansing done upfront
No manual cleanup. Your team starts with structured, trusted data.
Every value auditable
Trace every figure back to its calculation path and original source.
Targeted enrichments
Where data quality is low, we systematically identify and enrich records with better data points.
Coverage
Integration of Moody's best-in-class private companies dataset
The broadest source of truth with the most reliable information on the market.
600M+Private companies tracked
700M+Financial records
200M+Ownership records
400M+Company directors
Coverage figures are directional and rounded.
How It Gets Clean
We reconcile it before you ever run a query
Noise removal
~95% of raw entities are subsidiaries or assets, not operating companies. Removed before they clutter search.
Normalization
Input errors corrected. Categories aligned across every source.
Reconciliation
Duplicates removed within a source, and across sources that name a company differently.
Ambiguous datapoints dismissal
Our models score the data, and remove dubious outliers.
Built For AI
An LLM is only as good as the data underneath it
Old Way
Raw, unreconciled data
- Confusing for LLMs to reason over
- Hallucinated or ungrounded answers
- Same question, different answer twice
CapData
Trusted, reconciled dataset
- Query a reconciled, enriched fact base directly
- Grounded answers, consistent every time
- Native to your AI via MCP and Skills
One Dataset, Every Channel
Consume it however fits your stack
Analytics platform
Sector dashboards, league tables and deal screens, built into the CapData platform.
AI integrations
Use CapData's built-in AI assistant, or connect your own AI agents using our MCP- and Skills-native stack.
Your systems
Bulk files via S3, a GraphQL Lookup API, or a deployment matched to your stack.
About CapData
Built to power private market intelligence
Private capital markets run on fragmented, manual data. CapData was founded by a former partner at a large-cap private equity firm to fix that.
We combine modern data engineering and AI to turn fragmented information into one trusted foundation for investment teams, analytics platforms and intelligent agents — so leading institutions uncover better opportunities and build conviction faster.
- Headquarters
- London, UK
- Coverage
- Companies • Deals • Sponsors • Funds • Advisors • Sectors • People • News
- Mission
- Better Decisions Through Better Data
Leadership Team
Idriss started his career at McKinsey & Co. in Paris where he focused on Financial Institutions and Industrials. He later joined BC Partners, a large cap Private Equity firm where he stayed 12 years (of which 3 as partner) in Paris, New York and London. While at BC, Idriss was part of teams investing in 6 companies for a combined EV of c. $7bn. He was an active member of 4 boards across numerous sectors (retail, industrials, professional services and healthcare). Idriss holds an Msc. in Applied Mathematics from Ecole Centrale Paris.
Peter began his career in academia, working on machine learning models for online recommendations. He later transitioned to the industry, where he held various data architecture and engineering roles, including at several startups (e.g. Prezi, Attest) or at quantitative financial research firm G-Research. Peter holds a BSc. in Mathematics and an MSc. in Computer Science from the Budapest University of Technology and Economics. His Erdos number is 3.
Andreas worked for 13 years at Accenture as a management consultant. In his role, he served the leadership teams of global Financial Services organizations in a number of engagements in the UK and Continental Europe. He led teams using a data-centric approach to address client challenges including market entry, growth strategy, activity portfolio rationalization, as well as operational and service quality improvements. Andreas holds a Master of Business Administration at the Stockholm University.
Kostya is a highly experienced data scientist and software developer with a background in theoretical physics. He spent over a decade working at the Large Hadron Collider at CERN and on the particle physics experiments performed on the International Space Station. He analyzed vast amounts of experimental data and contributed to groundbreaking scientific discoveries - including that of the Higgs Boson. Kostya later transitioned to data-focused software development, bringing his analytical skills and expertise to elite consultancy Toptal, where he worked on a number of high-profile projects. He holds a PhD in Theoretical Physics from the University of Trento.