ILPA-Native Data Model
The FundCore Data Model
An ILPA-native schema for private fund data. Designed to produce ILPA-quality metrics, capital account statements, and LP reporting out of the box — not as an afterthought bolted on at quarter-end.
Every fund is a little different. Different waterfall. Different side letter structure. Different way the controller has been tracking commitments. Most data models cannot deal with that cleanly. Ours was built specifically for it, with ILPA reporting standards baked into the structure from day one.
What the model covers
Fund-level entities
- →Funds (vintage, strategy, size, structure)
- →Partnership terms (carry, hurdle, catch-up, fees, expenses)
- →Side letters (per-LP terms and exceptions)
- →Closings (initial, subsequent, final)
Investor-level entities
- →Investors / LPs (legal entities, contact info, tax structure)
- →Commitments
- →ILPA-compliant capital accounts
- →Capital calls, distributions, contributions
Portfolio-level entities
- →Portfolio companies
- →Investments (initial, follow-on)
- →Valuations (with methodology)
- →Realizations and write-downs
Operational entities
- →General ledger accounts and chart of accounts
- →Transactions (with full provenance)
- →Allocations (per investor, per fund)
- →Fees and expenses
Document entities
- →Subscription documents
- →Partnership agreements
- →Capital call notices, distribution notices, LP letters
- →Audit support, K-1 packets
How the model powers all four solutions
Powering Fund Data Foundation
A Foundation engagement IS mapping your data into the model. The Subscription IS keeping it mapped as new data lands.
Powering Fund-Native AI Agents
Our agents are built ON TOP of the model. Standard query patterns. Standard relationships. Standard semantics. That's why builds go fast.
Powering Technical Partner
Your retainer keeps the model evolving. New data sources, schema updates, agent improvements — all continuous, all on the same foundation.
Powering Managed Fund Admin
Quarter-end close, NAV packs, LP letters — all assemble from the model. Same structure whether we built it from your incumbent admin's tables or you're on FundCore admin natively.
What you actually get from it
- →ILPA-quality reporting out of the box — TVPI, DPI, RVPI, net IRR, capital account statements, fee disclosures — all computed from the model natively. Your LPs get institutional-quality reporting from day one, not quarter-end scramble output.
- →AI agents that actually work — Your AI doesn't have to guess what a PCAP is or how partnership terms relate to carry. The model encodes the relationships, so agents reason across your data instead of fumbling with it.
- →Outputs your auditors can verify — Every transformation, every cleanup decision, every derived field traces back to source. Quarter-end stops being a faith exercise.
- →One model across your whole stack — Same data structure whether your books are in an incumbent admin or running on FundCore. Reports, agents, and dashboards all speak the same language.
Anyone can clean data. Only we have the FundCore Data Model.
Model documentation is coming
A full public documentation surface for the FundCore Data Model, entity reference, relationships, methodology, is in development. For now, the best way to see it in action is to scope a Foundation engagement.