AI consulting · Venture capital
AI consulting for venture capital funds and fund operations
Native helps venture capital firms put AI agents into fund operations: reading portfolio and fund statements, keeping the fund's data current, drafting LP reporting and sorting deal flow. Every change to your records waits for a person's approval. At Crossover, a San Francisco venture fund, Native's agents process the statements from more than 20 underlying funds in production.
Featuring insights fromShaun Devan · Founder & CEOUpdated · 4 min read
Where AI has an impact in venture capital
Portfolio statement processing
Capital account statements and schedules of investments read in any format and turned into proposed record updates.
Fund data upkeep
Positions, valuations and ownership kept current in Airtable or your fund system, behind approval.
LP reporting
Quarterly letters and capital account figures drafted from the fund's own records.
LP questions
Requests about commitments, distributions and portfolio companies answered from the record.
Portfolio monitoring
Company updates and manager letters filed against the right company with a dated source.
Deal flow triage
Inbound decks read, matched to the thesis and logged with a short summary for the partners.
Fund-of-funds look-through
Underlying holdings from each manager's reports mapped to the companies behind them.
Audit preparation
Every figure traced to its source statement, ready for the fund's auditors.
Why fund operations is the right place to start
A venture fund's back office runs on documents it does not control. Capital account statements, schedules of investments and audited financials arrive from every underlying fund and administrator in its own format, and the layout drifts from one quarter to the next. Someone reads each one and keys the figures into the fund's records.
That work is slow, error-prone and invisible until it goes wrong in an LP report. It also follows clear rules, which makes it a strong first workflow for agents and an easy one to measure.
How a statement pipeline works
- Intake. A dedicated inbox is checked every few minutes, and each file is screened for integrity and run through OCR when needed.
- Classification and extraction. Each document is sorted by type and its figures extracted into structured financials, inside the fund's own cloud account.
- Matching. Each position is matched to the right fund and company in your records.
- Comparison. Extracted values are compared with the live record, using a threshold set from real data so rounding is never flagged as a change.
- Review and approval. A reviewer sees the source PDF beside each proposed change and approves, edits or rejects it. Only the approval step can write to the fund's records, and every write is logged.
The fund's own rules, written down
Fund data is full of edge cases a generic tool gets wrong: a SAFE that converts into a priced round, two share classes bought weeks apart, a round you track but did not join, an exit that should keep cost but carry no value. Each of these becomes a written rule the general partner signs off, and the agents follow the rulebook rather than guess.
When the GP changes a rule, the rule changes, not the code. That keeps the fund's records consistent with how the partners think about the portfolio.
Beyond statements: LP reporting and deal flow
Once the fund's data is current and trusted, the next steps are short. Agents draft the quarterly LP letter and capital account figures from it, answer LP questions from the record, and file manager updates and portfolio news against the right company with a dated source.
On the deal side, agents read inbound decks and updates, match them to your thesis and existing relationships, and keep the pipeline current, so partners spend their time on founders. The asset management page covers the research side of the same work.
Data control for funds
Fund and LP data never leaves your accounts. Extraction runs in the fund's own cloud environment with models that keep no copy, an in-dashboard assistant can explain any proposed change but has no way to write, and the production write credentials belong to the approval step alone. The code, the data and the credentials are the fund's.
Case study · Crossover
Crossover runs its fund data on agents, from statement to approved update.
Native helped Crossover, a San Francisco venture fund that invests in emerging managers and select direct companies, put its fund data on agents. In production, they read the statements from every underlying fund, keep the fund's records current, and send each change to the team for approval.
The challenge
Crossover's positions span more than 20 underlying funds plus direct investments, reported by different administrators in formats that change from quarter to quarter. Every figure was read and keyed by hand.What we built
- Agents that read every statement as it arrives, whatever the administrator or the format.
- Matching of each position to the right fund and company, with every change checked against the fund's current records.
- One review screen where the team sees each proposed update beside its source statement and approves it in a click.
The result
Statements from every underlying fund now flow into Crossover's records as they arrive, ready for approval. The team reviews instead of retyping, and every change is on record.Frequently asked questions
How are venture capital firms using AI?
Mostly in fund operations and deal flow: reading portfolio statements, keeping fund data current, drafting LP reporting and triaging inbound decks. Partners keep the investment decisions.
Can AI read fund statements and capital account statements?
Yes, across formats and administrators, including layouts that change between quarters. At Crossover, Native's agents read the statements from more than 20 underlying funds in production, across 48 formats.
Is it safe to let AI update our fund records?
Only through an approval step. Agents propose each change with its source beside it, a person approves, and only that step holds write access. Every write is logged and can be undone.
What does an AI consultant do for a VC fund?
An AI consultant maps the fund's operations, writes down the fund's own rules for its data, and builds agents that follow them inside the fund's systems. At Native the same forward-deployed engineers build and run the agents until your team takes them over.
How long does it take to automate VC fund reporting?
Crossover went from kickoff to a working end-to-end system in two weeks, and it now runs in production every quarter. Nothing writes to the fund's records without a person's approval.