The data layer for private markets.

AI agents are only as good as the data beneath them. Before a single agent runs, Raise builds a clean, canonical data layer across your firm — every figure standardized, validated, and traced to its source. With that foundation in place, our agents deliver finished work you can trust.

Schedule a demo How we build it

Why most "AI for private markets" fails.

Pointing a chatbot at your files feels like AI, but it's built on sand. When the underlying data is fragmented, inconsistent, and unverified, the model guesses — and in front of an IC or an LP, a confident guess is worse than no answer at all.

A chatbot on your raw files

Reads whatever it's handed — ten versions of the same number, no idea which is right
Answers can't be traced to a source, so nothing is auditable
Hallucinates figures that look plausible but are wrong
Every query starts from scratch; the mess never gets cleaned up

Raise's data layer underneath

Agents verify every figure they extract against the source, so the data is accurate and reliable — not a guess
Everything runs through multiple agentic review cycles, with conflicts caught and resolved before any result is shown
Each figure carries full lineage and a confidence score, cited to its source document and cell
The layer compounds — it gets cleaner and more complete every quarter

How we build the data layer.

You don't have to replace your existing systems or run a lengthy data migration. Raise connects to the sources your firm already uses and turns them into structured, reliable data infrastructure.

1. Ingest everything

Spreadsheets, PDFs, emails, contracts, deal docs — any format, from any source across the firm. Our team ingests it all for you during implementation, and Raise keeps it flowing automatically from there.

2. Standardize to one schema

AI agents clean and normalize every data point into a single canonical model, aligned to ILPA v2.0 and AIFMD 2.0. Ten inconsistent inputs become one reconciled figure.

3. Validate and score

Conflicts are flagged for review, and every value gets a confidence score. Nothing enters the layer unchecked, and low-confidence items route to a human.

4. Link to source

Every number keeps a live link back to the exact source document and cell it came from — a complete, defensible audit trail.

What the data layer gives you.

Clean, structured data isn't a feature — it's the foundation everything else depends on. It's what lets the agents produce work you can trust, and what earns the trust of your LPs and regulators.

Answers that don't hallucinate

Because agents read from a governed, canonical dataset — not raw files — every output is grounded in verified data and cites where it came from.

Full audit trail

Trace any figure back to its source document and cell. Complete transparency for compliance, LP diligence, and your own peace of mind.

Governed and secure

Human-in-the-loop review and role-based access, with a complete audit trail on every value. Your data is never used to train external models.

Compounds with use

Every quarter on Raise, your data gets cleaner, your benchmarks sharpen, and your history deepens. The foundation grows more valuable over time.

The bottom line. Clean, standardized data is the reason our agents deliver LP-ready reports, diligence memos, and portfolio intelligence you can actually put your name on — instead of AI output you have to double-check by hand.