Reuben AI

    Due Diligence Automation for Private Capital

    An AI-native diligence workflow that collects documents, surfaces risk, and drafts IC outputs, with every claim source-attributed and every step logged.

    Due diligence is the most labour-intensive part of any deal. Document collection eats weeks. Analysis is repetitive. Findings get scattered across tools. By the time IC sees the memo, half the analytical context is in a partner's head and half in a Slack thread.

    Reuben AI automates the entire diligence process: structured document collection, intelligent parsing, multi-dimensional analysis, risk surfacing, and IC-ready output, all within a single auditable system.

    The Automated Due Diligence Process

    Step 1: Structured request generation. Standard diligence checklists generate automatically based on deal type. The Founder Portal becomes the request and upload interface, no more email chasing.

    Step 2: Document parsing and indexing. Pitch decks, financials, contracts, cap tables, and legal documents are parsed automatically. Structured data flows into the analytical layer.

    Step 3: Multi-dimensional analysis. Financial, operational, legal, market, and team dimensions analysed in parallel. Confidence-scored findings with citations.

    Step 4: Risk surfacing. Red flags surface with severity scoring. Critical risks reach the deal lead within hours, not weeks.

    Step 5: IC memo generation. Findings flow directly into the memo with full evidence attribution. The committee gets a defensible artefact, not an unsourced summary.

    Due Diligence Automation Best Practices

    1. Source-tier every claim

    Self-reported data is a claim, not a fact. The platform tags every data point as self-reported, verified, or triangulated. This eliminates the most common diligence failure mode: confusing what a founder said with what is independently confirmed.

    2. Run analysis in parallel, not sequence

    Financial, legal, operational, market, and team dimensions analyse simultaneously. Critical risks surface in days, not after sequential workstreams complete in week 3.

    3. Keep humans in the loop on judgment

    Automation handles extraction, structuring, and surfacing. Humans handle judgment. Every AI-generated finding is reviewable with source links, so analysts spend their time deciding, not assembling.

    4. Build the audit trail as you go

    Provenance is captured automatically. When an LP, regulator, or auditor asks how you got to a decision, the trail is already there.

    5. Connect diligence to portfolio monitoring

    Diligence findings become portfolio monitoring baselines. When the deal closes, the company moves into monitoring with full historical context, not a clean slate.

    See the Due Diligence Automation Interface

    Book a walkthrough and see automated diligence end to end.

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