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Investor-Grade Audit Pack Generator

Author: PlanExe Team
Date: 2026-02-11
Status: Proposal
Audience: Developers, Investment Analysts

Overview

The Investor-Grade Audit Pack Generator automates the final mile of deal preparation. It compiles verified evidence, financial models, risk registers, and governance logs into a standardized, cryptographically-signed artifact (PDF/HTML) suitable for institutional due diligence.

Instead of a scattered collection of Google Docs and Excel sheets, the Audit Pack is a single source of truth.

Key Features

  1. Redaction Engine: Automatically hides sensitive data (e.g., specific salaries, trade secrets) based on the recipient's clearance level.
  2. Versioning: "Snapshot" a plan at a specific point in time (e.g., "Series A Pack - v1.0").
  3. Digital Signature: Signs the pack to prove it hasn't been tampered with since generation.

System Architecture

1. Data Aggregation

The generator pulls data from multiple internal systems: - Plan Content: The narrative text. - Evidence Ledger: The verification status of claims. - Financial Engine: The 5-year pro-forma model. - Risk Register: The Monte Carlo simulation results.

2. Redaction Layer

Before generation, the RedactionEngine filters the data. - Tags: Fields are tagged as public, investor_only, or internal_confidential. - Roles: Recipients are assigned roles (e.g., analyst, partner). - Logic: If role.clearance < field.sensitivity, the field is replaced with [REDACTED].

3. Artifact Generation

  • HTML: Renders a responsive, interactive report using Jinja2 templates.
  • PDF: Converts the HTML to a high-fidelity PDF using WeasyPrint or similar.
  • ZIP: Bundles the PDF with raw data files (CSV, JSON) for analysts who want to run their own models.

Output Schema (JSON)

The core data structure passed to the renderer:

{
  "pack_id": "pack_2026_02_11_abc",
  "plan_id": "plan_123",
  "generated_at": "2026-02-11T16:00:00Z",
  "recipient": "Sequoia Capital",
  "clearance_level": "investor_only",
  "sections": [
    {
      "title": "Executive Summary",
      "content": "..."
    },
    {
      "title": "Financial Model",
      "data": {
        "revenue_y1": 1000000,
        "revenue_y2": 5000000,
        "ebitda_margin": "[REDACTED]" 
      }
    }
  ],
  "signature": "sha256:..."
}

Redaction Logic

We use a simplistic but robust tagging system.

Tag Visibility Example
public Everyone Product description, Market size
investor_only NDA Signed High-level financials, Roadmap
internal_confidential Founders Cap table details, Employee salaries

Algorithm: 

def redact(data: dict, clearance: str) -> dict:
    if clearance == 'internal_confidential':
        return data  # Show everything

    sanitized = {}
    for key, value in data.items():
        tag = get_tag(key)
        if can_view(clearance, tag):
            sanitized[key] = value
        else:
            sanitized[key] = "[REDACTED]"
    return sanitized

API Reference

POST /api/audit/generate

Create a new audit pack.

Request: 

{
  "plan_id": "plan_123",
  "recipient_name": "Acme VC",
  "clearance_level": "investor_only",
  "format": "pdf" 
}

Response: 

{
  "pack_id": "pack_456",
  "download_url": "https://planexe.org/api/audit/download/pack_456.pdf",
  "expires_at": "2026-02-18T16:00:00Z"
}

GET /api/audit/verify/{signature}

Verify the integrity of a pack.

Response: 

{
  "valid": true,
  "generated_at": "2026-02-11",
  "plan_hash": "sha256:..."
}

Future Enhancements

  1. Watermarking: Dynamic watermarks with the recipient's email on every page of the PDF.
  2. Data Room Integration: Auto-upload to Carta, DocSend, or specialized VDRs.
  3. Interactive Models: Embed "Live Excel" components in the HTML version, allowing investors to tweak assumptions (within bounds).

Detailed Implementation Plan

Phase A — Artifact Contract and Templates (2 weeks)

  1. Define canonical pack schema with required sections:
  2. executive summary
  3. evidence ledger snapshot
  4. financial model summaries
  5. risk and scenario outcomes

  6. governance and decision logs

  7. Build template system (HTML + PDF) with strict section ordering.

  8. Add pack versioning semantics (vMajor.Minor.Patch).

Phase B — Data Aggregation Layer (2–3 weeks)

  1. Implement aggregation service pulling from:
  2. plan artifacts
  3. evidence ledger
  4. finance modules

  5. risk simulation outputs

  6. Add data completeness checks:

  7. missing required section blocks pack generation

  8. partial data surfaced with explicit caveats

  9. Capture source hashes for every included section.

Phase C — Redaction + Access Control (2 weeks)

  1. Build role-based redaction policy engine.
  2. Support recipient-specific variants with immutable redaction logs.
  3. Add expiration and revocation controls for downloadable packs.

Phase D — Signatures + Delivery (2 weeks)

  1. Generate cryptographic pack digest and signature metadata.
  2. Add verification endpoint for external auditors.
  3. Integrate delivery channels:
  4. direct download links
  5. optional data-room push adapters

Pack quality gate

Before marking pack as investor-ready: - required sections complete - evidence coverage threshold met - financial model freshness within SLA - risk section generated from latest simulation run

Data model additions

  • audit_packs (pack_id, plan_id, version, status, signature_hash)
  • audit_pack_sections (pack_id, section_name, source_hash, completeness)
  • audit_pack_access (pack_id, recipient, clearance, expires_at)

Operational safeguards

  • tamper-evident storage of generated artifacts
  • watermarking for leak attribution
  • regeneration lock to prevent stale concurrent pack versions

Validation checklist

  • deterministic rendering from same inputs
  • redaction correctness by role
  • signature verification pass/fail tests
  • section completeness gate enforcement
  • external usability testing with investor analysts