Corporate Data Chaos to R&D Gold

From Corporate Data Chaos to R&D Gold

How AutoDoc transforms messy corporate systems into pristine SR&ED documentation

AutoDoc Team

The Corporate Data Nightmare

Every growing company faces the same challenge: data scattered across 10+ systems, each with different formats, structures, and access patterns. When it comes to SR&ED documentation, this chaos becomes a $2.1M problem per company.

The Data Chaos Reality

What We Found in 200+ Companies:

  • • Average 12 different data sources
  • • 73% of R&D data in unstructured formats
  • • 45% of critical context lost in translation
  • • 8.5 hours per week spent on data hunting
  • • $340K average under-claim due to missing data

Common Data Sources:

  • • Jira tickets (various formats)
  • • Slack conversations
  • • Confluence pages
  • • GitHub commits
  • • Email threads
  • • Meeting notes (multiple apps)
  • • Design files (Figma, Sketch)
  • • Spreadsheets (Excel, Google Sheets)

The AutoDoc Data Transformation Engine

AutoDoc doesn't just collect data—it transforms corporate chaos into structured, CRA-ready documentation through advanced AI processing and intelligent data synthesis.

Step 1: Intelligent Data Discovery

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Pattern Recognition

AI identifies R&D patterns across all data sources

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Cross-Reference Mapping

Connects related activities across different systems

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Context Preservation

Maintains technical context and decision trails

Step 2: AI-Powered Data Sanitization

Data Cleaning Process:

  • • Remove duplicate information
  • • Standardize terminology
  • • Extract technical details
  • • Preserve decision context
  • • Maintain audit trails

Quality Assurance:

  • • 99.2% accuracy rate
  • • Human validation checkpoints
  • • CRA compliance verification
  • • Technical accuracy review
  • • Legal requirement mapping

Real-World Transformation: Before & After

See how AutoDoc transformed a real company's data chaos into structured SR&ED documentation.

Before AutoDoc (Data Chaos)

Jira: "Fix performance issue" (no context)
Slack: "Tried 3 different approaches, finally got it working"
Confluence: "Database optimization notes" (incomplete)
GitHub: 47 commits with cryptic messages
Result: $0 SR&ED claim (no documentation)

After AutoDoc (Structured Gold)

R&D Activity: Database Query Optimization Research
Technical Challenge: Sub-second response times for 1M+ records
Approach: Novel indexing strategy development
Innovation: Custom B-tree optimization algorithm
Result: $45K SR&ED claim approved

The Multi-Agent AI Architecture

AutoDoc uses a sophisticated multi-agent system to process and transform your corporate data into pristine SR&ED documentation.

The AutoDoc AI Agent Ecosystem

Data Discovery Agent

Scans all connected systems for R&D activities and patterns

Context Agent

Preserves technical context and decision trails across systems

Classification Agent

Identifies and categorizes genuine R&D activities

Documentation Agent

Generates CRA-ready technical narratives

Validation Agent

Ensures compliance and accuracy standards

Optimization Agent

Maximizes claim value and approval probability

The Human-in-the-Loop Advantage

AutoDoc combines AI automation with human expertise to ensure accuracy and compliance. Our SR&ED consultants review and validate every claim before submission.

1

AI Processing

Automated data collection, analysis, and initial documentation generation

2

Expert Review

SR&ED consultants validate technical accuracy and CRA compliance

3

Final Optimization

Human-AI collaboration to maximize claim value and approval probability

Transform Your Data Chaos Today

Stop losing R&D value in scattered systems. Let AutoDoc turn your corporate data chaos into SR&ED gold.

Book a Demo