The Multi-Agent Revolution
Traditional R&D documentation relies on single-purpose tools and manual processes. AutoDoc represents the next evolution: a sophisticated multi-agent AI system that works like a team of specialized experts, each focused on a specific aspect of SR&ED documentation.
The AI Agent Ecosystem
Core Intelligence Agents:
- • Data Discovery Agent (scans 10+ systems)
- • Context Preservation Agent (maintains technical context)
- • Classification Agent (identifies R&D activities)
- • Documentation Agent (generates CRA-ready content)
- • Validation Agent (ensures compliance)
Specialized Processing Agents:
- • Technical Analysis Agent (deep code understanding)
- • Innovation Detection Agent (identifies novel approaches)
- • Timeline Agent (tracks development progression)
- • Compliance Agent (CRA requirement mapping)
- • Optimization Agent (maximizes claim value)
Deep Technical Integration
AutoDoc's agents don't just read your tools—they understand them at a deep technical level, preserving context and making intelligent connections across your entire development ecosystem.
Jira Deep Integration
What Our Agents Analyze:
- • Technical complexity scoring algorithms
- • Problem-solving methodology patterns
- • Innovation indicators and novelty detection
- • Time investment and effort analysis
- • Cross-ticket dependency mapping
- • Decision trail reconstruction
AI Processing Capabilities:
- • Natural language processing for context
- • Machine learning for pattern recognition
- • Graph neural networks for relationship mapping
- • Transformer models for technical understanding
- • Reinforcement learning for optimization
- • Ensemble methods for accuracy validation
Confluence Intelligence Processing
Document Analysis:
- • Architecture decision record parsing
- • Technical specification extraction
- • Design pattern recognition
- • Problem-solving approach analysis
- • Knowledge sharing pattern detection
Context Preservation:
- • Multi-document relationship mapping
- • Temporal context preservation
- • Technical decision trail reconstruction
- • Cross-reference validation
- • Knowledge graph construction
The 10+ System Challenge Solved
Modern R&D teams work across 10+ different systems, each with unique data formats and access patterns. AutoDoc's multi-agent system is the only solution that connects them all into a cohesive R&D narrative.
The Data Transformation Pipeline
Discovery Agent
Scans all connected systems for R&D activities
Analysis Agent
AI processes and classifies technical content
Synthesis Agent
Combines data into coherent narratives
Documentation Agent
Generates CRA-ready documentation
Human-in-the-Loop Validation
AutoDoc combines AI automation with human expertise. Our SR&ED consultants work alongside the AI agents to ensure accuracy, compliance, and maximum claim value.
AI Processing (95% Automation)
Multi-agent system handles data collection, analysis, and initial documentation
Expert Review (5% Human Touch)
SR&ED consultants validate technical accuracy and CRA compliance
Collaborative Optimization
Human-AI collaboration maximizes claim value and approval probability
The Technical Sophistication Advantage
AutoDoc's multi-agent architecture represents the cutting edge of AI technology, providing capabilities that traditional SR&ED tools simply cannot match.
Advanced AI Capabilities
- ✓High accuracy in R&D classification
- ✓Real-time context preservation across systems
- ✓Intelligent decision trail reconstruction
- ✓Automated compliance validation
- ✓Dynamic claim optimization
Business Impact
- →Significant reduction in documentation time
- →High first-time approval rate
- →Increased claim value through better documentation
- →Eliminated back-and-forth delays
- →Real-time documentation updates
Experience the Future of R&D Documentation
Join 200+ Canadian companies already using AutoDoc's multi-agent AI system to maximize their SR&ED claims.
Book a Demo