Automation Workflow for Software Code Scans and Copyright/Patent Eligibility

This specialized agent clones and parses code from GitHub, GitLab, or Bitbucket, building an Abstract Syntax Tree (AST) to identify novel algorithms, unique architectural patterns, and proprietary UI components. It filters out boilerplate and common libraries, flagging only code segments with high novelty scores for downstream review. Integration with CI/CD pipelines ensures scans are triggered on every major commit or pull request.

A compliance-focused agent cross-references all imported libraries and code snippets against SPDX license databases and internal policies. It detects copyleft (GPL) contamination, ambiguous licensing, and unattributed code, generating a risk report that blocks the IP process until cleared. This prevents invalidating patent claims or exposing the company to litigation before filing.

This orchestrator manages a multi-agent search across USPTO, EPO, WIPO, and academic databases (arXiv, IEEE) using semantic search on the flagged code's functional description. It synthesizes results into a novelty confidence score and an evidence pack, providing a defensible basis for the patentability decision. The architecture uses LangGraph for state management across API calls and retrieval steps.

Upon approval, this agent transforms the technical code analysis and novelty report into a structured first-draft invention disclosure. It uses retrieval-augmented generation (RAG) to pull relevant boilerplate from past filings and drafts initial independent and dependent claims focused on the novel technical effect. Outputs are formatted for direct import into docketing systems like Anaqua or CPA Global.

A critical control layer where flagged inventions and draft materials are routed to the appropriate stakeholders—engineering lead, IP counsel, R&D manager—via Slack, Teams, or a dedicated dashboard. It manages review queues, collects feedback, and requires explicit approvals before proceeding to filing. The system logs all decisions and rationale for audit and chain-of-custody requirements.

The workflow's backbone, built with message queues (e.g., RabbitMQ) and APIs, connects the agents to source systems (GitHub, Jira), IP management software, and legal ops platforms. A centralized observability dashboard tracks pipeline health, metrics like 'inventions captured per sprint' and 'time-to-draft,' and alerts on failures or bottlenecks, ensuring the workflow is a reliable production system.

Gains a defensible innovation moat by systematically converting R&D output into protected IP. The workflow automates the discovery of novel algorithms, architectures, and UI patterns buried in Git history, ensuring valuable inventions are captured before they become open-source contributions or competitor prior art. This directly protects R&D investment and supports valuation during funding rounds or M&A.

Embeds IP governance into the SDLC without slowing velocity. The workflow integrates with GitHub, GitLab, or Bitbucket via webhooks, triggering automated scans on PR merges or release tags. It parses ASTs to identify novel functions and checks for inadvertent open-source license contamination, routing findings to legal while keeping developers focused on code. This creates a proactive IP hygiene layer within existing CI/CD pipelines.

Shifts from administrative bottleneck to strategic advisor. The workflow automates the initial heavy lifting: scanning repositories, generating preliminary novelty assessments against patent databases, and drafting structured invention disclosures with extracted code snippets. This reduces the time spent chasing engineers for details by 70%, allowing legal to focus on high-value claim strategy and prosecution.

Receives a data-driven map of patentable features within their product portfolio. The workflow provides dashboards showing IP coverage gaps against the product roadmap and competitor features. This enables proactive decisions to file, publish defensively, or open-source, turning IP into a strategic product planning tool rather than a post-development legal formality.

Builds a multi-agent system orchestrating code parsing, semantic search, and legal drafting. Core components include: Code Ingestion Agents (webhooks, repo crawlers), AST Analysis Engine (tree-sitter, custom parsers), Novelty Assessment Agent (vector search against USPTO/Google Patents embeddings), Disclosure Assembly Agent (LLM orchestration with legal templates), and Integration Layer (REST APIs to docketing systems like Anaqua or legal CMS). Governance is enforced via human-in-the-loop approval gates before any filing action.

Quantifies the shift from cost center to asset generator. Direct Cost Avoidance: Prevents loss of high-value IP (often worth millions in valuation or licensing). Operational Efficiency: Reduces patent preparation costs by 30-50% by automating discovery and initial drafting. Risk Mitigation: Systematically flags license compliance issues early, avoiding costly remediation or litigation. Velocity: Shortens the invention-to-filing cycle from months to weeks, securing priority dates faster in fast-moving tech domains.