AI-Powered Invention Disclosure Capture and Triage Workflow

Manual disclosure intake involves chasing inventors for incomplete forms, clarifying technical jargon, and manually tagging submissions—a process that can take weeks. A custom workflow uses a conversational AI agent to guide inventors through a structured Q&A, extracting key technical elements, claims language, and figures in a single session. This compresses the initial capture from days to minutes, accelerating the entire filing pipeline.

Without a systematic process, inventions documented in lab notebooks, Slack threads, or meeting notes are often lost. This workflow deploys monitoring agents to continuously scan internal R&D repositories (e.g., ELNs, Confluence, Git) for novel technical concepts, automatically generating draft disclosures for review. This transforms IP harvesting from a sporadic, recall-dependent task into a continuous operation, protecting against prior art created by your own unpublished research.

Paralegals and IP administrators spend significant time on data entry, routing, and chasing down information. Automation handles intake, populates docketing systems (e.g., Anaqua, CPA Global), assigns internal IDs, and routes submissions based on pre-configured rules (technical domain, business unit, strategic priority). This reallocates high-cost legal labor from administrative triage to high-value strategic review and prosecution.

Manual routing relies on individual judgment, leading to inconsistent prioritization. A custom workflow embeds a scoring agent that evaluates each disclosure against strategic criteria (market alignment, technical novelty, competitive landscape) and technical domain classifiers. Submissions are then queued for the appropriate IP committee, outside counsel, or technical expert with a pre-populated assessment brief, ensuring faster, more consistent decision-making.

Proving conception date and inventor contribution is critical in litigation. A manual process creates fragmented records. This workflow automatically timestamps every interaction, logs extracted technical elements, records routing decisions, and maintains a complete chain of custody from ideation to docketing. This immutable audit trail, integrated with ELM systems, strengthens legal defensibility and simplifies internal compliance.

A production build uses LangGraph or CrewAI to orchestrate specialized agents: a conversational intake bot, a document parsing agent for legacy scans, a scoring/routing agent, and an integration agent for docketing APIs. The architecture includes approval gates for legal review, exception queues for ambiguous disclosures, and observability dashboards to monitor throughput and agent performance. Integration points include MS Teams/Slack, SAP/PLM systems, and Anaqua/CPA Global APIs.

A chatbot or voice interface that guides inventors through a structured disclosure process, asking clarifying questions to extract complete technical descriptions, novel elements, and inventor contributions. This agent replaces static PDF forms, reducing incomplete submissions by 60-70% and cutting initial capture time from days to hours. It integrates with enterprise SSO and can be embedded in R&D collaboration platforms like Slack or Microsoft Teams.

Core NLP pipeline that parses the conversational transcript or uploaded documents to identify key entities: technical domains, novel components, potential claims language, and relevant prior art citations. It assigns a preliminary novelty score and technical classification (e.g., mechanical, software, chemical) using a fine-tuned model. This engine determines the initial routing path—to a specific IP attorney, external counsel queue, or a 'needs more information' hold bin.

Critical API orchestration layer that pushes the structured disclosure data—inventor info, technical summary, preliminary classification—into the enterprise legal management (ELM) or docketing system (e.g., Anaqua, CPA Global, Lecorpio). This creates a new matter record automatically, assigns docket numbers, and triggers calendar events for internal review deadlines. It eliminates dual data entry, ensuring the legal team operates from a single source of truth from day one.

Built using a framework like LangGraph or Temporal, this component manages the state of each disclosure. It routes submissions through configurable approval gates (e.g., lab head sign-off, export control check), escalates stale items, and sends reminders. It integrates with email and corporate messaging systems for notifications and can pause the workflow to collect additional data from inventors or R&D systems before proceeding to legal review.

Agents that query connected Product Lifecycle Management (PLM), Application Lifecycle Management (ALM), or Electronic Lab Notebook (ELN) systems to pull relevant context. For example, when a disclosure references 'Project Phoenix,' the connector can automatically attach the latest design files, test results, or commit history. This enriches the disclosure with supporting evidence and ensures the IP is linked directly to the R&D project that generated it, improving portfolio management.

A centralized dashboard for IP and R&D leadership showing real-time metrics: disclosure volume, average time in each queue, auto-triage accuracy, and bottleneck analysis. Every action in the workflow—from initial chat message to final docketing event—is logged with a full audit trail, which is crucial for inventorship disputes and process compliance. This component is typically built using OpenTelemetry traces fed into a observability platform like Grafana.

The primary user who interacts with the conversational intake agent (e.g., a chatbot embedded in Slack, Teams, or an internal portal). Their role is to provide raw technical details in a guided, structured format. The workflow reduces their administrative burden from hours of form-filling to minutes of conversation, ensuring disclosures are captured while the invention is fresh, which directly increases the volume and quality of submissions.

Owns the workflow's configuration, governance, and integration with docketing systems like Anaqua or CPA Global. They define the triage logic (e.g., routing rules based on technical domain, strategic priority), set approval thresholds, and manage the exception queue. Their oversight ensures the automated system aligns with legal strategy and compliance requirements, turning a manual sorting process into a managed orchestration layer.

Responsible for the technical build and ongoing health of the workflow. This includes integrating the conversational agent with internal data sources (e.g., Jira, Git, lab notebooks), implementing the orchestration logic (using frameworks like LangGraph or temporal workflows), designing the data pipeline for disclosure enrichment, and ensuring observability through logging and dashboards. Their role is to deliver a production-grade system that is reliable, scalable, and maintainable.

The human-in-the-loop for high-value or complex decisions. The workflow pre-screens and routes disclosures to them with a synthesized report containing extracted claims, prior art signals, and a preliminary novelty score. Their role shifts from manual first-pass review to strategic evaluation, focusing on the 20-30% of disclosures that require expert judgment. This improves their throughput and allows deeper engagement on high-potential filings.

Ensures secure, compliant integration with enterprise systems (e.g., Single Sign-On, data loss prevention policies, network security). They manage access controls for the workflow platform, oversee data residency for sensitive IP, and handle the deployment and monitoring of the orchestration infrastructure (often containerized on Kubernetes). Their role is critical for operational stability and meeting internal IT governance standards.

The ultimate beneficiary and sponsor. They define the strategic priorities that inform the triage routing logic (e.g., 'flag all AI-related disclosures for fast-track'). Their role is to measure the workflow's impact on key metrics: reduction in invention-to-filing cycle time, increase in disclosure submission rate, and the percentage of R&D spend yielding protected IP. They fund the build and validate the ROI.