Automations
This pillar focuses on innovation workflows that scan internal R&D signals, compare them against external patent registries, and prepare draft filing materials before valuable IP is lost. Pages should show how a custom workflow can shorten invention capture cycles, reduce missed filing opportunities, and integrate semantic search with legal and R&D operations.
This foundational workflow automates the end-to-end process from scanning internal R&D signals and lab notes to preparing draft patent applications. It reduces the invention-to-filing cycle from months to weeks by orchestrating semantic search across patent databases, novelty assessment, and automated drafting, integrating directly with R&D and legal management systems to prevent valuable IP from being overlooked or delayed.
A custom workflow that deploys agents to continuously monitor internal repositories, lab notebooks, and collaboration tools for novel technical concepts, automatically flagging potential inventions for review. This transforms sporadic invention harvesting into a systematic process, capturing IP earlier and reducing reliance on manual scientist recall, with architecture built on document parsing, vector search, and integration with PLM/ALM systems.
This workflow automates the labor-intensive prior art search by deploying specialized agents to query global patent databases, scientific literature, and technical forums, then synthesizing results into a novelty score and evidence report. It cuts search time from days to hours, improves assessment consistency, and provides a defensible audit trail for patentability decisions, built on orchestrated API calls to Derwent, USPTO, and semantic similarity models.
Automates the intake and initial evaluation of invention disclosures through a conversational interface that guides inventors, extracts key technical elements, and routes submissions based on technical domain and strategic priority. This reduces administrative burden on R&D and legal teams, accelerates triage, and ensures no disclosure languishes, with implementation involving chatbot agents, form automation, and integration with docketing systems like Anaqua or CPA Global.
A custom workflow that systematically mines years of unstructured research data—PDFs, presentations, code comments—to surface forgotten or latent inventions that never became formal disclosures. This recovers hidden IP value and protects against prior art created by one's own publications, using LLM-powered document understanding and entity recognition pipelines integrated with knowledge graphs and data lakes.
Automates the monitoring of competitor patent filings, litigation, and portfolio changes, delivering synthesized alerts and strategic briefs. This replaces manual, periodic reviews with a continuous intelligence operation, enabling proactive strategy adjustments and freedom-to-operate analysis, built on scheduled patent data API ingestion, NLP for trend detection, and dashboard integrations for IP and business teams.
This workflow automates the initial FTO screening for new products or features by mapping product claims against live patent databases and generating a risk heatmap. It provides rapid, preliminary go/no-go guidance to R&D and product teams, reducing legal consultation cycles and potential infringement risk early in development, with architecture combining product requirement documents, claim parsing, and semantic search agents.
Automates the creation of first-draft patent specifications from technical disclosures, including background, summary, detailed description, and initial claims. This drastically reduces drafting time and cost per application, allowing attorneys to focus on high-value strategic refinement, using a multi-agent system that structures technical input, retrieves relevant boilerplate, and generates coherent prose with legal formatting.
A specialized workflow where AI agents propose independent and dependent claim sets based on the invention's core novelty, then iteratively refine them through simulated examiner objections and inventor feedback loops. This improves claim quality and breadth, shortens prosecution, and is built as a collaborative tool integrating with drafting platforms and version control systems.
Automates the conversion of engineering CAD files, circuit diagrams, or chemical structures into patent-ready figures and corresponding detailed descriptions. This eliminates manual redrawing and drafting labor, ensuring consistency and accuracy, using computer vision models, diagram interpretation, and integration with tools like AutoCAD, Altium, or ChemDraw.
This workflow automates the assembly of Information Disclosure Statements (IDS), Application Data Sheets (ADS), and other formal filing documents by extracting data from internal systems and prior art searches. It reduces administrative errors and preparation time for paralegals, ensuring compliance with USPTO and other jurisdiction formats, through integration with docketing software and document assembly APIs.
Automates the first-pass response to common, non-substantive office actions (e.g., formality objections, minor claim clarification) by retrieving application history, suggesting amendments, and drafting response letters. This frees up attorney time for complex arguments, speeding up prosecution, and is built as a rules-based agent that integrates with the USPTO's PAIR system and document management.
Orchestrates the drafting, filing, and deadline management for global patent families across multiple jurisdictions. This workflow ensures consistency in claims, manages translation requirements, and tracks critical dates (PCT, national phase) automatically, reducing the risk of abandonment and operational overhead for large portfolios, with deep integration into ELM and docketing systems.
Automates the analysis of an existing patent portfolio against technology roadmaps and competitor landscapes to identify coverage gaps and white space. This provides data-driven input for R&D investment and filing strategy, moving from annual manual reviews to continuous strategic assessment, using knowledge graphs, clustering algorithms, and business intelligence tool integrations.
This workflow automates the analysis of patent value, market relevance, and cost to provide data-driven recommendations on whether to pay maintenance fees or abandon assets. It optimizes portfolio cost by systematically pruning low-value patents, replacing spreadsheets and guesswork with a rules-and-ML engine integrated with financial and market data sources.
Automates the intensive IP diligence process for mergers and acquisitions by rapidly analyzing target portfolios for strength, freedom-to-operate risks, encumbrances, and alignment with strategic goals. This accelerates deal timelines and improves risk assessment, using agents to pull data from multiple registries, analyze claim charts, and generate summary reports for legal and executive review.
A workflow that continuously scans the market for companies whose products or R&D directions align with under-utilized patents in a portfolio, identifying potential licensing or assertion targets. This turns a passive asset into a revenue-generating operation, using NLP to match patent claims to product descriptions and integrating with CRM systems for outreach tracking.
This workflow creates a bi-directional link between Product Lifecycle Management (PLM) or Application Lifecycle Management (ALM) systems and the IP process, automatically flagging new product features for patent review and tagging existing IP to specific product components. It ensures IP strategy is embedded in development, built on APIs for systems like Siemens Teamcenter, PTC Windchill, or Jira.
Automates the flow of IP docketing data, outside counsel invoices, and matter status between custom AI discovery tools and enterprise legal management systems like Onit, Mitratech, or LawVu. This eliminates dual data entry, ensures matter management accuracy, and provides a single source of truth for legal ops, using structured data pipelines and validation agents.
Links IP generation and cost tracking directly to R&D projects in ERP (SAP, Oracle) and project management tools (Asana, Smartsheet). This workflow automates the attribution of IP costs to specific projects, provides visibility into the IP yield of R&D spend, and triggers invention harvesting at project milestones, enabling better resource allocation and ROI calculation.
Fully automates the docketing of critical dates from patent office communications, filing receipts, and other correspondence into the IP management system. This eliminates manual entry errors and missed deadlines, using OCR, NLP for date extraction, and robotic process automation (RPA) to interface with legacy docketing software, ensuring high-reliability calendar management.
A domain-specific workflow for pharma that analyzes novel chemical entities, formulations, and methods of treatment against compound databases and patent landscapes to assess patentability and design-around strategies. It accelerates early-stage IP decisions in drug discovery, using cheminformatics models, structure-activity relationship (SAR) analysis, and integration with ELN systems.
Automates the analysis of code repositories to identify novel algorithms, architectures, and user interfaces that may be eligible for patent or copyright protection, while also checking for open-source license contamination. This brings systematic IP review to agile development, using code parsing, abstract syntax tree analysis, and integration with GitHub/GitLab.
This workflow automates the identification of patentable innovations within semiconductor design files (e.g., RTL, GDSII), such as novel circuit layouts, power management techniques, or fabrication processes. It protects high-value chip IP that is often buried in complex design data, using EDA tool integrations and agents trained on semiconductor patent claims.
Specialized for materials science and specialty chemicals, this workflow analyzes formulation data and experimental results to automatically draft robust composition-of-matter claims, predict likely examiner objections based on similar patents, and suggest broadening or narrowing strategies. It integrates with Laboratory Information Management Systems (LIMS) and chemical databases.
Automates the IP process for biotech by scanning genomic sequence data, assay results, and research papers to identify patentable sequences (DNA, RNA, protein) and novel therapeutic methods of use. It handles the complexity of biological data and prior art, integrating with bioinformatics platforms and sequence databases like GenBank.
Navigates the complex landscape of business method and software patents in finance by automating the analysis of trading algorithms, risk models, and payment systems for patent-eligible subject matter and novelty. This workflow helps draft claims that are more likely to withstand scrutiny, using agents trained on USPTO guidance and historical FinTech patent prosecution.
This workflow automates the IP review of medical device prototypes by analyzing CAD models, engineering requirements, and testing data to identify patentable mechanical, electrical, and software features. It accelerates IP strategy for fast-moving device development, integrating with QMS systems and regulatory submission pipelines to ensure comprehensive protection.
A comprehensive workflow for tech transfer offices that automates invention disclosure intake from faculty, assesses commercial potential, performs preliminary patent searches, and manages the marketing of technologies to potential licensees. It increases throughput and deal flow for under-resourced offices, using orchestration across CRM, patent databases, and disclosure management systems.
Automates the IP due diligence and landscape analysis for potential startup investments by a corporate venture arm. This workflow rapidly assesses the strength, freedom-to-operate, and strategic fit of a target's IP portfolio, enabling faster, more informed investment decisions, with integration into deal flow and portfolio management platforms.
This workflow assists in the complex process of developing Standard Essential Patents by analyzing technical standard specifications (e.g., 3GPP, IEEE) and mapping them to existing or draft patent claims to identify potential SEPs and draft claims accordingly. It reduces the manual, expert-intensive labor involved in SEP declaration programs.
Automates the process of creating and submitting defensive publications to prevent competitors from patenting in a technology area. This workflow identifies technical developments suitable for defensive publishing, drafts the technical disclosure, and manages submission to services like IP.com, providing a low-cost IP strategy tool integrated with R&D pipelines.
Automates the systematic identification of potential trade secrets within R&D, manufacturing, and business processes, then guides the creation of legally-defensible documentation and access controls. This proactive workflow helps protect valuable know-how that isn't patentable, using process mining and interview bots to capture tacit knowledge.
Automates the end-to-end process for design patents: extracting ornamental designs from 3D CAD or product renderings, generating the required line drawings and surface shading, and drafting the specification. This makes design protection fast and cost-effective for consumer products, automotive, and electronics, with direct integration into industrial design software.
This workflow automates the complex, often contentious process of determining inventorship by analyzing contribution records from Git commits, lab notebooks, and meeting notes, then proposing an inventorship list and logging any disputes for legal review. It reduces administrative burden and legal risk, using contribution tracking and evidence compilation agents.
Automates the verification that inventors have no conflicting obligations to prior employers and secures signed assignment agreements. This workflow integrates with HR systems, sends automated reminders, and uses NLP to review employment contracts, ensuring clean title to patents and reducing pre-filing delays and legal exposure.
Creates an immutable, automated audit trail for the entire IP lifecycle, from conception through filing, prosecution, and licensing. This is critical for litigation readiness and internal compliance, using blockchain or secure ledger techniques within the workflow orchestration to timestamp and log every decision, disclosure, and action.
Automates prior art search and analysis across patents filed in multiple languages (e.g., Chinese, Japanese, Korean, German), using translation agents and cross-lingual semantic search to ensure comprehensive coverage. This eliminates the cost and delay of human translation for initial searches, providing a global novelty assessment for multinational companies.
This workflow uses deep semantic models to find non-obvious prior art and potential infringements by analyzing patent claims and technical documents across different technical domains and vocabularies. It uncovers risks and opportunities that keyword-based searches miss, providing a competitive edge in crowded technology spaces.
Automates the highly manual process of creating claim charts for litigation or licensing, mapping product features or competitor patents to the claims of asserted patents. This drastically reduces the cost and time of pre-litigation analysis and discovery, using agents trained in claim construction and product teardown analysis.
This workflow uses historical prosecution data, examiner profiles, and art unit trends to predict the likelihood of grant and estimated time to allowance for a draft application. It helps prioritize filings and manage prosecution budgets, built as a predictive modeling pipeline integrated into the drafting and filing decision process.
Continuously monitors new product announcements, datasheets, and FCC filings to automatically compare public product descriptions against a company's own patent portfolio or a watchlist of competitor patents, flagging potential infringement. This enables proactive enforcement or design-around, using web scraping, NLP, and product feature extraction agents.
This advanced workflow uses generative AI models trained on patent landscapes and technical literature to propose novel invention concepts that fill identified white space. It acts as an R&D co-pilot, stimulating innovation in strategically valuable areas, with careful governance to ensure output novelty and alignment with business goals.
Fully automates the decision and payment process for patent maintenance fees by applying business rules (product lifecycle, market presence, licensing revenue) to each asset. This workflow can auto-pay for high-value patents and flag others for human review, integrating with financial systems and patent office payment portals to optimize portfolio costs.
Extends IP automation to trademarks by automating preliminary clearance searches across registries and common law sources, assessing risk, and preparing draft application materials. This workflow streamlines brand protection, reducing legal costs and accelerating time to market for new brands and logos, with integration into brand management platforms.
Automates the registration of copyrights for software codebases, documentation, and marketing content by assembling the required deposits, generating descriptions, and managing submission with the Copyright Office. This provides scalable protection for digital assets, using code repository scanning and content aggregation agents.
How We Work
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
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We understand the task, the users, and where AI can actually help.
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We define what needs search, automation, or product integration.
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We implement the part that proves the value first.
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We add the checks and visibility needed to keep it useful.
Read moreThe first call is a practical review of your use case and the right next step.
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