# ObviouslyNot

> AI-powered concept scanner that surfaces strategic technical concepts hidden in your GitHub repositories. First scan free. No API key or credit card required. Patentability determinations are made by patent attorneys, not by ObviouslyNot. We also publish original research on patent representation gaps.

## What ObviouslyNot Does

ObviouslyNot scans codebases for distinctive algorithms, architectures, and methods, then generates scored strategic concepts with evidence citations from actual code. Developers paste a GitHub URL, and the AI analyzes the repository for strategic concepts the developers may not have realized set their work apart from the competition. The scanner identifies; the patent attorney determines whether what was found may be patentable.

Key stats from early pilots:
- 147 strategic concepts identified
- 3.2x more findings than developers expected
- 92% accuracy in pilots

## Ways to Run the Scanner

One concept scanner engine, four ways to run it (see https://obviouslynot.ai/discover). It is not a patent scanner: it surfaces distinctive technical concepts in code; a patent attorney determines patentability.
- Local CLI (https://obviouslynot.ai/download-patent-scanner): open-source binary, scan locally with Ollama, free and private, code never leaves your machine.
- GitHub Concept Scanner Action (https://obviouslynot.ai/github-concept-scanner): the GitHub Marketplace Action (v1.0.5) + Docker image; scan every pull request in CI. Bring your own OpenAI-compatible provider, or Ollama on a self-hosted runner.
- Agent skills (https://obviouslynot.ai/patent-skills): the scanner and its patent-analysis companions as portable Agent Skills for Claude Code, Gemini CLI, Cursor, and any compatible agent.
- Hosted platform (launching): zero-setup scanning in the browser, plus the path from concept to a fileable provisional.

## Patent Practitioner Tools, a separate program for practitioners

https://patentcontinuation.com is a different product from the scanner, for a different reader and a later moment in the file. It takes a specification and the parent claims as filed, drafts candidate continuation claims, reads the file history for rejections and allowed limitations, flags 112(a) and 112(b) defects, and scores the drafting against the specification. Free; runs locally through Ollama or your own provider key, so an unfiled specification does not have to leave the building.

It is written for licensed patent attorneys and agents and those working under their supervision. It is R&D-grade and its output is never filing-ready: it drafts claim language and scores drafting quality, it does not assess patentability, novelty or non-obviousness, and it is not a substitute for a practitioner's judgment. Every output is drafting input for a practitioner who exercises that judgment over it.

## How It Works

1. Sign Up and Scan: Create an account and paste a GitHub URL. First repository scan is completely free, ObviouslyNot covers the AI costs.
2. Review Your Discoveries: AI analyzes the codebase for distinctive algorithms, architectures, and methods. Users get scored strategic concepts with evidence citations from actual code. A patent attorney can help determine whether to attempt to protect these strategic concepts by filing a patent application.
3. Go Further With Your Own Key: Add an OpenRouter API key for unlimited scans. Users choose the models. Full cost transparency. A typical scan costs $0.50-$2.00 in API credits.

## Who It's For

- Software Engineers: Algorithms, architectures, and technical solutions may be patentable. Most engineers never find out.
- Tech Founders: IP is a competitive moat. Discovering and protecting it early shapes fundraising, licensing, and exit value.
- Vibe Coders: AI is changing who creates software. If building novel systems with AI tools, the innovations are still protectable.
- Patent Attorneys: Scanner finds strategic concepts that might be inventive in clients' codebases and generates structured technical disclosures ready for review. AI-structured disclosures, Alice/Mayo aware draft claim sets anchored to specific technical implementations, scans Git repos and PRs. Attorney-first by design, the tool discovers and structures, attorneys exercise the legal judgment.
- Women Inventors and the institutions that support them: The patent system loses too many inventions to disclosure-stage failures. ObviouslyNot's scanner closes that gap structurally rather than asking inventors to self-nominate.

## AI Agent Skills

ObviouslyNot publishes open-source AI agent skills built on the Agent Skills standard. These work with Claude Code, Gemini CLI, Codex CLI, Cursor, and any compatible agent.

### Patent Analysis Skills
- Code Patent Scanner: Scan codebase for distinctive patterns. Get structured scoring and evidence for patent consultation.
- Code Patent Validator: Turn code scan findings into search queries. Research existing implementations.
- Patent Scanner: Describe a concept for structured analysis and patent consultation.
- Patent Validator: Turn concept analysis into search queries. Research the landscape.

### Principle Extraction Skills
- PBE Extractor: Extract invariant principles from any text. Find ideas that survive rephrasing.
- Principle Comparator: Compare two sources to find shared and divergent principles.
- Principle Synthesizer: Synthesize invariant principles from 3+ sources into a unified core.
- Essence Distiller: Find what actually matters. The ideas that survive any rephrasing.
- Pattern Finder: Discover what two sources agree on. Find the signal in the noise.

### Advanced Skills
- Core Refinery: Find the core that runs through everything across 3+ extractions.
- Golden Master: Track source-of-truth relationships between files.

Install: `git clone https://github.com/Obviously-Not/patent-skills` then `cp -r patent-skills/code-patent-scanner .claude/skills/`
Or via OpenClaw: `clawhub install leegitw/code-patent-scanner`

Note: These tools identify technical patterns, not patentability. They do not search patent databases, assess patentability, provide legal conclusions, or replace professional counsel. Consult a patent attorney for IP guidance.

## Security

- API keys encrypted with AES-256-GCM before touching the queue
- Plaintext keys never logged, stored in a database, or visible to the team
- OpenRouter is an AI gateway giving access to Claude, GPT, Gemini, DeepSeek through a single API key

## Research

ObviouslyNot publishes original research on patent representation and access. Our flagship is the patent gender gap series, the largest current data compilation on U.S. women inventors with primary-source citations to USPTO, WIPO, EPO, UK IPO, PNAS, Science, Nature Biotechnology, and AEJ:Economic Policy.

### The Patent Gender Gap Series (hub + 8 child pages)

Hub: [The Patent Gender Gap by the Numbers](https://obviouslynot.ai/patent-gender-gap). Women make up 29% of the U.S. STEM workforce but hold 12.8% of U.S. patents (USPTO 2019). Globally, WIPO reports 18.0% of PCT inventors are women (2024). The hub summarizes the data; each child page walks one specific mechanism with primary-source citations.

Children:

**[Where Women's Patents Disappear](https://obviouslynot.ai/patent-gender-gap/where-womens-patents-disappear)**: The U.S. patent gender gap is six compounding failures: filing, first office action, response and abandonment, appeal, grant and claim scope, post-grant citation and licensing. More than half the granted-patent gap is attributable to differential abandonment after rejection (MIT Press, 2024). UK IPO 2026: individual female applicants are 1.6x more likely to terminate their applications before grant than all-male teams.

**[The Breakthrough Penalty](https://obviouslynot.ai/patent-gender-gap/the-breakthrough-penalty)** (FLAGSHIP): The 2026 PNAS paper by Sowrirajan, Whalen, and Uzzi analyzed 6.2 million USPTO applications (2001-2018) and found that the gender gap in U.S. patenting is concentrated in unconventional inventions. No meaningful gap on conventional patents; a 14.9 percentage point gap on highly unconventional patents. All-women teams with low-experience women examiners grant at 37.1%; all-men teams with high-experience men examiners grant at 81.8%, a 44.7 pp paired-team gap. The mechanism is institutional (examiner-assignment patterns and differential experience), not individual bias. Replicated in Canada and UK at P<0.001.

**[AI's Gender Gap Is Becoming an Ownership Gap](https://obviouslynot.ai/patent-gender-gap/ai-ownership-gap)**: The USPTO AI Patent Dataset (Giczy, Pairolero, & Toole) classifies 15.4 million U.S. patent documents from 1976-2023. AI patenting has been one of the fastest-expanding patent categories of the past decade. Women's AI patent participation is growing but lags the already-low baseline. As AI inventorship compounds into commercialization, today's gap becomes tomorrow's wealth gap. China's WTO accession (NBER 2024 Agrawal et al.) provides cross-national evidence that the AI gender gap is policy-responsive: post-WTO, Chinese patents with at least one female inventor rose 95% relative to comparison countries.

**[Engineering vs Biotech Breakdown](https://obviouslynot.ai/patent-gender-gap/engineering-vs-biotech-breakdown)**: Chemistry ~18%, biotech/pharma 15-18%, design patents ~17%, electrical engineering 10%, software/ICT 7-10%, mechanical engineering ~6%. The fields with the most patents have the fewest women. Hunt et al. (NBER 2013) found 78% of the gap is field composition. Koning et al. (Science 2021): all-female biomedical inventor teams are 35% more likely to focus on women's health needs.

**[WIPO International Data](https://obviouslynot.ai/patent-gender-gap/wipo-international-data)**: Türkiye 26.0%, China 24.2%, U.S. ~17.8%, Japan ~10%, Germany ~10% (WIPO PCT Yearly Review 2025). Regional: Latin America & Caribbean 24.9%, Africa 14.5%. EPO 2026 "Promoting women in STEM" found 13.8% women inventors in Europe in 2022 with comparable inventive potential. UK IPO 2026 (Brady Bowes) found 7.8-10.9% UK inventor occurrence and termination rates by team type (48.3% individual-female, 42.1% all-female, 29.7% all-male).

**[One Woman Is Not Parity](https://obviouslynot.ai/patent-gender-gap/one-woman-is-not-parity)**: The methodological distinction every reader needs. "At least one woman inventor" patents: 21.9% of U.S. patents. Share-weighted women inventor rate: 12.8%. All-women inventor teams: ~4%. The 17.9 percentage points between these metrics is the gap between optical and actual progress. The choice of metric determines the story.

**[Historical Timeline 1900-2025](https://obviouslynot.ai/patent-gender-gap/historical-timeline-1900-2025)**: 125 years of women in U.S. patenting. Three structural shifts coincided with most of the visible growth: expanded STEM education access (Title IX 1972), the modern university tech-transfer system (Bayh-Dole 1980), and the post-2014 wave of institutional interventions. Women's share of patents went from <1% in 1900 to 21.9% (at-least-one-woman) and 12.8% (share-weighted) by 2019.

**[Closing Strategies That Work](https://obviouslynot.ai/patent-gender-gap/closing-strategies-what-works)**: Four interventions with measured evidence. USPTO Pairolero RCT (AEJ:EP 2025): +12 percentage points grant rate from examiner-side procedural support. Washington University WIT program: +129% women faculty patent filings (2011-13 vs 2013-16). Stanford OTL 50-year analysis (Tseng et al., Patterns 2022): women's inventor share roughly tripled from ~7% (mid-1990s) to ~20% (2020). USIPA Innovation Diversity Pledge (50+ company signatories). All interventions are categorized by evidence strength: causal RCT, institutional case study, descriptive, or accountability/transparency.

### The Patent Representation Gap Index

[Patent Representation Index](https://obviouslynot.ai/patent-innovation-gap-index): Composite score ranking 91 tech companies on how well they translate women's technical work into patent inventorship. Five sub-indices: women in STEM workforce, women inventors as a share of all inventors, the ratio between them, the trend over the last 24 months (sample-size weighted), and inventor concentration. Built from BigQuery patent data and government EEO-1 workforce filings.

[Full Company Data](https://obviouslynot.ai/patent-innovation-gap-index/patent-innovation-gap-full): Complete underlying data table covering 170 companies with sub-index breakdowns. Methodology and limitations documented.

### Other Research

[Technology Discrimination](https://obviouslynot.ai/technology-discrimination-patent-access): The structural argument behind functional inequality for software inventors in the patent system. Companion piece to the gender gap series.

## Guides

- [Why Most Software Patents Start Too Late](https://obviouslynot.ai/software-patents-start-too-late)
- [Is it obvious?](https://obviouslynot.ai/is-my-invention-obvious)
  - [The seven rationales behind an obviousness rejection](https://obviouslynot.ai/is-my-invention-obvious/mpep-2143-seven-rationales)
  - [When combining things that already exist is obvious](https://obviouslynot.ai/is-my-invention-obvious/combining-things-that-already-exist)
  - [Novelty and obviousness are different tests](https://obviouslynot.ai/is-my-invention-obvious/novelty-and-obviousness-are-different)
  - [Anticipation needs one reference to carry the whole claim](https://obviouslynot.ai/is-my-invention-obvious/one-reference-has-to-carry-the-claim)
- [What Is Patent Mining?](https://obviouslynot.ai/patent-mining)
- [What counts as prior art?](https://obviouslynot.ai/what-counts-as-prior-art)
  - [Printed publication means findable](https://obviouslynot.ai/what-counts-as-prior-art/printed-publication-means-findable)
  - [What available to the public reaches](https://obviouslynot.ai/what-counts-as-prior-art/available-to-the-public)
  - [The one year you get, and what it does not cover](https://obviouslynot.ai/what-counts-as-prior-art/the-one-year-you-get)
  - [Whose provisional counts, and when](https://obviouslynot.ai/what-counts-as-prior-art/whose-provisional-counts)
- [The PPA as a Stock Option on Your IP](https://obviouslynot.ai/provisional-patent-strategy)
  - [What a provisional application actually is](https://obviouslynot.ai/provisional-patent-strategy/what-a-provisional-actually-is)
  - [What the twelve months actually buy](https://obviouslynot.ai/provisional-patent-strategy/what-the-twelve-months-buy)
  - [How a later application inherits an earlier one's date](https://obviouslynot.ai/provisional-patent-strategy/how-a-later-application-inherits-a-date)
  - [The restoration nobody quotes](https://obviouslynot.ai/provisional-patent-strategy/the-reference-deadline-nobody-quotes)
  - [Continuation and divisional are names, not instruments](https://obviouslynot.ai/provisional-patent-strategy/continuation-divisional-and-cip)
  - [Claiming the benefit: what the manual adds](https://obviouslynot.ai/provisional-patent-strategy/claiming-the-benefit)
- [Software patents in Europe](https://obviouslynot.ai/software-patents-in-europe)
  - [COMVIK: features that cannot support inventive step](https://obviouslynot.ai/software-patents-in-europe/comvik-technical-and-non-technical)
  - [Aerotel: superseded in February 2026](https://obviouslynot.ai/software-patents-in-europe/aerotel-macrossan-four-steps)
  - [The further technical effect](https://obviouslynot.ai/software-patents-in-europe/the-further-technical-effect)
  - [UK Patents Act section 1, after Emotional Perception](https://obviouslynot.ai/software-patents-in-europe/uk-patents-act-section-1)
- [Patent Continuations](https://obviouslynot.ai/patent-continuation-applications)
- [Invention Disclosure Procedure: A Step-by-Step Guide](https://obviouslynot.ai/invention-disclosure-procedure)
- [How your application is put together](https://obviouslynot.ai/how-your-application-is-put-together)
  - [When a drawing is required, and why a later one cannot rescue](https://obviouslynot.ai/how-your-application-is-put-together/when-a-drawing-is-required)
  - [What a patent drawing must look like](https://obviouslynot.ai/how-your-application-is-put-together/what-a-patent-drawing-must-look-like)
  - [Flow charts belong in the drawings](https://obviouslynot.ai/how-your-application-is-put-together/flow-charts-belong-in-the-drawings)
- [Software Patents After Alice](https://obviouslynot.ai/software-patents-after-alice)
  - [Recentive v. Fox: the AI eligibility ceiling](https://obviouslynot.ai/software-patents-after-alice/recentive-v-fox)
  - [Contour v. GoPro: what passes Alice step one](https://obviouslynot.ai/software-patents-after-alice/contour-v-gopro)
  - [Ollnova v. ecobee: timing rules survive Alice](https://obviouslynot.ai/software-patents-after-alice/ollnova-v-ecobee)
  - [GoTV v. Netflix: labels are not structure](https://obviouslynot.ai/software-patents-after-alice/gotv-v-netflix)
  - [Results-oriented claims still fail Alice](https://obviouslynot.ai/software-patents-after-alice/us-patent-7679637-v-google)
  - [Desjardins: when AI training claims are eligible](https://obviouslynot.ai/software-patents-after-alice/ex-parte-desjardins)
  - [Examination guidance on eligibility](https://obviouslynot.ai/software-patents-after-alice/uspto-2024-eligibility-guidance)
  - [Constellation Designs v. LG: result-oriented claims](https://obviouslynot.ai/software-patents-after-alice/constellation-designs-v-lg)
- [Continuation Claims](https://obviouslynot.ai/continuation-claim-drafting)
- [Building in Public and Patents](https://obviouslynot.ai/build-in-public-patent-risk)
- [Section 101 Declaration Strategy](https://obviouslynot.ai/section-101-declaration-strategy)
- [Co-Founder IP: Who Owns What](https://obviouslynot.ai/cofounder-ip-ownership)
- [Who Owns the Code You Write on Your Own Time?](https://obviouslynot.ai/who-owns-your-side-project)
- [AI Patent Discovery and Privilege](https://obviouslynot.ai/ai-patent-discovery-evidence)
- [Your Open Source License Is Also a Patent Decision](https://obviouslynot.ai/open-source-licenses-patent-rights)
  - [A license is not freedom to operate](https://obviouslynot.ai/open-source-licenses-patent-rights/license-versus-freedom-to-operate)
- [IP Ownership Clauses for Remote Contractors](https://obviouslynot.ai/ip-ownership-clauses-remote-contractors)
- [AI Inventorship and Human Conception](https://obviouslynot.ai/ai-inventorship-who-counts-when-ai-helps)
- [IP Protection Checklist for Engineering Teams](https://obviouslynot.ai/ip-protection-checklist-engineering)
- [Tight Ownership Protocols for AI Code Teams](https://obviouslynot.ai/tight-ownership-ai-code-dev-teams)
- [Agentic AI Inventorship: The Open Question](https://obviouslynot.ai/agentic-ai-inventorship)
- [AI Patent Risk: 2026 Firm Consensus](https://obviouslynot.ai/ai-patent-risk-firm-consensus-2026)
- [Drafting with Local AI: What It Protects, and What It Costs](https://obviouslynot.ai/local-model-patent-drafting)
- [Cloud AI Leaks: Trade Secrets vs Patents](https://obviouslynot.ai/cloud-ai-leaks-trade-secrets-vs-patents)
- [Why Local-First Matters for Patent Discovery](https://obviouslynot.ai/local-first-patent-discovery)
- [Software Invention Disclosure Example: A Completed Walkthrough](https://obviouslynot.ai/software-invention-disclosure-example)
- [How to Find Inventions in a Codebase](https://obviouslynot.ai/find-inventions-in-a-codebase)
- [Pre-Filing Patent Privacy: Cloud Risk and Trade Secret Protection](https://obviouslynot.ai/patent-cloud-privacy)
- [AI Tool Compliance Checklist for Patent Practitioners](https://obviouslynot.ai/ai-tool-compliance-checklist)
- [AI Agents and Your Intellectual Property](https://obviouslynot.ai/ai-agents-intellectual-property)
- [IP Ownership in Local-First Sync Engines](https://obviouslynot.ai/ip-ownership-local-first-sync-engines)
- [Tesla's .smol Patent: Data Format IP for Counsel](https://obviouslynot.ai/tesla-smol-data-format-patent-analysis)
- [Protecting Creativity in the AI Era](https://obviouslynot.ai/protecting-creativity-ai)
  - [AI Innovation Addendum](https://obviouslynot.ai/protecting-creativity-ai/ai-innovation-addendum)
  - [AI Innovation Addendum (Lightweight)](https://obviouslynot.ai/protecting-creativity-ai/ai-innovation-addendum-lightweight)
- [Patenting AI Agents for Autonomous Payments](https://obviouslynot.ai/patenting-ai-agents-autonomous-payments)
- [Invention Discovery in AI-Augmented Sprints](https://obviouslynot.ai/invention-discovery-ai-dev-teams)
- [What AI drafting does to draft quality](https://obviouslynot.ai/what-ai-drafting-does-to-draft-quality)
- [Design patents for software interfaces](https://obviouslynot.ai/design-patents-for-software-interfaces)

## Frameworks

- [How to Write a Patent Disclosure: The Three-Level Framework](https://obviouslynot.ai/problem-first-disclosure)
- [AI+Human Innovation Framework](https://obviouslynot.ai/ai-human-innovation-framework)

## For Patent Practitioners

- [Before the PTAB](https://obviouslynot.ai/ptab-practice)
  - [Discretionary briefing is separate, institution is one decision](https://obviouslynot.ai/ptab-practice/ptab-discretionary-institution)
  - [Apple v. Squires: no right to institution](https://obviouslynot.ai/ptab-practice/apple-v-squires)
  - [Arthrex, and the rule that makes you choose](https://obviouslynot.ai/ptab-practice/arthrex-and-director-review)
  - [Proposed, not adopted](https://obviouslynot.ai/ptab-practice/ptab-institution-nprm-2025)
- [Filing and Fees](https://obviouslynot.ai/uspto-filing-and-fees)
  - [The 60 and 80 percent fee reductions](https://obviouslynot.ai/uspto-filing-and-fees/uaia-small-micro-entity-fees)
  - [IDS size fees and the required assertion](https://obviouslynot.ai/uspto-filing-and-fees/uspto-fy2025-fee-rule-non-continuation)
  - [After-final practice without AFCP 2.0](https://obviouslynot.ai/uspto-filing-and-fees/afcp-termination)
  - [Filing format and who may sign](https://obviouslynot.ai/uspto-filing-and-fees/docx-and-electronic-signatures)
- [Duties, and Who May Practise](https://obviouslynot.ai/practitioner-duties)
  - [Disclosure, inquiry, and other agencies](https://obviouslynot.ai/practitioner-duties/duties-of-disclosure)
  - [Using AI before the Patent Office](https://obviouslynot.ai/practitioner-duties/ai-tools-in-practice-guidance)
  - [When a foreign applicant must use a US practitioner](https://obviouslynot.ai/practitioner-duties/foreign-applicant-representation)
  - [Who may practise, and on what terms](https://obviouslynot.ai/practitioner-duties/practitioner-access-reforms)
- [Invention Disclosure Form](https://obviouslynot.ai/invention-disclosure-form)
- [Software §101 Eligibility Worksheet](https://obviouslynot.ai/software-101-eligibility-worksheet)
- [Non-Obviousness Worksheet](https://obviouslynot.ai/non-obviousness-worksheet)
- [Claim Scope Ladder](https://obviouslynot.ai/claim-scope-ladder)

## Legal Templates

- [Idea Disclosure Template](https://obviouslynot.ai/idea-disclosure-template)
- [Idea Strength Check](https://obviouslynot.ai/idea-strength-check)
- [Three Levels of Your Idea](https://obviouslynot.ai/three-levels-of-your-idea)
- [Disclosure Quality Check](https://obviouslynot.ai/disclosure-quality-check)

## Legal Precedents

- [Who Owns It, and Who Invented It?](https://obviouslynot.ai/who-owns-it-and-who-invented-it)
  - [Omni MedSci: promise to assign is not assignment](https://obviouslynot.ai/who-owns-it-and-who-invented-it/omni-medsci-v-apple)
  - [Fortress Iron: the coinventor you can't find](https://obviouslynot.ai/who-owns-it-and-who-invented-it/fortress-iron-v-digger)
  - [Thaler v. Vidal: inventors must be human](https://obviouslynot.ai/who-owns-it-and-who-invented-it/thaler-v-vidal)
  - [Minerva v. Hologic: when founders can fight back](https://obviouslynot.ai/who-owns-it-and-who-invented-it/minerva-v-hologic)
  - [The 2024 AI inventorship guidance is rescinded](https://obviouslynot.ai/who-owns-it-and-who-invented-it/revised-ai-inventorship-guidance)
- [What recent patent decisions add up to](https://obviouslynot.ai/recent-patent-decisions)
- [Patent Term and Double Patenting](https://obviouslynot.ai/patent-term-and-double-patenting)
  - [In re Cellect: when extra term becomes a liability](https://obviouslynot.ai/patent-term-and-double-patenting/in-re-cellect)
  - [Allergan v. MSN: the limit on In re Cellect](https://obviouslynot.ai/patent-term-and-double-patenting/allergan-v-msn)
  - [Ex parte Baurin: the limit on Allergan's limit](https://obviouslynot.ai/patent-term-and-double-patenting/ex-parte-baurin)
- [If You Are Sued, or You Sue](https://obviouslynot.ai/if-you-are-sued-or-you-sue)
  - [Caltech v. Broadcom: IPR is one shot](https://obviouslynot.ai/if-you-are-sued-or-you-sue/caltech-v-broadcom)
  - [Ingenico: estoppel follows grounds, not evidence](https://obviouslynot.ai/if-you-are-sued-or-you-sue/ingenico-v-ioengine)
  - [SRI v. Cisco: what willful infringement means](https://obviouslynot.ai/if-you-are-sued-or-you-sue/sri-v-cisco)
  - [Columbia v. Gen Digital: claims, not the spec](https://obviouslynot.ai/if-you-are-sued-or-you-sue/columbia-v-gen-digital)
  - [Hikma v. Amarin: inducement needs active steps](https://obviouslynot.ai/if-you-are-sued-or-you-sue/hikma-v-amarin)
  - [EcoFactor v. Google: damages evidence tightened](https://obviouslynot.ai/if-you-are-sued-or-you-sue/ecofactor-v-google)
  - [Brumfield v. IBG: foreign damages, U.S. patents](https://obviouslynot.ai/if-you-are-sued-or-you-sue/brumfield-v-ibg)
  - [Lynk Labs: prior art dated from filing](https://obviouslynot.ai/if-you-are-sued-or-you-sue/lynk-labs-v-samsung)
  - [Socket Solutions: no presumed irreparable harm](https://obviouslynot.ai/if-you-are-sued-or-you-sue/socket-solutions-v-import-global)
  - [VDPP v. Volkswagen: your licensees have to mark](https://obviouslynot.ai/if-you-are-sued-or-you-sue/vdpp-v-volkswagen)
- [When Must I File?](https://obviouslynot.ai/when-must-i-file)
  - [Celanese v. ITC: secret process, public sales](https://obviouslynot.ai/when-must-i-file/celanese-v-itc)
- [How Broadly Can I Claim?](https://obviouslynot.ai/how-broadly-can-i-claim)
  - [Amgen v. Sanofi: the more you claim, the more you enable](https://obviouslynot.ai/how-broadly-can-i-claim/amgen-v-sanofi)
  - [Juno v. Kite: two examples, one billion lost](https://obviouslynot.ai/how-broadly-can-i-claim/juno-v-kite)
  - [Wyeth v. AstraZeneca: dosage claims and enablement](https://obviouslynot.ai/how-broadly-can-i-claim/wyeth-v-astrazeneca)
  - [Showing possession of what you claim](https://obviouslynot.ai/how-broadly-can-i-claim/showing-possession-of-what-you-claim)
  - [Enablement and the Wands factors](https://obviouslynot.ai/how-broadly-can-i-claim/enablement-and-the-wands-factors)
  - [Three requirements in one sentence](https://obviouslynot.ai/how-broadly-can-i-claim/three-requirements-in-one-sentence)
- [AI Patent Legal Precedents](https://obviouslynot.ai/ai-patent-legal-precedents)
- [LKQ v. GM: design patent obviousness reset](https://obviouslynot.ai/lkq-v-gm)
- [AI Prompts in Federal Discovery (2026)](https://obviouslynot.ai/ai-prompts-discovery-federal-court)
- [AGI SureTrack v. Farmers Edge §101](https://obviouslynot.ai/agi-suretrack-section-101)

## Case Studies

- [27 Strategic Concepts Hiding in a Flight-Control Codebase](https://obviouslynot.ai/px4-autopilot-concept-scan)
  - [Hover-Thrust Integrator Compensation](https://obviouslynot.ai/px4-autopilot-concept-scan/hover-thrust-compensation)
  - [Sequential Desaturation with Airmode Priority](https://obviouslynot.ai/px4-autopilot-concept-scan/sequential-desaturation)
  - [External Mode-Executor Registration](https://obviouslynot.ai/px4-autopilot-concept-scan/external-mode-registration)

## FAQ

Q: Is my first scan really free?
A: Yes. First repository scan is completely free. No credit card or API key required.

Q: What kind of code can be patentable?
A: Novel algorithms, data processing pipelines, system architectures, and technical methods.

Q: How much does scanning cost after the first free scan?
A: A typical repository scan costs roughly $0.50 to $2.00 in API credits on the user's OpenRouter account, depending on repository size.

Q: What is OpenRouter?
A: An AI gateway that gives access to Claude, GPT, Gemini, DeepSeek, and more through a single API key.

Q: Is my API key secure?
A: Yes. Keys are encrypted with AES-256-GCM before touching the queue. Plaintext keys are never logged or stored.

Q: What can I do once I find a strategic concept that might be worth attempting to protect?
A: That's up to you. Some developers use their discoveries for fundraising conversations, defensive positioning, or internal IP tracking. For those who want to file, our technical disclosure pipeline is free while in beta, generates a technical description of your strategic concept from your scan results. Take this to a patent attorney to explore patentability.

Q: Why does ObviouslyNot publish patent gender gap research?
A: The most consequential failure in the U.S. patent system happens at the disclosure stage, before any application reaches USPTO. ObviouslyNot's scanner closes that gap structurally rather than asking inventors to self-nominate. Our research documents the gap quantitatively and the interventions that close it.

## Company

Founded in 2024 by twin founders. Based in Alaska and Texas; the team came out of Seattle and remains part of its tech and legal ecosystems.

- Website: https://obviouslynot.ai
- Scanner App: https://app.obviouslynot.ai
- Patent Practitioner Tools: https://patentcontinuation.com (for licensed practitioners)
- GitHub: https://github.com/Obviously-Not
- YouTube: https://www.youtube.com/@2ObviouslyNot
- Contact: hello@obviouslynot.ai