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Nine US patent applications, 495 claims, 62 independent claims. Methodology validated at scale on public corpora; production accuracy pending Q3-Q4 2026 customer pilots. Honest framing, not marketing inflation.

Patent register

All 9 provisionals filed at USPTO between March and April 2026 under micro-entity status ($585 total). PCT international protection deadlines noted below.

# Patent Application Filed Claims IC PCT deadline
1G — AI authorship attributionUS 64/009,8642026-03-183242027-03-18
2J — Single-pass multi-domain scanUS 64/022,4662026-03-305052027-03-30
3K — Real-time visualization (Dracula)US 64/030,7312026-04-067782027-04-06
4H — AI Artifact Audit (HAES)US 64/030,7522026-04-065682027-04-06
5A — Tiered LLM remediationUS 64/030,7622026-04-065882027-04-06
6F — PredOpt backlog optimizerUS 64/030,7732026-04-065272027-04-06
7B — CI/CD gate w/ policy DSLUS 64/033,0222026-04-085162027-04-08
8D — Cross-tool canonical scoringUS 64/033,0582026-04-087192027-04-08
9C — Regression detectionUS 64/033,0632026-04-084872027-04-08
Σ 9 filed (Patent E defensive-published only) 495 62

Validation evidence

Patent G PoC v3.0 (March 2026). Methodology cross-referenced against 6,439,303 code samples spanning 64 distinct AI models (Llama, Qwen, DeepSeek, Gemini, Phi, GPT-4, Claude, IBM Granite, StarCoder, …) across 13 programming languages and 9 published datasets (AICD-Bench T1/T2/T3, DroidCollection, CodeMirage, GPTSniffer, DevGPT, SWE-bench, Stack Overflow Survey). All 7/7 Patent G claims CONFIRMED with STRONG-to-VERY-STRONG evidence at scale.

Three confirmed claims

  1. Multi-signal detection necessary. Single-feature classifiers (e.g. code length alone) are insufficient — Cliff's δ 0.07-0.28 (negligible-to-small effect size across 6M+ samples). Patent G's multi-signal architecture is necessary, not optional.
  2. Per-model fingerprinting feasible. Distinct line/character/stdev signatures per LLM (e.g. o3-mini avg 169.9 lines vs llama3.3 avg 83.2 — a 2× difference). Enables per-tool quality scoring on customer codebases.
  3. AI adoption is exponential. DevGPT corpus shows 145% growth in 77 days (Spearman rs = 0.98, p < 0.001); power users dominate (Gini 0.68 — top 7% of authors produce 41% of AI commits).

Honest framing

The PoC validates the methodology at scale on public corpora. End-to-end ariada.ai classifier accuracy on production customer code is pending Q3-Q4 2026 customer pilots (PoC v4.0 in scoping). We do not claim "validated on N customer sites today."

Patent F + Patent J research record

Sources: research/poc/patent-g/PATENT_G_POC_V3_REPORT.md, umbrella PRD §13, research/output/competitive-Q2-2026.md.

Security & compliance footprint

Risks (honest framing)

Top risks from the umbrella PRD §14, abridged. Full risk register lives in the internal product spec.

# Risk Impact Mitigation
1Enterprise sales cycle (180-360d) > runwayCriticalLand-and-expand from blamer/clamper Pro; partner agency program; founder-led outbound to 50 named accounts
2Incumbent (Deque, Siteimprove) adds 1-2 ariada.ai capabilitiesHigh9-patent stack means single-capability copy non-fatal; arxiv-monitor weekly + competitor quarterly
4Pilot accuracy below 80% canonical scoring agreementHighPhase 1 limited to high-confidence rule mappings; iterative D-weight tuning; manual override
7LLM cost overrun on Tier-2/3 remediationMediumTier cascade + cache + similarity reuse; per-org budget; auto-downgrade; dual-vendor
8Founder bandwidth — 1-2 ppl can't ship 6 capabilities + salesCriticalPhase 1 narrowed to 6 capabilities, not all 9; build-prompts dispatched in fresh sessions
10Patent infringement claim (AudioEye 10-K IP-litigation posture)Critical9 ADOPTA provisionals + CANTOR / Evinced / AudioEye prior-art scans + threat-triage; PCT on time; design-around reserve

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