TIER 3 · ADDRESSABLE NICHE · SCIENTIFIC RESEARCH AND PEER REVIEW
Audit infrastructure / for research AI.
AI-assisted drug discovery, literature synthesis, and peer review are accelerating the research pipeline while creating new reproducibility challenges. FDA requirements for AI-assisted drug development, NIH data sharing policies, and research integrity requirements for journals using AI review all create concrete demand for auditable AI decision records.
REGULATORY OBLIGATIONS
FDA / NIH research AI guidance
Active · US federally funded
AI in research integrity and grant compliance
FDA guidance requires documented, auditable AI decision trails for AI-assisted research with regulatory submission implications. NIH and NSF grant terms increasingly require disclosure and documentation of AI tools used in funded research. For pharma R&D with full GxP audit requirements and FDA Warning Letter context, see /for/pharma-rd — this segment covers academic and independent research contexts.
NIH data sharing
Active · US federally funded
Data management and sharing policy
NIH 2023 data management and sharing policy requires NIH-funded research to document AI tool use in data analysis. Reproducibility requires that AI decisions be traceable to the exact model version and inputs used.
Research integrity
Active · major journals
Journal AI-assisted peer review policies
Nature, Science, Cell, and other top journals have established policies on AI-assisted peer review and research. Disclosure and documentation of AI use is required. Tamper-evident records satisfy the documentation standard.
* EU AI Act Annex III enforcement date: August 2, 2026 (legally operative). EU Digital Omnibus provisional agreement (May 7, 2026) proposes extending to December 2, 2027 — not yet formally enacted. Prepare for the earlier date.
HOW YOLO SATISFIES IT · PRIMITIVE → REQUIREMENT
PRIMITIVE
REQUIREMENT SATISFIED
AUDIT CHAIN
NIH reproducibility · research integrity documentation
Every AI research decision — literature synthesis, hypothesis generation, statistical analysis, peer review recommendation — logged in a tamper-evident, reproducible record. Journal editors, NIH program officers, and institutional review boards can verify independently. The chain provides the reproducibility evidence required by journals (Nature, Science, Cell) and funding agencies.
IDENTITY REGISTRY
AI tool version traceability for reproducibility
Each research AI tool version has a verifiable identity. Reproducibility requires knowing which exact version of which model generated which result. ERC-721 identity provides permanent, third-party-verifiable version documentation across the decade-long lifecycle of a research program.
REPUTATION ORACLE
Research AI quality signal for institutional credibility
Reputation scores computed from verified AI output history. Research institutions and AI tool vendors can demonstrate a track record of reproducible, well-documented AI outputs — a third-party verifiable signal that goes beyond self-reported accuracy claims or single-study validation.
AUDIT CHAIN AND IDENTITY REGISTRY ARE LIVE ON BASE MAINNET TODAY.
PRICING · DECISIONAL LOGGING TIERS
ROUTINE
$0.0001 / event
Routine events
CONSEQUENTIAL
$0.01 / event
Consequential events
HIGH-STAKES
$0.10 / event
High-stakes events
VOLUME NOTE
Academic research: routine for literature synthesis + consequential for analysis decisions = $10K–$50K/year per active R1 research institution. NIH-funded R01-scale research team: ~$5K–$20K/year. High-stakes ($0.10/event) for peer review recommendations and integrity-critical classifications. Academic pricing available with institutional agreements.
SCALE
$10K–$100K/year per academic research institution. Top-100 R1 biomedical research universities (Harvard, Hopkins, Stanford, UCSF, MIT): $50K–$100K/year. National labs (NCI, NHLBI, NIAID, Broad Institute, Wellcome Sanger): $50K–$250K/year. Academic medical centers (Mass General Brigham Research, Mayo Clinic Research): $25K–$100K/year. TAM: ~$10M–$25M ARR at maturity.
WHO BUYS THIS
NIH-funded R1 universities · Broad Institute · Wellcome Sanger Institute · MRC Laboratory of Molecular Biology · Karolinska Institute · Mass General Brigham Research · Mayo Clinic Research · Cleveland Clinic Research · EMBL European Molecular Biology Lab · Allen Institute for Brain Science · Chan Zuckerberg Biohub · Scripps Research · Cold Spring Harbor Laboratory · Howard Hughes Medical Institute · Salk Institute · Fred Hutchinson Cancer Center · Dana-Farber Cancer Institute · MD Anderson Cancer Center · CSIRO Australia · Max Planck Institutes · Francis Crick Institute · Alan Turing Institute
WHAT THIS REPLACES
NIH grant suspension for data integrity failure: $1M–$50M+ in lost funding. Retraction of major paper: incalculable career damage + $500K–$5M institutional response cost. Failed reproducibility study restart: $500K–$5M. Manual AI provenance audit per journal submission: $5K–$50K per paper in documentation overhead.
ACTIVATION TRIGGER
NIH 2023 data management and sharing policy enforcement active. Next major journal retraction citing AI provenance issues accelerates institutional adoption. NSF/NIH moving toward machine-readable AI decision records. Pharma R&D with regulatory submissions: see /for/pharma-rd for the Tier 1 active pursuit version of this segment.
For research integrity officers, principal investigators, IRB chair, director of research computing, NIH program officers, journal editors (Nature, Science, Cell).