tegrityAI.com — Scientific Integrity Verification
Tegrity independently derives conclusions from raw scientific data — before ever seeing what the authors claimed. If the experiment was clean, our conclusion matches theirs. If it doesn't, you have a finding.
Scientific papers conflate two distinct things: the experiment and the interpretation. Raw data is fact. Conclusions are choices. Every downstream decision that relies on published science is exposed to interpretation contamination.
An estimated majority of published scientific findings fail independent reanalysis. The causes are well-documented: selective reporting, p-hacking, spreadsheet errors, missing statistical corrections. The consequences compound for decades.
Licensing deals, clinical guidelines, regulatory filings, and policy decisions all reference published science. None of them independently verify the conclusion against the raw data before committing. Until now.
Existing tools — citation analysis, statistical error checkers, retraction trackers — audit the interpretation layer or its artifacts. None independently derive a conclusion from the underlying data before comparing. That's Tegrity's structural distinction.
When any model, analyst, or peer reviewer reads the abstract first, they absorb the authors' conclusion before they see the data. Every subsequent evaluation is primed. Tegrity's architecture ensures the deriving model never sees the original conclusion. Separation is structural, not procedural.
Every stage has a single responsibility. No stage can contaminate the next. The separation isn't a rule — it's the architecture.
Tegrity has been validated against five published cases where both a flawed original paper and a corrected reanalysis exist publicly. In every case, the pipeline diverged from the flawed original and converged with the corrected reanalysis — without being told which was correct.
| Paper | Domain | Flaw Type | Verdict |
|---|---|---|---|
| Reinhart-Rogoff (2010) | Economics / Policy | Spreadsheet error excluded 5 countries from high-debt cohort, reversed sign of effect | DIVERGE |
| Fear Memory Gene Expression | Neuroscience | Multiple-testing corrections omitted; statistical significance inflated 4.2× | DIVERGE |
| Microplastics 5g/week (2019) | Environmental Science | Double-counting errors produced 2× overestimate; propagated into policy for 3 years | DIVERGE |
| Thiram Adsorption Thermodynamics | Chemistry | Internal thermodynamic inconsistency — parameters don't reconstruct from reported data | DIVERGE |
| Obesity Drug Supplement Meta-Analysis | Clinical Research | Data extraction errors across included studies inflated pooled effect size | DIVERGE |
Any decision that relies on published science is exposed. Tegrity gives you a machine-generated audit trail before you commit.
Your BD team is three weeks from closing a $50M licensing agreement. The target compound's efficacy claim rests on a competitor's published biomarker study. Tegrity runs the paper overnight and returns a verdict before you close. Diverge means you have a material due diligence finding before it's too late.
Catch interpretation contamination during peer review, not after retraction. Tegrity integrates into your submission workflow and returns a structured verdict on any paper you flag. Pre-publication screening — not post-hoc correction.
Reproducibility requirements are expanding across NIH, DoD, and DARPA. Tegrity provides a machine-generated, auditable integrity record for grant-funded research — structured, versioned, and defensible for any oversight review.
The question in scientific litigation is whether the data actually supports the conclusion. Tegrity produces a machine-generated audit trail with evidence citations — structured, reproducible, and ready for deposition.
Tegrity ignores the interpretation layer entirely. That's not a feature difference — it's an architectural one.
| Tool | Approach | Limitation |
|---|---|---|
| Scite.ai | Citation sentiment | Operates on citations, not raw data |
| Retraction Watch | Manual curation | Reactive — post-hoc only |
| Statcheck | Statistical error detection | Works inside author's framework |
| Papermill Alarm | Metadata anomaly | Pattern-matching, not derivation |
| Clarivate / Elsevier | Plagiarism, citation integrity | Not data-derivation independent |
| Tegrity | Independent derivation | Derives before comparing |
"The distinction maps exactly to engineering controls versus administrative controls in GMP manufacturing. Administrative controls tell the model what to ignore. Engineering controls ensure the model never encounters what should be ignored. Tegrity's Stage 1 deterministic prescreen is that wall. The interpretation is removed before any model touches the data. The hallway doesn't exist."
Each buyer solves their own personal problem. Their win creates the input condition for the next buyer's win. Nobody optimizes the system. The system optimizes itself.
The fan becomes a wall becomes a building code. Each stage is irreversible.
We're onboarding a limited number of pilot partners — pharma BD teams, journals, and research integrity professionals. No commitment required.