Pre-Flight
Validator for Research.
Define the institutional standard. ARGUS-Thesis functions as an adversarial pre-flight check. It generates a Technical Governance Report evaluating your manuscript against the structural patterns of high-impact research.
Trusted By
PhD Candidates
Stress-testing defenses
Lab Directors
Standardizing output quality
Grant Writers
Validating core impact
Technical Governance: The system generates a timestamped Audit Artifact documenting the logical stress-test results. This is a computational benchmark, not a peer review replacement.
Top 25% of Papers Verified by ARGUS-Thesis
are Accepted without Revisions.
Calibrated for Researchers at Top Universities
The Adversarial Compiler.
Research is not written; it is forged. ARGUS-Thesis treats your manuscript as code, compiling it against strict logical axioms and novelty requirements.
1. Structural Extraction
Decomposing text into a map of core claims, evidence, and logical connectives.
2. Adversarial Logic Engine
A proprietary multi-model system attacks the argument structure from conflicting perspectives to expose fallacies.
3. Consensus Verification
Only claims that survive the adversarial convergence process are stamped with a Validity Key.
Zero-Retention Protocol.
Your intellectual property is ephemeral. The system processes the signal in volatile memory and purposefully destroys the session data post-audit.
- No database persistence of manuscript text.
- Cryptographically signed Audit Artifacts.
fn verify_signal(input: Signal) -> Result:
let vectors = engine.extract(input);
match engine.adversarial_check(vectors) {
Ok(score) => sign_certificate(score),
Err(e) => reject_with_trace(e),
}
System Constraints
Logical Consistency Only
ARGUS-Thesis verifies internal logic and novelty structure. It does not verify external empirical data correctness vs the real world.
No Authorship
The system is a critic, not a writer. It will never generate manuscript prose, only structural critique.