Tensoric Research
Autonomous scientific exploration across millions of papers, formal proof checking, and reproducible empirical analysis.
Tensoric Research conducts deep scientific investigations across peer-reviewed publications and clinical/genomic datasets. It synthesizes literature, validates mathematical lemmas using formal verification engines (Lean 4, Z3), and outputs reproducible computational workflows with every citation verified against primary sources.
Runtime execution
in real environments.
Synthesize recent 2025-2026 breakthroughs in 4-bit transformer quantization for edge devices.
Engineered for
mission-critical accuracy.
Rigorous Primary Source Grounding
Every scientific assertion links directly to an active DOI, PubMed ID, or arXiv identifier. Unsubstantiated claims are rejected by the validation kernel.
Interactive Theorem Proving
Integrates with Lean 4 and Z3 SMT solvers to evaluate mathematical theorems, eliminating reasoning gaps in formal specifications and algorithmic proofs.
Self-Executing Computational Notebooks
Generates containerized Python/Jupyter workflows with pinned dependencies and dataset downloaders to replicate statistical experiments on demand.
Cross-Discipline Synthesis
Unifies insights across biotechnology, machine learning, physics, and computational biology to identify cross-domain hypotheses and unexplored solutions.
Deterministic pipeline
step by step.
Deep Literature Retrieval & Filtering
Queries scientific APIs and vector embeddings to construct a high-relevance citation corpus.
Formal Claim & Theorem Verification
Transcribes mathematical arguments to Lean 4 code and validates truth values against axiom sets.
Synthesized Report & Code Package
Compiles a verified scientific brief with cited bibliographies and executable experimental code.
System specifications &
runtime constraints.
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