Agentic evidence-grounded research assistant for biology
Alvessa integrates entity recognition, validated tool orchestration, and statement-level verification to deliver trustworthy, provenance-preserving answers to biomedical questions.
Built for trustworthy biomedical reasoning
Entity Recognition
Purpose-built ensemble combining LLMs, Flair, GLiNER, and regex patterns to identify genes, variants, drugs, and miRNAs.
Validated Tool Catalog
Pre-defined, tested tools for 20+ databases including ChEMBL, UniProt, Reactome, GWAS Catalog, and AlphaFold-ensuring consistent, reproducible results.
Statement-Level Verification
Every claim is evaluated against retrieved evidence and classified as supported, partially supported, or unsupported-with explanations surfaced to users.
Evidence Provenance
Direct citations link every statement to source records. Explore underlying data and verify claims independently.
Interactive Outputs
Rich HTML reports with 3D protein viewers, molecule renderings, and expandable evidence panels for deep exploration.
GenomeArena Benchmark
720 curated questions spanning 8 categories to evaluate genomic reasoning capabilities-freely available for community use.
Multi-agent pipeline with verification loop
Example Outputs
Druggability Comparison
Comparative assessment of SMAD2 vs SMAD3 targeting strategies, integrating chemoproteomics, structural data, and pharmacological evidence.
→Translational Target Assessment
Cross-species hypothesis evaluation combining expression profiles, protein disorder analysis, and target tractability for a longevity-associated gene.
→No Evidence, No Claims
How Alvessa handles queries with insufficient data - reporting missing information rather than generating unsupported claims.
→Resources & Documentation
Reference
@article{sokolova2025alvessa,
title = {An Evidence-Grounded Research Assistant for Functional Genomics and Drug Target Assessment},
author = {Sokolova, Ksenia and Kosenkov, Dmitri and Nallamotu, Keerthana and Vedula, Sanketh and Sokolov, Daniil and Sapiro, Guillermo and Troyanskaya, Olga G},
journal = {bioRxiv},
year = {2025},
month = dec,
doi = {10.64898/2025.12.30.697073},
url = {https://www.biorxiv.org/content/10.64898/2025.12.30.697073v1},
note = {Preprint}
}