Motif is an AI‑driven research assistant that ingests full‑text scientific papers, extracts biomarker associations and cross‑references each finding against more than 50 specialized databases. Users ask natural‑language questions and receive structured, citation‑linked biomarker data, evidence scores, and a visual, cumulative knowledge graph that can be exported in formats such as PDF, CSV, GraphML, or Neo4j for grant writing, target selection, and diagnostic development.
Funding
Funding not disclosed
Founders
Product
Problem
Biomedical researchers spend weeks manually reviewing literature and cross-referencing dozens of databases to identify and validate biomarkers, which delays target selection, diagnostic development, and grant preparation.
Solution
Motif provides an AI‑driven research assistant that ingests full‑text scientific papers, extracts biomarker associations, and automatically cross‑references each finding against more than 50 specialized clinical, genomic, and regulatory databases. Users submit natural‑language research questions and receive a structured knowledge base that includes citation‑linked biomarker data, evidence scores, and a visual, cumulative knowledge graph. The platform supports follow‑up Q&A, generates grant‑ready summaries, and exports results in formats such as PDF, CSV, GraphML, and Neo4j, enabling seamless integration with existing workflows and team collaboration.
Target Audience
Motif serves drug discovery teams, diagnostic developers, and academic researchers who need rapid, citation‑backed biomarker insights for target prioritization, assay development, and grant writing.
Features
- Full‑text extraction from PubMed, PMC, and Europe PMC with AI‑based entity and relationship detection covering 80+ biomarker types across 15 categories
- Three‑tier cross‑database validation against 50+ trusted sources (e.g., CIViC, ClinVar, PharmGKB, gnomAD, Reactome, FDA)
- Cumulative, team‑shared knowledge graph that visualizes biomarker‑disease‑pathway connections and can be exported to Cytoscape or Neo4j
- Natural‑language Q&A interface for follow‑up queries, delivering AI‑synthesized summaries with PMID citations and evidence scores
- Automated generation of grant‑ready documentation (PDF reports, Excel tables, PowerPoint decks) with fully formatted citations (APA, Vancouver, BibTeX, RIS)
- Enterprise features including API access, programmatic exports, secure data handling, version control, and audit trails for compliance
- Streaming pipeline that streams results as they are processed, reducing latency between query submission and insight delivery