CeleriLab offers an AI‑driven infrastructure for microbiome research, providing a curated, searchable database of over 1,400 public human gut shotgun metagenomic studies that are standardized for cross‑study comparability. The platform includes unified processing pipelines, rich metadata, and AI tools for biomarker discovery and patient stratification, and it can integrate private datasets to support large‑scale, reproducible analyses for academic and biotech researchers.
Funding
Funding not disclosed
Founders
Product
Problem
Microbiome researchers struggle with fragmented, inconsistently processed public gut metagenomic datasets that lack standardized metadata, making large‑scale meta‑analysis, reproducibility, and biomarker discovery time‑consuming and error‑prone.
Solution
CeleriLab provides an AI‑driven infrastructure that curates and standardizes public human gut shotgun metagenomic studies into a searchable, metadata‑rich database. The platform applies unified processing pipelines to ensure cohort‑level comparability across studies, enabling researchers to locate relevant datasets with a single query. Built on this foundation, CeleriLab offers AI tools for biomarker identification and patient stratification on aggregated, high‑quality data. The service is designed to integrate private datasets and support co‑design of analysis workflows with early‑adopter research teams, accelerating reproducible microbiome research.
Target Audience
Primary customers are academic microbiome research groups and biotech companies that need reliable, large‑scale gut microbiome datasets and AI‑enabled analysis tools for biomarker discovery and clinical translation.
Features
- Curated, searchable database of >1,400 publicly available human gut shotgun metagenomic studies, updated weekly
- Standardized processing pipeline that harmonizes raw reads and metadata for cross‑study comparability
- Unified metadata schema with clean, structured annotations to facilitate cohort assembly
- AI analysis modules for biomarker discovery, patient stratification, and large‑scale statistical modeling
- Ability to incorporate private datasets alongside public studies for comprehensive analyses
- Collaborative roadmap where research teams can co‑design workflows and model development