Kallyope
Deciphering the gut-brain axis through AI-driven drug discovery for transformative therapeutics.
Unifying life sciences data into an actionable knowledge graph for accelerated drug discovery.
The Euretos AI Platform is a sophisticated computational biology ecosystem designed for pharmaceutical and biotech researchers. At its core, it leverages one of the world's largest integrated Knowledge Graphs (KG), semantically linking over 200 public and proprietary data sources including PubMed, Ensembl, UniProt, and clinical trial registries. The platform’s architecture utilizes high-dimensional vector embeddings and semantic reasoning to identify non-obvious relationships between genes, diseases, drugs, and phenotypes. In the 2026 market, Euretos positions itself as a 'Human-in-the-loop' AI system, prioritizing transparency through direct evidence traceability—where every AI-generated hypothesis is backed by specific literature citations or experimental data points. This mitigates the 'black box' risk inherent in standard LLMs. Technically, the platform supports multi-omics data integration, allowing researchers to overlay their proprietary lab results onto the global knowledge graph to identify novel targets, validate biomarkers, or predict drug repurposing opportunities with high statistical confidence.
A multi-layered graph database linking 200+ disparate sources using a standardized semantic schema.
Deciphering the gut-brain axis through AI-driven drug discovery for transformative therapeutics.
Accelerating drug discovery through an end-to-end generative AI pipeline for target identification, molecular design, and clinical trial prediction.
The industry-standard interactive visualization tool for integrated exploration of large-scale genomic datasets.
Unlocking the causal biology of disease through Gemini Digital Twins.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
AI models that provide a traceable path of evidence (citations) for every predicted relationship.
Computational simulation of gene knockouts and their effects on metabolic pathways.
Secure mechanism to upload and map internal lab data onto the global graph without data leakage.
Natural language processing optimized for biomedical nomenclature to ingest unstructured text.
Interactive GUI for exploring complex multi-protein interaction networks.
Algorithms that match drug signatures with disease signatures across different indications.
Lack of experimental data for niche conditions.
Registry Updated:2/7/2026
Finding new indications for existing approved compounds.
High failure rates in Phase II due to poor patient stratification.