exera provides the exera Augmented Research Companion (eARC), an AI‑native platform that acts as an autonomous, auditable co‑pilot for healthcare and life‑science research. By securely ingesting heterogeneous data such as EHRs, genomics, and scientific literature within confidential computing enclaves, eARC synthesizes findings, generates contextual hypotheses, and delivers explainable outputs to accelerate drug discovery, disease surveillance, and regulatory readiness.
Funding
Funding not disclosed
Founders
Product
Problem
Researchers and clinicians in healthcare and life sciences face overwhelming volumes of heterogeneous data—such as electronic health records, genomics, and scientific literature—making hypothesis generation, drug design, and public‑health surveillance time‑consuming and error‑prone. Existing AI tools often lack auditability, data governance, and secure execution, limiting their adoption in regulated, mission‑critical environments.
Solution
Exera delivers the exera Augmented Research Companion (eARC), an AI‑native platform that acts as an autonomous, auditable co‑pilot for research and decision‑making. eARC ingests internal and external datasets within confidential computing enclaves, applies modular AI agents to synthesize findings, and generates contextual hypotheses for therapeutic design, disease surveillance, and drug‑repurposing. The system provides explainable outputs and supports federated, API‑first integration, enabling secure collaboration across institutions. By automating literature synthesis, data analysis, and insight discovery, eARC can reduce research cycle times by up to 60 % in oncology trials and accelerate regulatory readiness. The platform is built on Exera’s Trusted Agentic AI Framework, ensuring data governance, multi‑agent orchestration, and traceable decision paths.
Target Audience
Primary customers are pharmaceutical R&D teams, biotech researchers, public‑health laboratories, and clinical decision‑support groups that require secure, explainable AI assistance for drug discovery, epidemiology, and health‑outcome analysis.
Features
- Autonomous co‑pilot that rapidly ingests and harmonizes EHR, genomics, and literature data within secure enclaves
- Modular AI agents orchestrated through a federated API, enabling flexible workflow composition and integration with existing tools
- Explainable AI outputs with audit trails to satisfy regulatory and compliance requirements
- Confidential computing architecture that protects sensitive health data during processing
- Context‑aware hypothesis generation for therapeutic molecule design, drug repurposing, and public‑health risk assessment
- Demonstrated 50–60 % reduction in time required for oncology trial data analysis and insight discovery