We build agentic AI infrastructure that automates the dry lab and delivers FDA-grade explainability for clinical diagnostics — collapsing months of manual R&D into hours.
Targeting the biggest automation gaps in modern biopharma — from experiment design to clinical decision support.
Biologists need AI agents that can autonomously design experiments, analyze results, and push instructions directly to robotic wet-lab platforms. We build the middleware that closes this loop — turning weeks of hand-offs into automated pipelines.
Autonomous experiment design, result analysis, and robotic platform instruction — all in a single closed loop.
Natural language pipeline execution for single-cell NGS — giving smaller biotech teams the power of a full ML team.
Deterministic, executable code output. Every agent action is verifiable — because a wrong pipetting instruction costs $10K+.
Reconciles EHR, imaging, and omics data in a unified environment — solving the challenge that plagues 81% of life science firms.
Diagnostic AI is colliding with strict regulation. Doctors and the FDA won't accept black-box models when patient lives are on the line. We make any model explainable — generating compliance-ready audit trails on top of existing AI systems.
An API that sits atop any black-box vision or genomic model to auto-generate FDA-compliant audit trails for regulators.
SHAP, LIME, and attention mechanisms adapted for multimodal medical data — turning confidence scores into clinician-readable reasoning.
Built-in explainability frameworks that satisfy new mandates from global regulators — avoiding heavy penalties for non-compliance.
XAI outputs presented in clinician-friendly formats that fit high-stress hospital workflows without causing alert fatigue.
| Feature | Agentic Scientist | Responsible AI (XAI) |
|---|---|---|
| Primary End User | Biotech Researchers, Bioinformaticians | Radiologists, Clinicians, Regulators |
| Market Driver | R&D Efficiency & Cost Reduction | FDA / EU AI Act Compliance & Trust |
| Technical Focus | Multi-agent orchestration, Data Pipelines | Interpretability, Bias Mitigation, Auditing |
| Sales Cycle | Faster — B2B SaaS to Biotech | Slower — Hospital IT & Regulatory Buy-in |
| Market Size (2030) | $7.75B (bioinformatics) | $21.06B (XAI healthcare) |
| Key Challenge | Data Fragmentation (EHR, Omics, Imaging) | Performance vs. Transparency Trade-off |
| Regulatory Burden | Moderate | High (FDA, EU AI Act) |
Autonomous agents that design, execute, and iterate experiments — connected directly to wet-lab robotic platforms via deterministic APIs.
Interoperability engine that reconciles EHR, imaging, and omics data into a single queryable environment — eliminating the #1 bottleneck in life sciences AI.
A post-hoc explainability layer using SHAP, LIME, and attention mechanisms — generating human-readable, FDA-compliant reasoning from any upstream model.
Clinician-ready dashboards and audit trails that integrate into existing hospital systems without introducing alert fatigue or workflow friction.
Join leading biotech startups and research institutions in our early access program. We're onboarding select partners to co-develop and validate our agentic pipelines.