Helical AI provides a cloud‑based Virtual AI Lab that lets biologists design and run in‑silico experiments through a no‑code visual interface, leveraging integrated biological foundation models for instant predictions. The platform also includes a Model Factory with VS Code integration and managed compute for ML engineers to fine‑tune models, and an interactive dashboard that delivers results directly into drug discovery decision workflows.
Funding
$3.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Biologists and pharmaceutical researchers often must write code or rely on specialized data scientists to set up and run AI-driven experiments, slowing hypothesis testing and limiting scalability of discovery workflows.
Solution
Helical AI offers a cloud‑based Virtual AI Lab that lets biologists design, execute, and evaluate in‑silico experiments through a graphical interface without writing code. The platform integrates large biological foundation models and provides automated inference pipelines that generate experimental predictions at the speed of model execution. For machine‑learning engineers, the Model Factory supplies a production environment with native VS Code integration, managed compute resources, and experiment tracking to personalize and align models to specific projects. Results are presented in an interactive dashboard that connects model outputs directly to decision‑making workflows, enabling rapid iteration from hypothesis to actionable insight. Large pharma R&D teams use the system across target identification, biomarker discovery, and therapeutic design, accelerating the overall drug discovery timeline.
Target Audience
Primary users are biologists and research scientists in large pharmaceutical R&D organizations, as well as machine‑learning engineers who develop and customize AI models for drug discovery pipelines.
Features
- No‑code experiment builder allowing biologists to define perturbations, datasets, and analysis pipelines via a visual interface
- Integrated biological foundation models that run inference instantly, delivering predictions for cellular, molecular, and phenotypic outcomes
- Model Factory with VS Code plug‑in, scalable compute provisioning, and built‑in experiment tracking for model fine‑tuning and alignment
- Interactive results dashboard that visualizes predictions, confidence metrics, and links directly to downstream decision workflows
- Secure, cloud‑hosted environment with role‑based access control and audit logging to meet pharmaceutical data governance standards
- API and export tools for seamless integration of model outputs into existing R&D data platforms and ELN systems