Co-Founder & CEO/President
Revr
Revr provides a cloud‑based platform that uses advanced machine‑learning and high‑performance computing to generate and evaluate protein sequences at scale. Users specify functional targets and receive candidate designs optimized for stability, activity, and manufacturability, with integrated simulation tools and an API/web interface for seamless R&D workflow integration.
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Updated 5 months ago
Funding
Raised to date
$11.4MRaised 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.
Funding rounds are not available yet.
Founders
Product
Problem
Designing functional proteins with desired properties is time‑consuming and often limited by low‑throughput experimental methods and inaccurate computational models, leading to high costs and slow progress in biotechnology and therapeutic development.
Solution
Revr offers a cloud‑based platform that leverages advanced machine‑learning algorithms and high‑performance computing to generate and evaluate protein sequences at scale. Users input target functional specifications, and the system produces candidate designs optimized for stability, activity, and manufacturability. Integrated simulation tools assess structural feasibility, while an automated scoring pipeline ranks designs for experimental validation. The platform provides an API and web interface for seamless integration into existing R&D workflows, accelerating the iteration cycle from concept to prototype.
Target Audience
Primary customers are biotech companies, pharmaceutical R&D teams, and academic laboratories that require fast, reliable protein engineering for therapeutics, enzymes, or synthetic biology applications.
Features
- Deep generative models trained on large protein structure and function datasets for rapid sequence generation
- High‑throughput in silico screening using physics‑based simulations and AI‑driven stability predictions
- Automated design optimization loops that balance multiple objectives such as affinity, solubility, and expression yield
- RESTful API and web dashboard for batch submission, result visualization, and export of design files
- Scalable cloud infrastructure that allocates GPU resources on demand to handle large design campaigns