Reshape Biotech develops AI-powered lab robots that automate routine microbiological tasks, such as plate filling and image analysis, while capturing high-quality data for real-time machine learning insights. This technology addresses inefficiencies in laboratory workflows, enabling faster decision-making and increased throughput by standardizing data collection and analysis across experiments.
Funding
$29.3M 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.
AVFounders
Product
Problem
Microbiology labs face challenges in automating repetitive tasks like plate filling and image analysis, leading to workflow inefficiencies and slower decision-making. Manual data collection and analysis can also introduce inconsistencies, hindering the standardization of experiments and the generation of reliable insights.
Solution
Reshape Biotech offers an AI-powered robotic platform designed to automate routine microbiological tasks, streamlining lab workflows and accelerating research. The platform integrates robotic devices with a cloud-based system for real-time data capture and AI-driven analysis. By automating experiments and standardizing data collection, Reshape Biotech enables labs to increase throughput, improve data quality, and gain faster, more accurate insights. The system's machine learning capabilities empower scientists to make data-driven decisions from day one, accelerating discovery and innovation.
Target Audience
Reshape Biotech targets microbiology labs across various industries, including agriculture, industrials, food and ingredients, and personal care and cosmetics, seeking to automate experiments, improve data quality, and accelerate research.
Features
- Automated plate imaging and incubation with high-resolution image capture
- Real-time AI analysis of experimental data for immediate insights
- Cloud-based platform for seamless data capture, analysis, and sharing
- Machine learning algorithms for faster, smarter decision-making
- Standardized data collection across labs for improved reproducibility
- Integration of robotics and AI for end-to-end experiment automation
- High-throughput imaging capabilities for analyzing and capturing images at scale