Yoneda Labs provides AI‑driven software that predicts reliable reaction conditions and accelerates process optimization for chemists.
Funding
$4M 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.
9OFounders
Product
Problem
Chemists often face lengthy, costly trial‑and‑error cycles when trying to identify optimal reaction conditions for new or existing syntheses, leading to delayed projects, high material waste, and limited capacity for process development.
Solution
Yoneda Labs offers AI‑driven software tools that predict reliable reaction conditions, accelerate process optimization, and automate LCMS data analysis. Yoneda Predict leverages a model trained on tens of thousands of experimentally generated data points to suggest conditions that are guaranteed to work for novel reactions, cutting lead‑compound nomination time in half. Yoneda Optimize applies statistical and machine learning algorithms to design minimal experimental batches, enabling chemists to reach near‑optimal yields within days instead of months while reducing material consumption and environmental impact. Yoneda Analyze automatically detects, integrates, and annotates overlapping LCMS peaks, visualizing complete datasets on a single page and saving several hours of manual labor per plate. The suite integrates with existing laboratory workflows through a desktop application and cloud‑based analytics, delivering actionable insights without extensive setup.
Target Audience
Primary customers are process chemists and R&D teams in pharmaceutical, agrochemical, and specialty chemical companies who need rapid, data‑driven reaction development and analytical automation.
Features
- Predictive modeling trained on >10,000 wet‑lab reaction data points to recommend conditions that reliably succeed
- Bayesian and machine‑learning optimization algorithms that identify optimal parameters in 2–3 experimental batches
- Automated LCMS spectrum processing that deconvolutes overlapping peaks, assigns masses, and presents results in a unified dashboard
- Desktop application with simple installation and guided workflow for first‑time users
- Cloud‑hosted analytics pipeline that provides yield forecasts, cost and environmental impact estimates, and real‑time progress tracking
- Compatibility with common chemical descriptor libraries to enhance model accuracy for custom substrates