Zynoviq Solutions
ZYNOVIQSOLUTIONS

INNOVATION LAB

MoleculeForge

ML-Accelerated Material Discovery

Research PhaseGlobal TAM: $4BAdvanced Materials & Chemical R&D

The Problem

5-10 Years and $50-100M Per New Material

Material discovery is painfully slow and expensive, with 99% of synthesized candidates failing while first-principles simulations limit the design space that can be explored.

Decade-Long Discovery Cycles

Discovering new functional materials (OLED emitters, battery electrolytes, specialty chemicals) takes 5-10 years and $50-100M per successful candidate.

5-10 years and $50-100M per successful material discovery

99% Candidate Failure Rate

99% of synthesized candidates fail performance, stability, or manufacturability requirements, representing a massive waste of lab time, reagents, and researcher capacity.

99% of synthesized candidates fail to meet requirements

Simulation Bottleneck

Molecular property prediction from first principles (DFT, MD simulations) takes days per candidate, limiting the chemical design space that can be explored to tiny fractions.

Days of compute per candidate with first-principles methods

Manual Synthesis Planning

Synthesis route planning is done manually by experienced chemists. Optimal routes are often missed because the combinatorial space of possible reactions is too vast for human intuition.

100M+ known reactions impossible for humans to fully search

How It Works

AI-Accelerated Material Design Pipeline

MoleculeForge predicts material properties, generates optimized candidates, and plans synthesis routes to compress discovery timelines from years to months.

1000x faster than DFT

Property Prediction

Predicts material properties (emission wavelength, thermal stability, solubility, conductivity) from molecular structure using graph neural networks trained on 10M+ data points.

1000x larger design space

Inverse Molecular Design

Generates candidate molecules optimized for target properties using generative models that explore chemical space orders of magnitude faster than traditional screening approaches.

Optimal pathways from 100M+ reactions

Synthesis Route Planning

Designs optimal synthesis pathways by searching retrosynthetic trees against a database of 100M+ known reactions, reagent availability, and cost constraints.

Key Metrics

Market Opportunity

$4B
Global TAM
$20-60M/yr
Annual Value
Research
MVP Timeline
30-60
Target Customers

Interested in MoleculeForge?

Contact our innovation team to explore ML-accelerated material discovery for your R&D pipeline.