Stock Markets February 10, 2026

Evogene Boosts Google Cloud Tie-Up; Shares Tick Up 4% on Agent Integration Plan

Company to deploy Vertex AI-powered Agents within ChemPass AI to scale small-molecule discovery for pharmaceutical and agricultural programs

By Ajmal Hussain EVGN
Evogene Boosts Google Cloud Tie-Up; Shares Tick Up 4% on Agent Integration Plan
EVGN

Evogene Ltd. (NASDAQ:EVGN) saw its stock climb 4% on Tuesday after revealing an expanded collaboration with Google Cloud to embed AI Agents into its ChemPass AI platform. The initiative will use Google Cloud's Vertex AI to automate and scale parallel molecular discovery workflows with the aim of accelerating design-make-test-analyze cycles for small-molecule products in pharma and agriculture.

Key Points

  • Evogene announced an expanded partnership with Google Cloud to integrate AI Agents into its ChemPass AI platform using Vertex AI.
  • The integration is intended to automate and scale small-molecule discovery and optimization, targeting pharmaceutical and agricultural products.
  • Evogene says the initial phase produced a generative AI foundation model that now underpins its platform and has helped drive recent collaborations.

Evogene Ltd. (NASDAQ:EVGN) shares rose 4% on Tuesday following an announcement that the computational chemistry company is broadening its collaboration with Google Cloud to incorporate advanced AI Agents into its proprietary ChemPass AI platform.

The renewed partnership centers on developing AI Agents leveraging Google Cloud's Vertex AI environment to strengthen Evogene's small-molecule discovery and optimization processes for both pharmaceutical and agricultural applications. The move builds on an earlier phase of the relationship, which Evogene and Google Cloud initiated in October 2024.

Evogene says the AI agent integration is designed to automate and scale core discovery tasks, enabling wide-ranging parallel exploration of molecular designs while compressing the time spent in design-make-test-analyze loops. According to the company, these platform enhancements are intended to raise the accuracy and success rate when designing small-molecule-based products.

"The integration of AI agents into ChemPass AI is expected to improve our speed, cost structure, and ability to run multiple discovery programs in parallel," said Ofer Haviv, President and CEO of Evogene. "We are also excited about the potential to make parts of our real-world innovation tools globally accessible through Google Cloud Marketplace. This collaboration marks for us a shift from AI models to autonomous discovery, as ChemPass AI enters a new phase of scale and execution."

Evogene noted that the first stage of its work with Google Cloud produced a generative AI foundation model that now functions as a central element of the company's platform. Evogene attributes recent partnership activity to the capabilities provided by that foundational model.

Market reaction was immediate, with the stock moving higher on the announcement. The company frames the expanded effort as a progression from model development to deploying autonomous discovery workflows, alongside an intent to broaden access by listing tools on the Google Cloud Marketplace.

The collaboration stresses automation, parallel program execution, and a focus on improving both cost and speed for small-molecule design. Evogene explicitly links these platform advances to potential gains in program throughput and success rates for its pharmaceutical and agricultural discovery pipelines.


Sectors impacted: Biotechnology, pharmaceuticals, agricultural technology, and cloud/AI infrastructure.

Risks

  • The benefits cited - improved speed, cost structure, and parallel program capability - are presented as expectations and potential outcomes rather than guaranteed results, creating execution risk for intended gains (impacts biotech and pharma R&D).
  • Making parts of Evogene's tools available via a cloud marketplace is described as potential, indicating uncertainty about timing and adoption of that distribution channel (impacts cloud platforms and commercial reach).
  • The company relies on a generative AI foundation model as a core platform element, which creates dependency risk if the model does not perform as anticipated across all discovery programs (impacts R&D efficiency in biotech and agtech).

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