Evogene Ltd. (EVGN): 5 FORCES Analysis [Nov-2025 Updated]

You're looking at Evogene Ltd. (EVGN) right now, and honestly, the picture is sharp: they've made a major pivot to their ChemPass AI platform for small molecule discovery, but they're doing it while holding a market capitalization of only around $10.2 million as of late 2025. That small base, paired with first nine months 2025 revenue of just $3.5 million, means their bargaining power against big customers like Bayer and Corteva is definitely low, and rivalry with internal R&D teams at those giants is fierce. We need to map out exactly how this AI-first strategy fares against the five forces-from the threat of substitutes like traditional screening to the high barriers for new entrants, which we saw evidenced by the $3.5 million sale of MicroBoost AI-so you can see the real risk and reward profile here.

Evogene Ltd. (EVGN) - Porter's Five Forces: Bargaining power of suppliers

When you look at Evogene Ltd.'s supplier landscape, you see a clear split: the digital/intellectual capital side versus the physical/agricultural input side. Honestly, the power dynamic is quite different for each.

Core supplier power is low since ChemPass AI is Evogene's proprietary technology. This engine is the real moat here. Evogene's in-house algorithm teams developed this foundation model, which internal computational analysis shows delivers approximately 90% precision in successful, novel molecule designs, a massive leap from the approximately 29% precision seen in traditional GPT AI-models. This model was trained on a proprietary dataset comprising about 38 billion molecular structures. When the core value driver is internally developed and outperforms general models so significantly, the supplier power for the technology itself is negligible.

Highly specialized AI and computational biology talent commands significant compensation, raising labor costs. You know how it is in this field; top-tier talent isn't cheap. Evogene addressed this head-on as part of a strategic realignment. During the fourth quarter of 2024 and the beginning of 2025, Evogene established an expense reduction plan, leading to a reduction of ~30% in headcount, which was completed by the end of Q1 2025. This focus on capital efficiency is reflected in the reported expenses. For instance, General and administrative expenses for the third quarter of 2025 decreased to approximately $1.1 million compared to approximately $2.8 million in the same period of the previous year, primarily due to decreased expenses in Casterra and Evogene, which includes lower personnel costs. Here's the quick math: managing headcount directly impacts the cost of securing that specialized expertise.

Reliance on major cloud computing providers (e.g., Google Cloud collaboration) creates a dependency, but competition exists. Evogene's generative AI foundation model (version 1.0) was developed in collaboration with Google Cloud, and the model was trained and deployed using their advanced AI infrastructure. This partnership signifies a reliance on a single major infrastructure supplier for the heavy computational lifting required by ChemPass AI. However, the market for hyperscale cloud services remains competitive, meaning Evogene isn't locked into one vendor indefinitely, though switching costs would be substantial given the model's deployment architecture.

Suppliers of raw materials for Casterra's castor seed production are fragmented, limiting their power. Casterra built its genetic assets based on a broad collection of over 300 castor lines sourced from over 40 different geographic and climatic regions. This diversity in genetic sourcing suggests a wide base for initial inputs. Furthermore, the operational side, involving local growers in Kenya, appears fragmented, as evidenced by a past issue where a provision for doubtful debt was recorded for one of Casterra's seed suppliers in 2024. The fact that the issue was isolated to one supplier, rather than a systemic supply chain failure, supports the view that the supplier base for physical inputs is not highly concentrated.

Here is a snapshot of the key figures related to Evogene Ltd.'s supplier dynamics as of late 2025:

The bargaining power of these suppliers breaks down based on what they provide:

• Technology/IP: Power is very low; Evogene's ChemPass AI is proprietary.
• Specialized Labor: Power is moderated by Evogene's cost-cutting actions, including the ~30% headcount reduction.
• Cloud Computing: Power is high due to dependency on a major provider like Google Cloud for core AI infrastructure.
• Agricultural Inputs: Power is low due to the fragmented sourcing of over 300 genetic lines and reliance on local growers.

Finance: review Q3 2025 personnel cost allocation against the $1.1 million G&A spend by next Tuesday.

Evogene Ltd. (EVGN) - Porter's Five Forces: Bargaining power of customers

You're analyzing Evogene Ltd. (EVGN) and the power its customers hold, which is a critical lens for understanding near-term commercial risk. Honestly, when you look at the revenue base, the leverage these buyers have is quite pronounced.

The bargaining power of customers for Evogene Ltd. is decidedly high. This stems from the nature of its key relationships, particularly within the agricultural chemical sector where its AgPlenus activity has historically engaged with giants.

Customers hold strong negotiating leverage, which is amplified by Evogene Ltd.'s relatively small scale of operations. For the first nine months of 2025, Evogene Ltd.'s total revenues amounted to approximately $3.5 million. This small revenue base relative to the potential size of its partners means each contract carries significant weight.

The threat of backward integration is a constant consideration. Large, global agricultural and pharmaceutical companies possess the capital and, increasingly, the internal AI capabilities-like Evogene Ltd.'s ChemPass AI platform-to potentially develop similar generative design or predictive biology solutions internally. This capability acts as a credible ceiling on the pricing power Evogene Ltd. can command in negotiations.

The power dynamic is further illustrated by looking at the specific revenue streams and the entities involved:

• Major customers are large, global companies like Bayer and Corteva.
• Past revenue recognition from these partners, such as a one-time payment from Bayer in Q1 2024, highlights the lumpiness and dependency on these key relationships.
• Strategic engagements with Bayer and Corteva continue, validating the technology but also keeping them in a strong negotiating position.

The Casterra subsidiary presents a slightly different, but still concentrated, buyer power scenario. While Casterra's seed sales provided a primary revenue driver in Q1 2025, its sales are directed toward a limited number of industrial partners focused on the biofuel market.

For instance, the recent strategic collaboration with Fantini Italia, focused on large-scale commercial castor cultivation, depends on integrated solutions for industrial-scale supply. When sales volume is concentrated among a few industrial partners, those partners gain significant purchase volume power over Casterra Ag, Ltd.

Here's a quick look at the financial context framing this buyer power:

Finance: draft 13-week cash view by Friday.

Evogene Ltd. (EVGN) - Porter's Five Forces: Competitive rivalry

You're looking at Evogene Ltd. (EVGN) in a market that is absolutely flooded with deep-pocketed players. The rivalry here isn't just a minor headwind; it's a defining feature of the operating environment, especially now that Evogene Ltd. is laser-focused on its ChemPass AI platform.

High rivalry exists against internal R&D divisions of multi-billion-dollar pharmaceutical and agricultural giants.

Honestly, competing against the internal discovery engines of Big Pharma and AgChem means you are fighting an uphill battle on resources. These giants can deploy capital that dwarfs Evogene Ltd.'s entire market valuation. Consider the potential prize: the pharmaceutical small molecule drug market, driven by AI, is projected to reach nearly $190 billion by 2034. That massive potential draws continuous, massive internal investment from established players who don't need to worry about quarterly cash burn in the same way Evogene Ltd. does.

Evogene competes with a growing number of well-funded, AI-first drug discovery startups globally.

The competition isn't just from the incumbents; it's from nimble, well-capitalized newcomers. The funding environment for AI drug discovery, while cyclical, saw a strong rebound, with investment growing 27% in 2024 to reach $3.3 billion. These startups are attracting serious venture capital, which directly translates into competitive pressure on talent and technology development speed. Here's a quick look at the scale of funding some rivals are pulling in, which you need to keep in mind when assessing Evogene Ltd.'s competitive position:

What this estimate hides is that many of these firms are focused on platform development, just like Evogene Ltd., meaning they are competing for the same partnership opportunities.

The company's small market capitalization of around $10.2 million (as of late 2025) limits its ability to compete on scale.

To be fair, Evogene Ltd.'s size is a major constraint in this high-stakes arena. As of November 25, 2025, the market capitalization stood at approximately $9.96 million. This small base means any significant R&D misstep or delay in partnership milestones has a much larger impact on perceived value than it would for a larger firm. Look at the financials from the nine months ending September 30, 2025:

• Total Revenues: approximately $3.5 million.
• Total Operating Expenses (Q3 2025): approximately $2.9 million.
• Operating Loss (9 months 2025): approximately $8.8 million.
• Consolidated Cash Position (Sept 30, 2025): approximately $16.0 million.

The cash position of $16.0 million provides a runway, but the operating loss rate means scale is definitely a factor against competitors with billions in the bank.

The strategic shift to focus on ChemPass AI means intense competition in both the ag-chem and pharma small molecule spaces.

Evogene Ltd. is now squarely in the crosshairs of the small molecule discovery battle, using ChemPass AI. This focus means direct competition with every entity using AI to design novel small molecules for human health or crop protection. For instance, in Q1 2025, Evogene Ltd.'s R&D expenses were approximately $3.2 million. This level of spend must generate superior, faster results than competitors who are also leveraging AI, like those mentioned above who are securing nine-figure funding rounds. The rivalry is about who can generate the most validated, de-risked candidates first.

Finance: draft 13-week cash view by Friday.

Evogene Ltd. (EVGN) - Porter's Five Forces: Threat of substitutes

You're looking at the competitive landscape for Evogene Ltd. (EVGN) as of late 2025, and the threat of substitutes is definitely a major factor, especially given the company's strategic pivot toward a focused, AI-driven model centered on ChemPass AI. We need to look at alternatives across both the pharma and ag-tech segments.

Traditional, Non-AI Drug Discovery Methods

Honestly, the established way of doing things still poses a threat, even as AI adoption accelerates. Traditional drug discovery remains a long haul, often requiring more than a decade and billions of dollars for a single approval. Contrast that with the market Evogene is targeting: the global AI in Drug Discovery Market was valued at USD 6.93 billion in 2025, and it's projected to hit USD 16.52 billion by 2034 at a CAGR of 10.10%. This growth shows the industry is moving away from the old ways, but the sheer inertia and existing infrastructure of traditional high-throughput screening methods mean they are definitely a viable substitute for any new AI-derived molecule in the near term. By 2025, it's estimated that only 30% of new drugs will be discovered using AI, leaving a massive 70% still relying on older, established, albeit slower, processes.

Direct Substitutes in the Biofuel Market (Casterra)

For Evogene's subsidiary, Casterra, the threat comes from other established oil crops in the biofuel space. Casterra is developing high-yielding castor bean seeds as a sustainable feedstock, especially since the EU banned palm oil and soybean as biofuel feedstock beginning in 2023 through 2030. Still, soy, palm, and canola are the incumbents. The global castor market itself was valued at USD 1.083 billion in 2025, but that's against the much larger vegetable oil markets. India, for instance, accounts for approximately 70% of global castor production, showing where the bulk of the supply chain power lies outside of Casterra's specialized, high-yield varieties. If commodity prices for these alternatives drop significantly, the economic incentive to switch to castor oil biofuels lessens, even with its 'green' benefits.

Here's a quick look at the market context for these substitutes:

Competing AI Platforms

Evogene is betting big on its ChemPass AI engine, but you can't ignore the competition in the AI space itself. Other platforms are emerging not just for small molecules, which is Evogene's current focus, but also for genetic elements and microbes. This means alternative solutions exist for the agricultural side as well. For example, Evogene's H1 2025 revenues were $3.2 million, up from $2.3 million in H1 2024, but the Q3 2025 revenue of $312,000 missed the estimated $650,000, suggesting market penetration against established AI players is still a climb. The threat here is that a competitor might develop a superior AI for genetic elements or microbes faster, undercutting Evogene's subsidiaries like Lavie Bio (prior to its asset sale) or AgPlenus.

Low-Cost Generic/Off-Patent Substitutes in Seeds

In the seed business, the cost of entry for a farmer using a generic or off-patent seed variety is a constant, low-cost substitute for the premium biotech products Evogene's subsidiaries develop. The price gap is significant, which directly impacts adoption rates for new technology. You see this clearly when comparing seed prices:

• GMO corn seeds average around $250 per bag in the U.S.
• Non-GMO corn seeds average around $150 per bag.
• Commodity soybean seeds are priced $40-$60 per bag.
• Specialty or high-protein soybean seeds can cost $75 or more per bag.

This price difference means that if the expected yield increase or input reduction from a new biotech trait doesn't substantially outweigh the initial cost premium, farmers will stick with the cheaper, off-patent options. For instance, the $100 per bag difference between GMO and non-GMO corn seeds is a real hurdle for adoption, regardless of the underlying science.

Finance: review the Q4 2025 cash burn rate against the $16.0 million cash position as of September 30, 2025, to model runway sensitivity to slower-than-expected adoption due to these substitute threats.

Evogene Ltd. (EVGN) - Porter's Five Forces: Threat of new entrants

You're looking at the barrier to entry for Evogene Ltd. (EVGN), and honestly, it's a mixed bag. Building something proprietary and validated, like Evogene's Computational Predictive Biology (CPB) platform, isn't a weekend project. It requires significant capital and time to reach the level of sophistication Evogene has achieved. Think about the scale: their ChemPass AI foundation model is built on a dataset of approximately 38 billion molecular structures, which is a massive undertaking in data acquisition, cleaning, and training. While building an advanced, enterprise-grade AI solution might start around $150,000 and easily exceed $1M (Source 13), a platform validated across multiple life science domains like Evogene's CPB likely represents an investment far exceeding these general estimates, especially when factoring in the specialized biological expertise needed to make the AI predictive rather than just generative.

The regulatory environment definitely helps keep the riff-raff out, particularly in the pharma and agriculture spaces. Navigating complex regulatory frameworks is a known hurdle for AgriTech startups, especially concerning areas like genetic engineering, which is a key focus for Evogene's subsidiaries (Source 5). In fact, the strong regulatory pressure in agriculture means that only business structures with a broad organizational base can meet the current challenges (Source 11). This acts as a significant moat. To put the market size in perspective, the North American AgTech sector was estimated to be worth $11.46 billion in 2025 (Source 12), but getting a new product through the necessary trials and approvals is a multi-year, multi-million-dollar slog that deters many smaller players.

Still, the market shows that proven technology engines command a high price, which validates the effort but also shows a path for new entrants if they can prove their tech. Evogene's own transaction history confirms this: the sale of the MicroBoost AI for Ag tech-engine to ICL Group Ltd. in July 2025 was for approximately $3.5 million (Source 3, 6). That's a concrete number for a specialized, validated AI engine for agriculture. It shows that a proven asset has a clear market value, but it also means a new entrant needs to secure similar funding or validation to compete directly.

On the flip side, the computational barrier is definitely getting lower. New entrants benefit from increasingly accessible, powerful open-source AI tools. While Evogene boasts 90% precision in novel molecule design using its proprietary model, compared to 29% for traditional GPT AI models (Source 9), a startup can certainly spin up an MVP using readily available, powerful open-source models without the initial multi-billion-molecule training investment. Here's a quick look at the cost disparity for building versus buying a foundational AI capability:

The threat is mitigated by the validation and integration Evogene has achieved across its tech-engines. A new entrant might have the code, but they don't have the years of biological data integration or the established IP portfolio. The barriers to entry are less about the raw compute power today and more about the proprietary, validated knowledge layer on top of it. Still, you can't ignore the accessibility factor:

• Open-source models lower the initial software development cost.
• Fewer large M&A deals in AgTech in 2025 mean less capital is being deployed by incumbents (Source 12).
• The need for standardized, quality data remains a major hurdle for any new AI player (Source 19).
• Regulatory complexity favors established organizational bases over new entrants.

Finance: draft a sensitivity analysis on the cost of a 12-month delay in CPB platform validation by next Tuesday.