Bindwell

What do they actually do

Bindwell is an R&D company using in‑house AI models and a small wet lab to discover new pesticide candidates. They run structure prediction to identify binding sites, then apply protein–ligand and protein–protein affinity models to rank chemical and biological candidates. Top hits are synthesized or ordered and tested in their San Carlos lab; validated data is fed back to improve the models. They are currently working on targets such as Spodoptera frugiperda and publish parts of their stack openly, including APPT (protein–protein affinity) and PLAPT (protein–ligand affinity) models and code (homepage, APPT post, APPT repo, PLAPT repo).

They are not selling an off‑the‑shelf SaaS product today; their primary users are internal, with external researchers able to run the open models and engage for early collaborations. Recent seed funding is aimed at expanding lab capacity, hiring biology/ML staff, and advancing at least one proprietary pesticide candidate beyond model outputs into deeper validation (BusinessWire, TechCrunch, “Defeating pests with AI”).

Who are their target customer(s)

• Large agrochemical R&D teams seeking new active ingredients: Long, costly discovery cycles and pressure to deliver target‑specific, lower‑toxicity chemistries; need faster triage and early validation to de‑risk programs (Bindwell post, BusinessWire).
• Specialty biopesticide startups: Small labs and limited screening budgets; need affordable ways to find and prioritize candidate molecules or proteins, plus some wet‑lab support to show traction (APPT repo, PLAPT repo, APPT post).
• Contract research organizations and mid‑size in‑house discovery groups: High assay costs and throughput limits; need clearer confidence about which compounds to synthesize and test to avoid wasted experiments (APPT repo, PLAPT repo, APPT post).
• Academic pest‑biology and protein‑engineering labs: Lack of turnkey binding prediction tools and budgets for commercial platforms; need open code/weights to reproduce or extend results locally (APPT repo, PLAPT repo, APPT post).
• Crop protection product managers at companies selling to farmers: Need differentiated, registrable products that meet tightening safety/environmental expectations; seek target‑specific candidates to feed into formulation and registration pipelines (homepage, BusinessWire).

How would they acquire their first 10, 50, and 100 customers

• First 10: Direct outreach to a handful of biopesticide startups, academic labs, and 1–2 CROs/mid‑size ag R&D teams; run waived‑fee pilots that include in‑silico ranking plus a small number of in‑lab assays, using the open APPT/PLAPT repos and write‑ups as proof points (APPT repo, PLAPT repo, APPT post).
• First 50: Package 1–2 offering tiers (short de‑risking pilot; larger lead‑ID package), convert pilot users to paid projects, and publish case studies showing reduced wet‑lab assays; scale targeted outreach via email/LinkedIn, webinars with CRO partners, and selective conferences.
• First 100: Build a small BD and field‑science team to sell standardized license + lab‑service bundles; introduce clear per‑project or subscription pricing and secure co‑development/licensing deals with a few large agro firms; expand lab throughput and bring in regulatory/field expertise using seed funding (BusinessWire, TechCrunch).

What is the rough total addressable market

Top-down context:

Global crop‑protection spending is roughly USD 80–85B/year, representing the downstream market that ultimately buys products discovered by companies like Bindwell (report 1, report 2). The broader agri‑chem industry generated about USD 396B in 2024 with R&D at ~7–10% of revenue, indicating tens of billions spent annually on discovery and development (Infosys).

Bottom-up calculation:

Using 7–10% R&D intensity on USD 396B yields USD 27.7–39.6B in annual R&D, and industry data suggests ~57.7% of R&D goes to research and development of new active ingredients. That implies a discovery/early‑development spend of ~USD 16.0–22.9B/year that tools and early validated candidates can target (Infosys, CropLife/AgbioInvestor).

Assumptions:

• R&D intensity of 7–10% applies broadly across major agro‑chem firms in 2024 and is a reasonable proxy for near‑term spend accessible to vendors.
• The ~57.7% share for research + development of new active ingredients maps to the discovery/early‑development work Bindwell can sell into.
• Bindwell can reach a portion of this budget via pilots, collaborations, and licensing without needing to fund full registration, manufacturing, and distribution upfront.

Who are some of their notable competitors

• AgPlenus (Evogene): Computational discovery company focused on new agrochemical modes of action, backed by Evogene’s predictive biology platform; competes for small‑molecule crop protection discovery partnerships.
• Enko: Crop‑protection company using modern discovery tools (including DNA‑encoded libraries and computation) to develop new active ingredients; notable for pharma‑style discovery applied to ag.
• Oerth Bio: Develops targeted protein degraders for agriculture; an alternative next‑gen modality aiming for higher specificity and new modes of action.
• GreenLight Biosciences: Develops RNA‑based crop protection products; offers a non‑traditional, target‑specific approach that competes with novel chemical/biological actives.
• Provivi: Produces pheromone‑based pest control solutions; not an AI discovery shop but a notable alternative to conventional insecticides targeting many of the same end markets.