Elders signs Octopusbot for AI crop forecasts after $1m raise

By Takeshi Mori · 2026-08-01

Elders brings AI forecasting inside its agronomist network

Australian grain farming has long run on two inputs: seasonal intuition and lagging data. Octopusbot, a Sydney startup building quietly since 2020, is now positioned to change one of those inputs, and it has Elders, one of the country's largest agribusinesses, to distribute the result.^[1]

Elders has signed a partnership with Octopusbot that pairs the startup's AI crop forecasting platform with the agribusiness's agronomist network across Australia.^[1] Octopusbot's forward-looking production and price signals will now reach growers through the same advisers they already rely on for crop management decisions. Elders operates across agronomy, livestock and real estate services for farmers nationwide, so that distribution is not a small thing.

Alex Greetham, Chief Agronomist at Elders, was direct about what drew the company to the deal. "Octopusbot leads the market in crop assessment and the use of AI to analyse multiple data sources," Greetham said.^[1]

First institutional money, timed to the moment

The Elders announcement arrived alongside Octopusbot's first external funding round, which closed at more than $1 million.^[1] Folklore Ventures and No Brand backed the round, giving the company its first institutional capital since Carolina Ferreira and Rodrigo Cortes founded it in Sydney in 2020. Early-stage agtech companies often struggle to sign enterprise partners before institutional validation arrives, and institutional investors want evidence of enterprise traction before they write cheques. Octopusbot appears to have threaded both at once.

Folklore Ventures published its investment thesis on its own site, detailing the platform's architecture and the founders' backgrounds.^[2] That level of public disclosure from an early-stage investor is a signal in itself.

Who built it and why

Ferreira is an electrical engineer with a cybersecurity background. Cortes spent years in supply chain roles at PepsiCo, Kirin and Heineken before the two turned their attention to agriculture.^[2] Crop forecasting is not a soft problem; it requires the kind of systems thinking that comes from building complex infrastructure. Cortes's supply chain experience gives him a clear view of where information failures cost money, in procurement, price risk and logistics, which is precisely where Octopusbot's forecasts are designed to intervene.

Ferreira framed the company's purpose in terms of timing rather than technology. "Octopusbot aims to give farmers and agribusinesses earlier, more objective information so they can make decisions with confidence rather than reacting after the market has already moved," she said.^[1] A forecast that arrives after futures markets have priced a drought is not a forecast; it is a confirmation. Octopusbot's pitch is that it moves the information far enough forward to be genuinely useful.

How the platform works

Octopusbot runs more than 10,000 interconnected AI models, drawing on satellite imagery, weather data, historical yields and commodity-market signals to produce crop production and price forecasts months ahead of traditional sources.verifiedVerified Source: folklore.vc^[2] That figure reflects the granularity required to forecast at field level across different crop types, geographies and seasonal conditions simultaneously. A single national-scale model averaging across Australia's grain belt would produce estimates that are accurate in aggregate and useless in practice.

Each model feeds into connected models, so a change in forecast rainfall in the Mallee updates not just yield projections but price signals and procurement recommendations downstream. That chain of inference is where the platform earns its value, not in any single data feed, but in the relationships between them.

During the 2024-25 season, Octopusbot's models reported an average accuracy of 95% on forecasts made seven months before harvest and 97.4% accuracy on final crop estimates.verifiedVerified Source: octopusbot.ai^[3] Both figures come from the company's own published accuracy data, and Bushletter could not independently verify them against third-party audits. The gap between the seven-month figure and the final-estimate figure is small, which suggests the models are not simply regressing toward better data as harvest approaches; they are starting from a reasonable baseline and refining it.

The market Octopusbot is moving into

The precision farming sector is valued at around $19 billion globally, yet most Australian growers still rely on periodic reports from the Australian Bureau of Agricultural and Resource Economics and Sciences and industry trade estimates for seasonal planning.^[2] Those sources are credible but slow. By the time an official production estimate is published, commercial decisions have already been made on rougher information.

Octopusbot has secured close to 100 paying customers globally since its founding in 2020, according to Folklore Ventures.verifiedVerified Source: folklore.vc^[2] That is a real commercial base for a pre-institutional startup, but it is still a small number relative to the scale of the industry it is entering. The Elders partnership is the mechanism by which that changes; Elders' agronomist network embeds the platform's outputs into conversations already happening between agronomists and growers at critical decision points in the season.

Grain traders making procurement decisions months out, growers managing price risk on forward contracts, and agribusinesses planning post-harvest logistics all operate on forecasts of some kind. Octopusbot's bet is that its models are accurate enough and early enough to be genuinely useful, and Elders has now placed its agronomist network behind that position.

Takeshi Mori

Takeshi Mori writes about technology and start-ups. He is curious about how products get built and who they are really for, and he would rather see a thing working than hear it described.