What if your next employee isn’t a person—but an AI that certifies seed fields, drafts SOPs, and rewrites the rules of farming in real time?
Brock Moir doesn’t just believe in artificial intelligence—he builds it, shapes it, deploys it. And if you’re in the seed business, he’s probably already built something that’s going to change the way you work.
Physicist-turned-agricultural-technologist, Moir is on a mission to drag farming into the algorithmic age. From building AI tools that auto-certify seed fields in minutes, to launching custom workflows for dusty documents like Circular 6, Moyer is reframing what agtech can be: not sensors and soil maps, but smart, adaptive systems that think alongside humans — and sometimes ahead of them.
“This isn’t about the future,” Moir says. “It’s about what you can automate today. And how quickly you’re falling behind if you don’t.”
Moir’s origin story reads like a Wired sidebar: A master’s in particle physics, analyzing subatomic collisions at the Large Hadron Collider; early experiments in machine learning before it was cool; a pivot into AI leadership at the Alberta Machine Intelligence Institute (Amii), one of Canada’s premier AI hubs. There, he helped launch scaled AI services and worked with ag-robotics startup DOT (now part of CNH) and Bayer’s Climate Corp to model seed performance using genotype and phenotype data.
Then came AgVisor Pro, a kind of Siri-for-farmers, followed by Visor Pro for equipment techs. And now, as co-founder of Maleva Studio, Moir is building custom AI workflows across the agri-food landscape — like an LLM-based system that reads crop inspection reports and spits out seed certification results in minutes, instead of weeks.
“AI Used to Be Expensive. Now It’s Inevitable.”
A few years ago, AI in agriculture meant big investment for narrow applications. But with the rise of large language models (LLMs), the game has changed. “They can read, write, listen, act, reason. That alone gives you a five-tool player,” says Moir. “They’re not just software. They’re infrastructure.”
In his demo-packed talk, Moyer outlines five AI “archetypes” every business should know:
- Understand & Generate: LLMs can now read and summarize complex reports (think: financials or seed regulations), or draft grant proposals and SOPs in seconds. “If you’re not using ChatGPT to brainstorm or draft, you’re wasting time,” Moir says.
- Retrieve: Semantic search makes keyword matching obsolete. Want to know soybean isolation requirements from Circular 6? Ask, and the system returns exactly the paragraph you need — no scrolling through PDFs required.
- Act: New tools like ChatGPT Operator or Lovable can build apps, fill forms, or take digital actions autonomously.
- Listen: Audio interfaces are now real-time, conversational, and shockingly accurate. Using Google’s NotebookLM, Moyer turns dense regulation docs into podcast-style audio explainers — with interactive Q&A on the fly.
- Automate: AI doesn’t just analyze. It decides. With the CSGA, Moir built a pipeline where inspection reports get auto-reviewed by an AI system trained on Circular 6, dramatically cutting review time while flagging outliers for human audit.
AI Isn’t Taking Your Job. It’s Taking Your Bottlenecks.
Let’s be clear: Moir isn’t here to sell hype. He’s building boring AI — the kind that eliminates spreadsheet misery, not sentient robots.
“In soybeans, you’ve got 5,000 inspection reports in four weeks. Reviewing them manually was a bottleneck,” Moir explains. “We digitized that flow. Then layered AI on top. Now, instead of weeks, we’re talking minutes.”
Accuracy? About 90%. But the system flags uncertainty and kicks reports to human reviewers when needed. “It’s not replacing people — it’s triaging complexity,” he says.
At Maleva, Moyer sees the same pattern: Executives are eager to plug in AI, but lack the organizational scaffolding to do it well.
“You need leadership buy-in, a culture that can handle change, and internal talent to build or manage AI workflows,” he says. “Without that, you’re just playing with shiny toys.”
His advice: Start where tasks are manual, high-volume, and data-heavy. Think seed inspections, service tickets, SOP drafting, customer support flows. Train your team to use AI as a thinking partner. And focus less on SEO, more on LLM discoverability — making sure the next GPT can find and understand your brand as easily as Google does.
And don’t just prompt — contextualize. “If the AI isn’t giving you good results, it’s probably your prompt. Ask it to interview you. Feed it raw documents. Get it to reflect on what info it’s missing.”
The Future is Already Working
“We’re just scratching the surface,” Moyer says. “In six months, you’ll be building apps on your phone. In a year, AI will be attending your meetings, summarizing your action items, and guiding your next move.”
And in agriculture? “AI’s not a tool. It’s a co-worker. If you haven’t hired one yet, you’re behind.”
—This article is based on a live presentation delivered at today’s meeting of the Canadian Seed Growers’ Association in Victoria, B.C.
