What a Digital Twin Actually Does With Your Data

What Goes In

Three categories of input drive a recommendation: soil type and test results (texture, organic matter, existing nutrient levels), crop type and target yield, and field-specific data where available (past application history, irrigation, regional climate norms). The model doesn't need all of it to produce a recommendation, but accuracy improves as more real field data is supplied instead of defaults.

What Happens In Between

The model cross-references that input against formulation logic built on established agronomic relationships — nutrient availability curves by soil type, crop-specific uptake patterns, and microbial dosing thresholds — rather than a single fixed recipe applied to every field. Two fields with the same crop but different soil texture and organic matter get different recommendations, because they need different things.

What Comes Out

A specific blend recommendation: ratios, application rate, timing, and microbial dosing guidance where relevant — something a co-op agronomist can act on directly, or adjust based on what they know about a specific grower's field that the model doesn't have.

What Doesn't Change

Your co-op still does the physical blending, still holds the fertilizer registration required in your state, and still distributes product exactly the way it does today. Algaeo sits upstream of all of that, as an independent input into the recommendation — not a link in the supply chain.