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GEOVISUAL TECHNOLOGIES INC

Agritech · Private

Plant-by-plant precision fertilization system using variable rate application (VRA) technology for specialty crop farming

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Updated · geovisual-analytics.com

Sector
Agritech
Total capital
$8.1M
Federal grants
$3.3M
8 awards · 2019–2024
Rank in peer group#4 of 199
Private capital raised
None on recordNo Form D filings on SEC EDGAR. Some raises are not filed.
Federal contracts
$4.8M
8 awards · NASA
Rank in Agritech#14 of 882
Granted patents
None on recordNo USPTO grants. Applications publish after 18 months.

Capital timeline

2012201420162018202020222024FEDERAL ↑EQUITY ↓Cumulative $8.1M$749K$1.1M$1.1M$850K$750K
2012201620202024FEDERAL ↑EQUITY ↓Cumulative $8.1M$1.1M$1.1M$850K

Latest events

  • Federal grantNASA · Phase II · Ccrpp~ Near-realtime Estimation And Forecasting Of National And Global Specialty Crop Supplies$750K
  • Federal contractNASA · Ccrpp~ Near-realtime Estimation And Forecasting Of National And Global Specialty Crop Supplies$750K
  • Federal grantNASA · Phase II · SBIR Phase II Ignite - Decision Support For Water Management In The Specialty Crop Agriculture Sector$850K
  • Federal contractNASA · SBIR Phase II Ignite - Decision Support For Water Management In The Specialty Crop Agriculture Sector$1.1M
  • Federal grantAgriculture · ** Awards Issued Prior To January 20, 2025, Were Funded Under Previous Administrations And May Not Reflect The Priorities And Policies Of The Current Administration.** This Project Will Develop A Plant-by-plant, Precision Fertilization Capability For Cool Season Vegetable Crops That Will Increase Harvest Yields While Reducing The Overall Amount Of Fertilizer Applied. Vegetable Growers Face Increasing Pressures To Reduce Their Fertilizer Usage From Rising Fertilizer Costs, Tighter Environmental R$600K
  • Federal contractNASA · SBIR Phase I Ignite$150K
  • Federal grantNASA · Phase I · SBIR Phase I Ignite$150K
Show 9 earlier federal awards
  • Federal grantAgriculture · Rising Input Costs, Particularly For Fertilizer, Have Been An Ongoing Concern For Agriculture In General But More Recently Have Become Increasingly Serious As Global Supplies Have Been Disrupted. For Specialty Crop Farmers In Particular, This Adds Pressure To An Industry That Faces Multiple Challenges That, If Left Unaddressed, Could Jeopardize The Viable Production Of Many Vegetable, Fruit And Nut Crops In The Country. We Propose To Demonstrate A Plant-by-plant Precision Fertilization Capabilit$175K
  • Federal grantAgriculture · Precision Harvest Forecasting Of Fresh Vegetable Crops$600K
  • Federal contractNASA · Multi-resolution Deep Learning For Land Use Applications$1.1M
  • Federal grantNASA · Phase I · Multi-Resolution Deep Learning for Land Use Applications$125K
  • Federal grantAgriculture · Precision Time-to-harvest Forecasting Of Specialty Crops$100K
  • Federal contractNASA · Igf::ot::igf The Outcome Of This Ccrpp Effort Will Be An Operational Capability To Deliver High Resolution, Accurate, And Up To Date Classifications Of Land Cover, And Forecasts Of Agricultural And Ecological Changes. The Proposed System Will Facilitate The Ease Of Use Of Multiple Advanced Machine Learning Algorithms And Integrate Imagery From Airborne And Satellite Sensors And Validation Data From In Field Sensors. The Principal Market Opportunity For The Proposed Technology Is The Agriculture $749K
  • Federal contractNASA · Igf::ot::igf We Propose To Demonstrate A Fully Automatic Capability For Generating A Global, High Resolution (30 M) Land Classification Map, With Continuous Updates From Satellite Imagery And Crowdsourced Ground Truth, And An Annual Publication Cycle. The Resulting Map Will Be Fully Extensible, Supporting Many Layers Including Anderson Type Land Cover Categories, Specific Crop Types In Agricultural Areas, And Even Continuous Variables Such As Crop Yield Estimates. Our Methodology Involves Fusing$123K
  • Federal contractNASA · Igf::ot::igf The Objective Of This Proposal Is To Demonstrate A Set Of Methods For Automatically Extracting Metadata From Diverse Data Sets To Serve As A Common Vocabulary By Which Data Can Easily Be Queried, Retrieved And Combined For Visualization In A Geobrowser. We Propose Extracting Keyword Tags From Both Structured And Unstructured Data Sets By Applying Natural Language Processing (nlp) To Metadata And Unstructured Content. The Extracted Tags Will Be Associated With Each Data Set As Supple$699K
  • Federal contractNASA · The Objective Of This Proposal Is To Demonstrate A Set Of Methods For Automatically Extracting Metadata From Diverse Data Sets To Serve As A Common Vocabulary By Which Data Can Easily Be Queried, Retrieved And Combined For Visualization In A Geobrowser. We Propose Extracting Keyword Tags From Both Structured And Unstructured Data Sets By Applying Natural Language Processing (nlp) To Metadata And Unstructured Content. The Extracted Tags Will Be Associated With Each Data Set As Supplementary Metad$125K

Node area is scaled to amount. Form D reports securities sold, which can differ from an announced round; filings are numbered in the order they were made.

Standing among 199 peers

Line = median

Agritech · System

  • Federal grants#4 · top 2%

Cumulative measures favor older companies. Rankings describe position today, not outcome. Below the median, ranks show as a band rather than a number.

Founders and team

Researcher links verified by same-company patents and grants
  • Jeffrey Leonard OrreyResearcherExecutive Officer, DirectorLinked by $125K in grants as PI
  • Andrew Leonard McGregorDirectorNamed in SEC Form D filings
  • Carl Leonard KalinDirectorNamed in SEC Form D filings

What it has protected

No granted patents are on record.

USPTO usually publishes applications 18 months after filing, so recent applications may not be visible yet. Patents assigned under a different entity name won’t match.

Checked: USPTO granted patents and published applications · Oct 23, 2026

Related companies, and why

Regulatory activity · Agritech

Sector-level, not company-level

Rules are matched to sector, not to company. Recent activity in a sector is context rather than a signal about this business — until rules are matched to what a company actually builds, the section is shown as context and nothing more.

Sources

Federal grants from SBIR/STTR, NIH, NSF and DoD records. Federal contracts from USAspending.gov. Private capital from SEC Form D. Patents from USPTO. Publications from OpenAlex. Regulatory activity from the Federal Register. Press matched on company name.

How to read this page

Figures show associations in public records, not causes or predictions. Nothing here is investment advice. An em-dash means no record was found under this company's name, not that none exists.

Data freshness

SEC Form D filings through . SBIR and STTR awards through .