Pixal 3D — Seed Round Investment Brief

The Problem

A Diagnostic Gap in Global
Agriculture

The tools growers rely on today can detect that a plant is stressed, but not why. Disease, drought, nutrients, and insects look identical on an NDVI map — and by the time symptoms are visible to the eye, physiological damage has already occurred and pathogens have spread beyond the treatment window. Across every major growing region, the result is the same: producers manage losses instead of preventing them.

Visual Scouting

Manual scouting covers a fraction of total acreage and only detects disease after visible symptom expression — when yield damage has already begun. A scout walking 1,200 acres cannot provide field-wide coverage.

Detects damage after the fact

Lab Diagnostics

Accurate — but at $50–$150 per sample, cost-prohibitive for field-wide application. Results arrive on a multi-day lag, too slow to inform within-season management decisions at scale.

$50–$150 per sample · days of lag

III

NDVI / Standard Imagery

Standard drone and satellite imagery detects that a plant is stressed — but cannot identify why. Disease, drought, nutrients, insects all look identical. Critically, NDVI only flags stress after physiological damage is already underway.

Symptom without diagnosis

$220B

The Solution

The Missing Diagnostic Layer
for Field Operations

Building a
Spectral Disease Library

Pixal 3D combines drone-mounted hyperspectral imaging, agronomic ground truthing, and machine learning to convert spectral signatures into disease-specific maps. The result is not another stress image. It is a decision layer for municipalities, agronomists, and growers.

Fly. Drone-mounted hyperspectral missions capture 680 spectral bands (400nm – 1700nm) across the entire field — orders of magnitude more biological signal than multispectral satellites resolve.

Diagnose. Our AI model reads those signatures and names the pathogen — 93% clubroot accuracy, validated against AAFC ground-truth data, detected before visible symptoms emerge.

Act. You receive a sub-metre disease map. Farmers treat only infected zones, avoiding wasted spray. Municipalities satisfy Pest Act reporting at true field-scale.

Farmer inspecting canola crop — Pixal 3D field operations

$220B in crops lost to disease every year — and no one has built the diagnostic layer to stop it.

Detects disease at the pre-symptom stage — before visible damage or yield loss begins.

Pre-symptomDetection stage

680 spectral bands captured per flight across 400nm – 1700nm — 130× more data than standard multispectral imagery.

680Spectral bands / flight

Hyperspectral Imaging

Pixal 3D captures reflectance information across visible and short-wave infrared wavelengths, expanding the signal available for disease discrimination well beyond standard RGB or multispectral capture.

Visible Spectrum

400nm – 700nm

VISIBLE LIGHT

Hyperspectral Insights

400nm – 1700nm

SHORT-WAVE INFRARED (SWIR)

Healthy Crop (false coloring)

Clubroot Disease Detected (false coloring)

Canola field — Pixal 3D hyperspectral view

DRAG

Hyperspectral Imaging + ML

Human Eye

Product Differentiation

The First Disease Specific
Aerial Diagnostic Platform

Every other remote-sensing platform tells a grower their crop is stressed. Only Pixal 3D names the pathogen, maps where it is, and quantifies what inaction will cost — at the pre-symptom stage, with peer-reviewed accuracy.

Capability Category

Incumbents Remote-sensing competitors

Pixal 3D Hyperspectral UAV platform

01 / 03 Diagnostic Depth What the platform can actually tell a grower about the crop.

Detects stress only

Flags that a plant is stressed — never why.

Competitor products surface generalized stress indices from multispectral imagery, without the spectral resolution to separate drought, nutrient, or disease causes.

~5Bands captured

GenericDisease-specific diagnosis

Detects & Diagnoses

A.I. powered hyperspectral UAV that names the disease.

Each flight captures 680 spectral bands — over 130× the spectral resolution of standard multispectral imagery. With that much spectral data, our AI model doesn’t just flag stress — we name the pathogen, before visible symptoms appear.

680Bands captured

SpecificDisease-specific diagnosis

02 / 03 Detection Window When the platform catches the problem.

Reactive

Only flags disease once it's already spreading.

By the time visible stress appears on a competitor's NDVI map, yield damage has already begun and the treatment window is closing — leaving growers managing losses rather than preventing them.

Post-symptomDetection stage

Damage controlGrower response

Predictive

Diagnoses disease before visible symptoms emerge.

Hyperspectral signatures capture the biochemical shifts that precede visible symptoms — opening a window for targeted, preventive intervention before yield loss begins.

Pre-symptomDetection stage

PreventionGrower response

03 / 03 Scientific Defensibility Whether growers, insurers, and regulators can trust the output.

Commercial heuristic

Vendor-claimed accuracy — no independent validation.

Competitor platforms rely on generic stress indices like NDVI. None publish peer-reviewed disease-detection benchmarks because the underlying multispectral hardware cannot resolve individual pathogens.

Vendor claimsValidation

No capabilityDisease-Detection Accuracy

Peer-reviewed science

Published Research Validated in the Field.

Our detection methodology is grounded in peer-reviewed hyperspectral research co-authored with Saskatchewan Polytechnic and the University of Guelph. That published baseline gives growers, insurers, and regulators something competitor platforms can’t offer: independently verified science.

Published studyValidation

93%Disease-Detection Accuracy

Benchmark · Pixal 3D vs. Generalist Remote Sensing SaaS · Canadian Prairie, 2025 Source: Pixal 3D technical brief

Market Opportunity

$250B Spent.
40% Still Lost.

Agriculture is one of the last trillion-dollar sectors without a decision operating system. $250B in global agrochemical spend still leaves 40% of the harvest lost to pests and disease, because blanket chemistry can’t solve what it can’t diagnose. Pixal 3D is building that missing diagnostic layer, anchored in Canada’s 93.6M cropland acres.

Tier

Figure

Definition

Underpinning Data

TAM 2030

$24.09B Total Addressable

Global precision farming market by 2030 — the software, hardware, and services layer Pixal 3D's hyperspectral diagnostics plug directly into.

Underpinned by $220B in annual global plant disease losses and $250B in global agrochemical spend — inefficiency Pixal 3D converts into precision.

Global disease losses$220B

Agrochemical spend$250B

SourceGrand View

SAM 2035

$4.40B Serviceable Addressable

Canadian disease-scouting & precision-spraying service market once Pixal 3D's spectral library covers the country's major field crops — built on 93.6M acres of Canadian cropland across canola, wheat, barley, pulses & corn.

Inspection: 93.6M acres × $8/acre × 5 visits/season = $3.74B. Precision spraying: 35% of acres × $20/acre = $655M.

Today-capable wedge: canola's ~22M library-validated acres yield a $1.03B near-term launch market. Each additional crop added to the library expands the SAM.

Inspection SAM$3.74B

Spraying SAM$655M

Canola wedge (today)$1.03B

ARR 2032

$14.96M 2032 ARR Target

Pixal 3D’s projected captured revenue from the Canadian opportunity. Anchored in our expanding municipal and provincial aerial crop disease surveillance program, scaled by 400K farmer acres under inspection, and supported by recurring agrochemical commissions.

Municipal and provincial operations in Alberta and British Columbia; Saskatchewan and U.S. expansion underway. Less than 0.5% of SAM — conservative capture, multi-billion-dollar headroom remains.

Municipal & Provincial Aerial Crop Disease Surveillance$9M

Farm Inspection Services$3M

SAM penetration< 0.5%

Source: Pixal 3D financial model · Grand View Research · Statistics Canada AgriCensus Updated: April 2026

Monetisation Strategy

Three compounding revenue engines, each activating in sequence

Near-Term 2026 – 2028

Channel 01 · Regional Agency

NWIPC Recurring Contract

$530K/yr · recurring · active

Pixal 3D's existing AI / ML contract with the Northwest Invasive Plant Council expands in 2027 to a $530K annual recurring engagement. A live government buyer carries the business through the pre-ASB revenue window and underwrites the 2027 revenue year independent of the ASB pipeline.

Channel 02 · Municipal

Mandated ASB Buyer

69 ASBs × $75K = $5.175M ceiling

Alberta's 69 Agricultural Service Boards are legally required to survey crop disease annually. Leduc County is the pilot — a legislated, recurring buyer. The pilot converts in 2026 and scales to 6 paid ASBs by 2028 (6 of 69, ~9% Alberta penetration), then doubles annually — 12 by 2029, 24 by 2030, tracking toward full-province saturation.

Channel 03 · Farmers

Seasonal Scouting Packages

3–5 visits/season · $8/acre/visit

On a typical 1,300-acre Alberta farm, a seasonal package generates $31K–$52K in annual contract revenue. Producers capture a 20% reduction in their ~$296K input spend — saving $59,200 per season — turning the service fee into a net financial gain from year one.

Medium-Term 2030 – 2033

Channel 04 · Agronomy

Agronomy Data Layer

$4/acre · multi-billion dollar industry

Agronomy service providers pay for access to Pixal 3D's diagnostic dataset to deliver more precise, field-specific recommendations to their farmer clients. A high-margin, zero-incremental-cost revenue stream that grows proportionally with the scouting base.

Long-Term 2034 +

Channel 05 · Agrochemicals

Wholesale & Retail Agrochemicals

$21B Canadian market · Pixal 3D directs the flow

With field-level diagnostic data at scale, Pixal 3D becomes a data-informed wholesale buyer of the agrochemicals it prescribes. Canadian farmers spend more than $21B annually on inputs. Every Pixal 3D recommendation creates a purchase decision — the only question is whether the margin flows to a distributor, or back to Pixal 3D.

Revenue Trajectory

Pixal 3D Financial Model · CAD

$150K2026Current-year project revenue

$600K2027NWIPC expansion · $530K/yr

$980K2028NWIPC + 6 ASBs · $1M threshold crosses 2029

$3.74M203024 ASBs + farmer base

$14.96M2032$10M milestone ✓ U.S. entry

$37.3M2035Pan-Canadian + wholesale

$116.8M2039$100M milestone ✓

Traction & Go-to-Market

Early Traction from Real Buyers,
Supported by Sector Credibility

Pixal 3D already has the ingredients investors look for a category-creating ag-AI company: an active municipal and provincial deployment path, and an industry endorsement from Alberta Canola — The organizational body representing 14,000+ canola farmers across Alberta Growers

Municipal Crop Disease Surveillance

Leduc County, AB · 2026 – 2027

Leduc County Clubroot Detection Pilot

Integrated drone-based hyperspectral imaging into Leduc County's crop disease surveillance program — replacing manual field inspection with autonomous aerial diagnostics across large parts of the county's canola acreage. Given that clubroot surveillance is a mandated requirement for all Alberta Agricultural Services Boards we see Leduc County as a key partner that can help us scale our solution across the province to the other 68 ASBs. There are two key factors working in a favor, 1. Under the Agricultural Pests Act, Every County in Alberta has a mandate to surveil for clubroot — this creates a pool of mandated buyers 2. Pixal 3D's has the only drone based platform on the market that can detect clubroot at 10x the speed and 10x the accuracy of traditional ground-based surveys — this creates a natural technology moat

▲ 69 ASBs Addressable

▲ $75K Avg Contract

▲ 93% Detection Rate

Provincial Invasive Species Surveillance

British Columbia · May 2026 – October 2026

B.C. Invasive Weed Detection and Management

Pixal 3D won a contract with Northwest Invasive Plant Council (NWIPC) to use AI and ML to detect and track the spread of invasive weed species across BC. This will be the first time that AI and ML are used to detect and track the spread of invasive weed species across BC. Giving the province a much more detailed information on the spread of invasive weed species across BC. A succesul demonstration could lead to an expanded scope worth over $500K annually — further aligning with our strategy to capture repeatable revenue streams from government contracts.

▲ 633,953m² area inspected/span>

▲ $133K Project Value

▲ $530K Potential Annual Contract Value

Reputable Clients

Exshaw, Alberta · May 2026

Amrize Environmental Assessment

Amrize, formerly LaFarge— contracted WSP to condct an enviromental assessment of parts of the quarry. This assessment required the classification of trees across the site to count and distinguish between conniferous and deciduous trees. Pixal 3D was contracted to provide the data capture and and processing capabilities to deliver on this project

▲ Top 5 Engineering Consulting Firm Addressable

▲ $7k Project Value/span>

▲ 500+ ha Area Surveyed

The Team

Operationally Driven,
Backed by Top Researchers

Pixal 3D unites a founding team in business development, drone operations, and machine learning with one of the strongest agricultural research benches assembled for a Canadian agtech startup — over 150 years of combined crop research experience, multiple peer-reviewed publication awards, and leadership that includes a past president of the Canadian Phytopathological Society.

C-Suite

Stephane Trazo

Chief Strategy Officer

Pixal 3D Inc.

BSc Geology; Post-Graduate Certification in Data Science & Machine Learning. Leads commercial strategy, investor relations, and works directly with the ML team on model refinement. Drives partnerships with municipalities, Alberta Innovates, and CAAIN.

Roosevelt Quiah

Chief Executive Officer / Chief Operating Officer

Pixal 3D Inc.

Over a decade of expertise in UAV operations, geomatics, and land surveying. Specialises in LiDAR, RGB, and thermal imaging. Ensures all hyperspectral flights are executed with RTK precision and correct geo-referencing — the operational backbone of data quality.

Tolu Olaiya

Chief Technology Officer

Pixal 3D Inc.

MSc Mathematics. Leads model development and analytics across Pixal 3D’s hyperspectral AI platform. Transforms raw datacubes into precision disease maps through statistical modelling and machine learning — the technical backbone of the diagnostic engine.

Core R&D Team

Tolu Akindele

Senior Developer

Pixal 3D Inc.

BSc Computer Science, University of Alberta. Builds and deploys ML infrastructure and scalable software powering Pixal 3D's aerial intelligence pipeline.

Christina Kaye

Project Lead, Smart Ag R&D

Olds College of Agriculture & Technology

Crop research and disease distribution analysis. Leads all field scouting and ground-truth data collection for model training and validation.

Kabal Singh Bohler

Research Manager

Gateway Research Organization

Professional Agrologist (P.Ag.) with extensive crop research experience. Leads canola small plot inoculation trials and brings resilience and data-driven rigour to agricultural productivity work.

Andrea Carlyon

Manager

Gateway Research Organization

BSc Animal Science, University of Alberta. Built her career with Corteva Agriscience managing canola and corn research plots. As GRO Manager she leverages her network for field access and project extension.

Scientific Advisory Committee

Dr. David A. Halstead

Research Chair — School of Natural Resources & Built Environment

Saskatchewan Polytechnic

M.Sc.; Professional Biologist (P.Biol.). Appointed Research Chair in 2014 following 20 years teaching aquatic sciences and supervising applied student research. Expertise spans aquatic biology, landscape ecology, and remote sensing across LiDAR, multispectral, hyperspectral, thermal, and RGB platforms. Leads the Prince Albert applied-research program for forestry, agriculture, and land reclamation. Co-author of the foundational hyperspectral clubroot detection study.

Dr. Mary Ruth McDonald

Full Professor & Research Program Director, Muck Crops Research Station

University of Guelph — Department of Plant Agriculture

Ph.D. Plant Pathology, University of Guelph. Recipient of the Canadian Phytopathological Society's Outstanding Research Award (2021). Internationally recognised expert on clubroot of canola and brassica crops, integrated pest management, and diseases of onion and carrot. Co-author of the groundbreaking drone-based hyperspectral ML clubroot study that forms the scientific foundation of Pixal 3D's platform.

Dr. Bruce D. Gossen

Fellow, Canadian Phytopathological Society

Agriculture & Agri-Food Canada (Retired)

Ph.D. Plant Pathology, University of Saskatchewan. 40-year Research Scientist at AAFC Saskatoon (1984–2023); Fellow and past President of the Canadian Phytopathological Society (CPS), and recipient of CPS's Outstanding Research Award. 220+ peer-reviewed papers, 3 books, and 30 book chapters. Lead editor of Diseases of Field Crops in Canada (4th ed., 2024). Co-author of the hyperspectral ML clubroot study.

Dr. Kelly Turkington

Research Scientist IV — Cereal & Oilseed Pathology

Agriculture & Agri-Food Canada — Lacombe Research & Development Centre

35+ years of cereal and oilseed disease research with AAFC Lacombe. Leads national collaborative programs on disease resistance breeding, cropping-system impacts, surveillance, and integrated disease management — working with AAFC Brandon, the University of Saskatchewan, and Alberta Agriculture. Foundational in establishing the Prairie Crop Disease Monitoring Network (PCDMN).

Herman Simons

Manager — Smart Agriculture Applied Research

Olds College Centre for Innovation (OCCI)

25+ years owning and operating his own farm before joining OCCI, plus leadership roles representing producers at provincial and national levels and as a farm-management consultant. Now leads OCCI's evaluation, demonstration, and validation of agricultural technologies — with a focus on broadacre dryland farming in Alberta soil and climate conditions. Brings the producer's lens to Pixal 3D's commercialisation pathway and field-trial infrastructure.

Investment Opportunity

A Clear Trajectory: Revenue, Partnerships, and Our Growing Moat

Pixal 3D is raising capital to convert early market validation into a defensible crop-diagnostics platform. With early traction, a strategic municipal deployment pathway, and a revenue plan that grows from $150K in 2026 to $600K in 2027, then to $1.43M by 2029, we have a clear path from pilot deployments to repeatable revenue.

Our moat strengthens with every acre flown, every ground-truthed dataset collected, and every disease signature added to our proprietary spectral library. This raise funds the transition from early deployments to scalable commercial adoption across municipalities, agronomists, insurers, and producers.

Capital Plan

Channel 01

$1.58M Seed SAFE Round

Priced equity-like investment from VCs and angels. This is what you're investing in.

↓ Term sheet below

Channel 02

$590K Non-Dilutive Capital

Grants and challenge capital pursued in parallel. Zero investor dilution — not drawn from the SAFE.

Adjacent to round

Two channels of capital. Investors fund Channel 01 only — Channel 02 is adjacent and does not dilute the round.

Pixal 3D · Seed Round · 2026

Raising $1.58M on a $8M
post-money SAFE.

Round size $1.58M SAFE · MFN · 18% discount

Validated Sask Poly × Guelph × Olds College Peer-reviewed co-research · 2 seasons

Instrument SAFE post-money · MFN · 18% discount

Valuation cap $8M post-money

Pro-rata rights Yes Series A allocation reserved

Min. cheque $25K angels · $100K funds (pro-rata)

Runway 24 mo to Series A criteria

Target close Jun 30 2026 rolling · first tranche open

Use of funds Allocation · $1.58M

01 Team — agronomy, engineering, pilotsAgronomist, senior developer, 2× data scientists, geomatics / lead UAV pilot, operating space — 24 mo $1.026M 65%

02 Hardware — sensor & UAV fleet2× DJI Matrice 400 platforms, 2× FigSpec FS64-C hyperspectral cameras (400nm – 1700nm), batteries, field vehicle $224K 14%

03 Research partnershipsOlds College 3,000-acre smart-farm access + Gateway Research Organization agronomy network $166K 11%

04 Cloud & consumablesAWS training + inference compute, Innotech clubroot inoculum for ground-truth plots $88K 6%

05 Reserve & contingency5% contingency per cost model $75K 5%

Σ Total raise $1.58M 100%

Value unlocked by your investment 24-month targets

6 / 69 ASB customers by 2028 From the Leduc County pilot to 6 of Alberta's 69 municipal Agricultural Service Boards under paid contract by end of 2028 — the entry cohort for a customer base that doubles annually toward full-province penetration by 2032.

$980K 2028 revenue run-rate NWIPC recurring ($530K) + the first ASB cohort of 6 at $75K. The $1M threshold crosses in 2029 as the ASB cohort doubles to 12 ($1.43M) — a Series A qualification data point, carried by a mandated, recurring government buyer base.

5+ Pathogens in the proprietary library Two seasons of hyperspectral flights expand the diagnostic moat beyond clubroot into sclerotinia, fusarium head blight, verticillium stripe, and other pathogens of economic significance. Each flight compounds a labeled spectral corpus competitors cannot replicate — the library becomes the product.

Why now

01 Hyperspectral escaped the lab A decade ago, HSI required benchtop spectrometers under controlled light. Sensors have since miniaturized while drones have gained payload, flight time, and RTK precision — bringing lab-grade spectral fidelity into the field. That hardware curve has now converged with production-ready ML inference, unlocking what was structurally impossible five years ago.

02 Disease pressure is accelerating in the launch market Clubroot confirmed in 42+ Alberta municipalities. Sclerotinia symptomatic in >90% of surveyed canola fields. The diagnostic gap widens every season.

03 Policy and commercial pull align Alberta's Agricultural Pest Act makes clubroot a regulated pathogen that all 69 Pest Act municipalities must monitor and report — but no field-scale diagnostic tool exists to satisfy the requirement. Pixal 3D is the first.

04 Input costs are forcing precision adoption Agricultural input costs have risen roughly 70% over the past five years. Margin pressure is flipping grower psychology from blanket-and-hope spray programs to actively seeking diagnostics that cut chemical use — precision disease maps pay back on every pass.

SAFE documents on file · post-money template · Alberta securities exemption Close: rolling through June 30, 2026

Canada's First Hyperspectral
Crop Disease Detection
Platform

A Diagnostic Gap in Global
Agriculture

The Missing Diagnostic Layer
for Field Operations

Building a
Spectral Disease Library

Hyperspectral Imaging

The First Disease Specific
Aerial Diagnostic Platform

Flags that a plant is stressed — never why.

A.I. powered hyperspectral UAV that names the disease.

Only flags disease once it's already spreading.

Diagnoses disease before visible symptoms emerge.

Vendor-claimed accuracy — no independent validation.

Published Research Validated in the Field.

This is the Pixal 3D Difference

$250B Spent.
40% Still Lost.

Monetisation Strategy

Revenue Trajectory

Early Traction from Real Buyers,
Supported by Sector Credibility

Leduc County Clubroot Detection Pilot

B.C. Invasive Weed Detection and Management

Amrize Environmental Assessment

Operationally Driven,
Backed by Top Researchers

A Clear Trajectory: Revenue, Partnerships, and Our Growing Moat

Raising $1.58M on a $8M
post-money SAFE.

Get in Touch —
We'd love to hear from you.

Ready to Learn More?

Canada's First HyperspectralCrop Disease DetectionPlatform

A Diagnostic Gap in GlobalAgriculture

The Missing Diagnostic Layerfor Field Operations

Building aSpectral Disease Library

Hyperspectral Imaging

The First Disease SpecificAerial Diagnostic Platform

Flags that a plant is stressed — never why.

A.I. powered hyperspectral UAV that names the disease.

Only flags disease once it's already spreading.

Diagnoses disease before visible symptoms emerge.

Vendor-claimed accuracy — no independent validation.

Published Research Validated in the Field.

This is the Pixal 3D Difference

$250B Spent.40% Still Lost.

Monetisation Strategy

Revenue Trajectory

Early Traction from Real Buyers,Supported by Sector Credibility

Leduc County Clubroot Detection Pilot

B.C. Invasive Weed Detection and Management

Amrize Environmental Assessment

Operationally Driven,Backed by Top Researchers

A Clear Trajectory: Revenue, Partnerships, and Our Growing Moat

Raising $1.58M on a $8Mpost-money SAFE.

Get in Touch —We'd love to hear from you.

Ready to Learn More?

Stay close to the build.

Canada's First Hyperspectral
Crop Disease Detection
Platform

A Diagnostic Gap in Global
Agriculture

The Missing Diagnostic Layer
for Field Operations

Building a
Spectral Disease Library

The First Disease Specific
Aerial Diagnostic Platform

$250B Spent.
40% Still Lost.

Early Traction from Real Buyers,
Supported by Sector Credibility

Operationally Driven,
Backed by Top Researchers

Raising $1.58M on a $8M
post-money SAFE.

Get in Touch —
We'd love to hear from you.