Precision Crop Health Monitoring
Hyperspectral and multispectral UAV imaging detects plant stress, nutrient deficiency, disease, and pest infestation days to weeks before visible symptoms appear.
Silicon Valley · Deep-Tech R&D · Agriculture
Seeing the field before the eye can.
Marut-X Labs builds UAV-enabled, AI-driven sensing and robotics systems that turn raw spectral light into field-level intelligence — giving growers the ability to act on plant stress, water deficit, and disease weeks before it's visible to the naked eye.
- Sensing band
- VNIR · 400–1000nm
Why we exist
Agriculture finds out too late.
Agriculture finds out too late.
We're building the instrument that finds out first.
By the time crop stress is visible to a person walking the rows, yield loss is often already locked in — and the inputs used to fight it are usually applied uniformly, wasting water, fertilizer, and money on the parts of the field that never needed them.
The problem today
- Stress, pests, and disease are typically caught by eye, days to weeks after the damage has already begun.
- Water, fertilizer, and pesticide are applied uniformly across whole fields rather than where they're actually needed.
- Precision-agriculture tools that exist today are priced and scaled for the largest industrial operations, leaving small and mid-sized growers behind.
Our approach Marut-X
- UAV-mounted hyperspectral and multispectral sensing reads plant and soil signals invisible to the human eye, well before visible symptoms appear.
- AI and machine-learning models turn raw sensor data into field-specific, actionable prescriptions — not just a pretty map.
- Modular, lower-cost hardware platforms designed to extend precision-ag benefits beyond the largest farms, over time.
Research & development
One sensing-and-autonomy stack.
One sensing-and-autonomy stack.
Fourteen places it changes outcomes.
Our technology stack spans software, hyperspectral and multispectral imagery, AI/ML, robotics, ground rovers, UAVs, environmental sensors, GNSS, and LIDAR — applied across the agricultural research domains below.
Precision Irrigation & Water Management
Thermal and NDVI-derived evapotranspiration mapping optimizes irrigation scheduling and reduces water use, fused with soil-moisture sensor networks.
Soil Science & Variable-Rate Inputs
Drone- and rover-based soil mapping feeds AI-driven prescription maps for variable-rate fertilizer, lime, and amendment application.
Crop Yield Prediction & Phenotyping
Multi-temporal imagery and LIDAR canopy structure feed ML yield-prediction models and high-throughput phenotyping for breeding programs.
Detection & Targeted Spraying
Computer-vision identification of weeds and pests, paired with autonomous precision-spraying drones, cuts chemical use versus broadcast application.
Livestock & Rangeland Monitoring
Thermal and RGB UAV surveys support herd counting, animal health and heat-stress detection, and forage-quality assessment across grazing land.
Orchard & Vineyard Management
Canopy volume and vigor mapping via LIDAR and photogrammetry support pruning optimization, yield estimation, and harvest planning.
Autonomous Field Robotics & Rovers
Ground-based autonomous rovers handle in-field scouting, sensor deployment, mechanical weeding, and selective harvesting alongside aerial data.
Precision Mapping & GNSS Surveying
RTK-GNSS and UAV photogrammetry support boundary mapping, drainage and topography analysis, and centimeter-level guidance for machinery.
Storage & Supply-Chain Monitoring
Sensing and imaging extended into storage and supply chains reduces post-harvest loss through early detection of spoilage and pest conditions.
Sustainability & Carbon Metrics
Remote sensing and ML-based estimation of soil carbon and cover-crop performance support verifiable sustainability and carbon-market participation.
Climate Resilience & Disaster Response
Rapid UAV-based damage assessment after floods, fires, frost, or storms helps growers anticipate and mitigate climate-related crop risk.
Data Platforms & Farm Software
Cloud and edge software fuses UAV, sensor, satellite, and ground-truth data into actionable dashboards and APIs for growers and agronomists.
Multi-UAV Swarm Coordination
Coordinated multi-drone research enables faster, lower-cost coverage and treatment across large-acreage farmland.
The thesis
Why this, why us, why now.
Why now
- Sensor and compute costs have fallen enough to make hyperspectral UAV sensing commercially viable, not just a research curiosity.
- FAA rules — Part 107, Part 137, and evolving BVLOS frameworks — are opening a real regulatory path for scaled agricultural UAV operations.
- Climate volatility and rising input costs are pushing growers toward precision, data-driven decisions out of necessity, not preference.
Why us
- Founder-led, research-first culture with field-validation discipline — we measure success in working fields, not lab demos.
- Silicon Valley base for deep-tech talent and capital access, paired with direct grower partnerships across California.
- A multi-disciplinary stack — UAV hardware, sensing, AI/ML, robotics — built for defensible IP across every layer, not a single point solution.
Business model
- Data-as-a-service subscriptions for ongoing field monitoring and seasonal prescriptions.
- Hardware-plus-software bundles sold or licensed to growers, cooperatives, and agricultural input companies.
- Non-dilutive grant funding — USDA SBIR/STTR, CDFA — pursued alongside equity capital to extend research runway.
Founding team
Built by two founders, in California.
Based in California. Co-leads platform & product, company strategy and operations, with a focus on partnerships, capital strategy, and bringing Marut-X Labs' research to commercial field deployment.
Based in California. Co-leads technology and research direction, with a focus on the UAV, sensing, and AI/ML systems at the core of Marut-X Labs' platform.
Get in touch
Building in agtech, robotics,
Building in agtech, robotics,
or AI/ML? Let's talk.
We're a seed-stage deep-tech R&D company based in Silicon Valley, working with California grower partners on first-season field validation. We're glad to hear from prospective partners, grower collaborators, research institutions, and investors.