Stop repeating last season's losses. Decide with what your farm already knows.
Built for smallholders, farm owners, and agronomists across Africa and Asia. Most farms repeat the same losses because what happened last season wasn't kept. FildraAI helps you break that cycle: record what happened, understand what it means, and decide what to do next.
The problem we're solving
Most farms are still farming in the dark.
A farm that doesn't remember what happened last season starts every season from scratch: the same pests, the same surprises, the same guesswork. FildraAI is built to end that. Every season should teach the next.
"Everything is fine."
The most common farm report is also the least useful. With no record, a remote owner cannot tell what "fine" actually means, or check it later.
No one remembers what worked
A practice works one season, but by the next nobody recalls the timing, the spacing, or the result. The knowledge leaves with the memory.
Problems found too late
Grain spoils, a planting window closes, a disease spreads, because the signal was never surfaced while there was still time to act.
Advice given, then forgotten
A recommendation is not tied to the field, tracked, or remembered next season, so the same questions and mistakes keep coming back.
The enemy is forgetting. When a farm has no record, every new crop cycle starts over from memory alone, and memory fades. Symptoms look unfamiliar again. Treatments get repeated without knowing if they worked. Costs blur together. The farmer carries the whole history in their head, and the farm pays for it.
FieldState is the memory. It captures what happened: plantings, observations, pest events, treatments, local practices, and costs. That record stays with the farm across sessions and seasons. FieldGuide draws on that history so guidance is grounded in your actual situation, not a generic answer.
Each season becomes a foundation. When what happened is recorded, the next question is better. The next diagnosis has context. The next decision has something to compare against. That is the loop FildraAI is designed to close: not a single clever answer, but a growing body of practical knowledge that belongs to the farm.
The two products
Two products. One farm workflow.
FieldGuide helps you decide what to do in the field. FieldState remembers what happened, so the next decision starts with context. Everything else, image checks, voice, maps, is a capability inside these two, not a separate thing to learn.
FieldGuide
Tell it what is happening. Know what to do next.
The flagship mobile experience that brings together everything in one interface. FieldGuide combines conversational AI, image diagnosis, knowledge retrieval, and location intelligence so you can ask questions, capture images, and get actionable guidance without switching between tools or opening a laptop.
- Single entry point blending chat, image diagnosis, maps, and knowledge in farmer-friendly language
- Mobile-first design optimized for phones, outdoor conditions, and intermittent connectivity
- Voice-led interaction for users who cannot stop work to type in the field.
- Region-aware answers respecting provinces, districts, and local regulations, never generic advice
- Full conversation history with the ability to reference previous diagnoses and recommendations
- Multilingual support with agricultural terminology preservation across languages
FieldState
The Memory Layer for Your Farm
FieldState captures every FieldGuide conversation as structured farm history. Diagnoses, treatment decisions, and agronomic observations accumulate over time into a queryable record of your farm's health, so context is never lost between sessions and patterns become visible across seasons.
- Persistent structured state built automatically from FieldGuide conversations
- Full crop lifecycle history, plantings, pest events, treatments, and outcomes per season
- Queryable farm memory: ask what was sprayed, when, and what the result was
- Per-event attention items, new field signals surface as they're logged, with the full record available for review across seasons
- Records carry forward consistently between the farmer's own sessions, so review later is grounded in what was logged earlier
- Money records sit next to the field activity they relate to, making spend-vs-activity review easier for the farmer
Design Philosophy
A Smartphone Is All You Need
We've engineered every product for the realities of field work, not the convenience of demo rooms. Our mobile-first approach ensures that a farmer in rural Zambia has the same access to sophisticated AI as an agronomist in Taiwan.
State-of-the-art technology shouldn't require state-of-the-art infrastructure.
The majority of the world's agricultural decisions happen far from reliable broadband and air-conditioned offices. They happen in fields, on farm paths, in village markets, places where a smartphone is often the only computing device available. We've built for this reality.
Every interface is designed for outdoor visibility: high contrast, readable in bright sunlight, functional with wet or gloved hands. Every feature is optimized for intermittent connectivity. Essential functions work offline, data syncs when networks are available, and nothing breaks when signal drops mid-session.
This isn't a compromise, it's a commitment. By building for the most challenging conditions first, we've created products that work beautifully everywhere. The same app that serves a smallholder farmer scanning a diseased leaf in remote Zambia delivers an excellent experience to an agronomist reviewing diagnostic reports in an urban research station.
Offline-First Architecture
Core diagnostic functions cached locally. Image capture and analysis continue without internet. Results sync automatically when connectivity returns.
Optimized Data Usage
Compressed image uploads, efficient API calls, and smart caching minimize data consumption for users on limited mobile plans.
Field-Ready Interface
Large touch targets, high-contrast text, and sunlight-readable displays. Designed for real conditions, not ideal lighting.
Phone-First, End to End
Every interface is built for the device farmers actually carry into the field. No desktop or tablet app is required to use FildraAI.
Why you can trust it
Built on real research, not hype.
The models, knowledge packs, and applied research behind FieldGuide and FieldState, built with transparent evidence, proper licensing, and safety as foundational principles.
Purpose-built for agriculture: Our technology stack is designed from the ground up for agricultural decision support, where accuracy, safety, and contextual relevance are non-negotiable. Unlike generic AI platforms adapted for farming, every component optimizes for real-world agricultural conditions.
Three integrated layers: A Vision Stack for image-based diagnosis with explainability, a Knowledge Layer for contextual intelligence with evidence trails, and a Safety Kernel that validates every recommendation against regulatory requirements and best practices before it reaches users.
Optimized for constraints: Every component is engineered for low-bandwidth environments, multilingual users, and intermittent connectivity. Models run efficiently on mobile devices, and knowledge bases support offline-first access patterns.
Computer Vision Models
A family of plant disease models trained on public datasets and curated field images, then validated against our own benchmarks across diverse African and international conditions.
- Top-k predictions with class-specific AI focus areas
- Configurable per crop and region
- JSON inference reports for audits
- Research-validated, field-aware
Country Knowledge Packs
Curated, licensed content packs for specific countries and provinces. Each pack is structured so FieldGuide can retrieve and ground its answers, not flat text dumps.
- Crop, regulation, and management content
- Transparent sources and licensing
- Multilingual variants available
- Localized, evidence-first
Field Testing & Validation
Applied research that leaves the lab: pilot deployments, demo plots, and monitoring studies to understand how tools behave under real constraints.
- On-farm and extension-led testing
- Accuracy, usability, trust evaluation
- Continuous feedback loops
- Applied, not just academic
Partner Services
Implementation & Support
Support for organizations deploying FieldGuide and FieldState at scale, from national agricultural programmes to focused regional pilots. We help you move from evaluation to impact.
Deployment & integration
Complete guidance to roll out FieldGuide and FieldState within your existing digital ecosystems and agricultural workflows, from technical integration to user onboarding.
- Integration into portals, mobile apps, CRMs, and farmer-facing tools
- Authentication, roles, and access patterns for different user groups
- Monitoring, updates, and long-term support planning
- Training materials and documentation customization
Custom Knowledge Packs
Tailored country or programme content packs that plug directly into FieldKB and FieldGuide, developed in collaboration with local research institutions and extension services.
- Localization for new countries, provinces, and priority crops
- Co-development with research institutes and extension services
- Licensing, attribution, and evidence tracking for compliance
- Multilingual content development and validation
Joint Pilots & Evaluation
Structured pilot programmes with clear success indicators so your team can measure real impact before scaling, including training pathways and post-pilot analysis.
- Pilot design, success metrics, and progress reporting
- Training pathways for field staff, advisors, and agronomists
- User feedback collection and analysis
- Post-pilot recommendations for expansion or refinement
Every season should teach the next.
Join the founding group helping shape FildraAI around memory, explained guidance, and local farming reality across Africa and Asia. Bring a question from your field, and we'll help you begin keeping the record.