Platform
A system of action above fragmented farm systems.
AcreFrame does not need to replace every farm system to create value. It sits above fragmented sources — plans, weather, equipment, labor, inventory, and records — and turns them into executable packets.
Architecture
Source Systems → Intake → Normalization → Constraint Engine → Human Approval → Execution Queue → Work Packet → Record Packet → Variance Loop
Source Systems
Plans, weather, sensors, imagery, scouting, equipment telematics, inventory, accounting
Intake
File upload, API ingestion, email parsing, manual entry
Normalization
Schema validation, artifact source tracking, field boundary linking
Constraint Engine
Weather gates, equipment readiness, inventory lots, operator availability
Human Approval
Review queue for regulated and high-stakes tasks
Execution Queue
Ranked tasks: Ready, Blocked, Review Required, Missing, Hold, Override Logged
Work Packet
Operator work order with boundaries, rates, materials, safety notes, source references
Record Packet
Source-linked completion record with timestamps, operator notes, weather snapshot
Variance Loop
Planned vs actual cost, rate, and time variance surfaced per field / operation
State model
The operating queue is not a todo list. It is a ranked view of what can actually happen given constraints. Tasks move through states that reflect operational reality, not software idealism.
Ready
All constraints satisfied. Can dispatch.
Blocked
Weather, equipment, inventory, or operator issue.
Review Required
Regulated or high-stakes. Awaiting human approval.
Missing
Incomplete plan, signal, or resource. Cannot queue.
Hold
Explicitly paused. Reason logged and attached to record.
Override Logged
Dispatched despite blocker. Timestamped and auditable.
Completed
Work finished with timestamps and notes.
Reconciled
Record verified, cost cross-referenced, artifacts linked.
Data model preview
FieldBoundary
GeoJSON, acres, soil type, drainage
SeasonPlan
Crop, variety, target dates, input schedule
SourceArtifact
Type, file, source system, upload date
InputProduct
Name, active ingredient, rate unit, EPA number
InventoryLot
Lot ID, quantity, location, expiry
MachineAsset
Type, ID, attachments, calibration date
Operator
Name, certifications, schedule, contact
TaskCandidate
Field, operation, priority, constraints
WeatherGate
Wind, temp, rain, inversion, soil condition
ApprovalDecision
Approver, timestamp, decision, notes
WorkOrder
Packet, boundaries, rates, materials, safety
ExecutionRecord
Timestamps, operator, weather, as-applied
CostVariance
Planned, actual, rate diff, time diff, notes
Human approval model
AcreFrame never dispenses agronomic, regulatory, or safety decisions. It produces decision-support packets. Qualified operators or managers review and approve before execution.
Auto-ready
Low-stakes tasks with all constraints green and no regulatory flag. Still human-visible and reversible.
Review gate
Regulated applications, high-rate changes, first-time fields, or weather-borderline conditions.
Hold
Operator or manager explicitly pauses a task. Reason is logged and attached to the record.
Override
Manager dispatches despite a blocker. Override is timestamped, attributed, and auditable.
Now vs. planned
| Capability | Now | Planned |
|---|---|---|
| Input task queue | Design partner shaping | Production queue with real constraints |
| Weather gating | Design partner shaping | Multi-source weather with inversion risk |
| Operator packets | Design partner shaping | PDF + mobile packet generation |
| Equipment readiness | Manual / CSV intake | Telematics ingestion from mixed fleets |
| Source artifacts | Manual attachment | Auto-link plans, labels, prescriptions |
| Cost variance | Spreadsheet-based | Real-time variance per field / operation |
| Records | Design partner export | Compliance-ready record packets |
| Integrations | CSV / PDF / email | API connectors to major FMIS platforms |
Security and data boundary
- All data in transit encrypted via TLS 1.2+
- Farm data is not sold or shared with third parties
- API keys and tokens stored in environment variables only
- Server-side validation on all form submissions
- Rate limiting and honeypot fields on inquiry forms
- File uploads validated for type and size
Integration posture
- Manual file upload (CSV, PDF, image) supported now
- API ingestion planned for weather, FMIS, and telematics
- Schema validation and artifact source tracking on all data
- Human review required before automated task creation
- No blind redirect following or unsafe scrape ingestion
- Robots.txt and Terms of Service respected for public sources
Product proof
Sample previews. Not live customer data.
AcreFrame Execution Queue
Sample preview. Not live customer data.AcreFrame Work Packet
Sample preview. Not live customer data.WO-2025-0503-008
Manager approval requiredNorth 80 — Block C | Post-emerge herbicide
Boundary / Source
FieldBoundary-FB-2024-089
Prescription: RX-2025-0442.pdf
Input / Material
Product: Glyphosate 41% (generic)
Lot: LOT-22A-044 | Rate: 22 fl oz/ac
Weather Window
Wind: 6 mph W | Gust: 9 mph
Temp: 68°F | Rain: 5% | Inversion: Low
Window opens 07:00 — closes 10:30
Equipment
Sprayer: JD-4040 | Boom: 90 ft
Nozzle: AIXR11004 | Calibration: OK
Safety / Label Review
Review buffer requirements and REI before dispatch. Label reference attached.
AcreFrame Cost Variance
Sample preview. Not live customer data.Planned cost / acre
$42.30
Actual cost / acre
$38.10
Rate variance
-2 fl oz/ac
Within labeled range
Time variance
+8 min
Turn delay at gate
Operator notes
Field was drier than forecast. Reduced speed to maintain coverage. No skips observed.
Measurement note
Directional pilot measurement, not guaranteed savings.
AcreFrame Execution Queue
Problem: Plans and tasks compete for attention across systems, texts, and whiteboards.
Output: Ranked execution queue with field context, priority, and readiness flags.
Why it matters: The day starts with what can actually happen, not what was hoped for.
Weather Window Intelligence
Problem: Timing is everything and windows move faster than manual coordination.
Output: Weather-gated task readiness with wind, precipitation, and temperature risk flags.
Why it matters: Less dispatch into bad conditions. Fewer surprise cancellations.
Labor and Operator Assignment
Problem: Work is only real when someone qualified can do it.
Output: Operator assignment and handoff packet with certifications and schedule.
Why it matters: Fewer calls and clearer accountability.
Equipment Readiness
Problem: Machine status is often discovered too late.
Output: Readiness flags before dispatch: calibration, maintenance, attachments.
Why it matters: Fewer avoidable delays and aborted field trips.
Input and Inventory Planning
Problem: Materials are often reconciled after the crew is ready to work.
Output: Input pull list and inventory context per task.
Why it matters: Fewer surprises. Better lot tracking. Clearer cost attribution.
Sensor / Imagery Signal Intake
Problem: Soil moisture, NDVI, and scouting signals live in separate portals.
Output: Signal ingestion as task triggers or execution modifiers with source artifacts.
Why it matters: Better evidence-driven field work.
AcreFrame Work Packet
Problem: Operators need clear, complete packets to execute efficiently.
Output: Work orders with boundaries, rates, materials, safety notes, and source references.
Why it matters: Better handoff. Less clarification. Cleaner execution.
AcreFrame Record Packet
Problem: Records get rebuilt later because sources are scattered.
Output: Attached plans, notes, labels, imagery, weather snapshots, and completion records.
Why it matters: Cleaner proof of work. Less after-hours reconstruction.
Records and Compliance Packets
Problem: Compliance and liability documentation is assembled reactively.
Output: Execution records with source links, timestamps, and operator notes where applicable.
Why it matters: Not a substitute for legal or regulatory review, but a stronger starting point.
Cost and Variance Intelligence
Problem: Planned versus actual cost is often invisible until reconciliation.
Output: Cost variance panels per field, per operation, with driver attribution.
Why it matters: Earlier detection of drift. Better budgeting next season.
Region / Operation Configuration
Problem: One-size-fits-all rules do not work across crops, regions, and regulations.
Output: Configurable crops, seasons, inputs, constraints, and workflow rules per operation.
Why it matters: Local accuracy without fake global compliance.