Driving rapid throughput of validated data to power global agri-tech
200,000
tree annotations validated
24-hour
turnaround time achieved
97%
data accuracy
USE CASE
Annotation workflow
INDUSTRY
Agricultural Tech
SOLUTION
Design Stack
The mission: Activate smarter agriculture practices with AI-driven insights
Aerobotics leverages AI solutions to develop intelligent tools for agriculture that assist clients with tree management, yield forecasting, and scalable decision-making. This mission required high-quality training data for their AI models to perform—a key challenge for Aerobotic's annotation team with the 24-hour turnaround time and sudden volume spikes.
The challenge: Meeting annotation needs amidst tight timelines and fluctuating data volumes
Aerobotics faced a barrier in ensuring data is correctly annotated with high volumes of aerial imagery to be processed and only a 24-hour turnaround time.
Key obstacles
- Fluctuating workloads and diverse agricultural patterns across regions made it challenging for annotation teams to maintain consistency
- Verifying annotations at scale without delaying turnaround time
- Potential AI model drift due to misclassification with overwhelming data to process
- Reduced capability to detect and resolve inconsistencies, ambiguity in labeling, especially in edge-case scenarios or evolving datasets
The goal
Implement a resilient verification workflow to maintain data fidelity in tandem with production speed.
The solution: A multi-tiered data labeling verification workflow for large, dynamic datasets
We tailored our annotation verification infrastructure for frictionless integration into Aerobotics' existing workflow, thereby ensuring high data quality, efficiency, and scalability for machine learning pipelines.
Our approach
- Applied a distributed workflow by utilizing a flexible workforce model to manage the fluctuation of data inflow without compromising on quality
- Layered QC with human-in-the-loop review cycles to flag inconsistencies early with continuous feedback to reduce error rates
- Assessed labels with context to ensure accurate interpretation based on agricultural nuances
- Initiated edge case escalation protocol for ambiguous or complex samples, engaging domain experts for resolution
The results: Uncompromised precision across any season
- Delivered 200,000 verified annotations within 24 hours
- Set up a target accuracy standard with a 97% baseline
- Scaled delivery by 170% without additional workforce
- Year-round volume flexibility
Aerobotics is now able to empower more growers around the world to manage and forecast their yield across all seasons with intelligence stemming from AI optimization.
Drive ML systems with quality data
Streamline workflow for voluminous data verification to ensure your AI models ingest purposeful data.
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