We successfully launched the application in under 3 months, while improving data quality, seed name accuracy, and back-end efficiency.
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AgTech
Improving data quality, classification, & uploading
We successfully launched the application in under 3 months, while improving data quality, seed name accuracy, and back-end efficiency.
Rearchitected the front-end to decrease data quality issues
Increased speed and accuracy of applying seed names to multiple fields at a time
Fine-tuned seed identification and old-to-new mapping
When seed demand outpaces supply, farmers need to quickly choose and manually classify new seeds to plant. This means huge data quality and seed recommendation issues for AgTech companies. This impacts 30% of fields in the US and was causing 60% of our client’s seed naming data issues. We helped by quickly building an application for correcting classified seed names, uploading and unifying seed data.
We had under 3 months to improve our client’s solution before peak usage (the start of planting season). We quickly updated and rearchitected a user interface flow to replace manual entry across multiple fields at once.
This was an international effort with team members across 6 hours of time zones. Though this was challenging, we efficiently handled tests, subsequent analytics, and CI/CD requirements.
Dallas
15455 Dallas Pkwy, Ste 300
Addison, TX 75001
214.396.5390
Pittsburgh
181 42nd St.
Pittsburgh, PA 15201
San José
SIGMA Business Center
San José, San Pedro
Engineering Growth™
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