Input Validator
Match field operation inputs with an external database
A simple and accurate way to validate product names and active ingredients for standardization and more accurate use of field operations data.
Documentation
Match user entered product names with structured input data
Match user entered product names with structured input data
No more unstructured data
Unstructured product data limits its value for analysis. Leaf Input Validator solves this by detecting similarities, allowing the data to be repurposed for various uses.
Increase the use of operations data
Many growers struggle to use unstructured operations data. Leaf Input Validator organizes it, making data-driven decisions easier and more effective.
Opening up new opportunities
Agtech providers using Leaf unlock new opportunities, from auto-creating tailored product picklists to setting custom matching criteria and building personalized databases.
Increasing speed-to-market
Speed-to-market is crucial for tech providers. Leaf helps agtech companies focus on product development and fast launches, avoiding delays from building back-end infrastructure.
Product label information
Manually entered product data in tractor monitors often doesn’t match databases like CDMS, Agrian, or Greenbook due to typos, internal codes, or long names. This mismatch affects traceability, compliance, and agronomy. Leaf solves this by using an algorithm to match product names with standardized database IDs, streamlining data accuracy.
Creating matches
Leaf Input Validator matches any product name from a machine file or field operation with a product in an input database. It returns a JSON with matching information like product name and productID. Each product is assigned a status: Predicted (suggested by Leaf’s algorithm), Validated (confirmed by user), Pending (no match found), or Invalid, along with a match score. You can configure preferences for the database used, minimum match rate, and the options available to users.
Using standardized data
Many agtech providers, like Farm Management Systems and label certification tools, use external databases to standardize crop input lists. Leaf Input Validator matches incoming product data with these databases, transforming unstructured information into standardized data. This saves the effort of building your own matching system and enables more analyses, speeding up the development of new digital products and services.
Start building with machine data
After authentication, Leaf’s API returns a standardized JSON for planting, application, and harvest operations with data summaries, full datasets and rendered maps.
