Gain insights from user feedback for your machine learning models and LLMs to make
data-driven improvements.
Seamlessly gather user feedback for your ML models without worrying about backend or databases so you can focus on the data science
Make data driven decisions to make your users love your product more
With ever changing models and algorithms, we will work with you to build custom dashboards tailored to your unique dataset and use cases
Upload user feedback data on your ML model from your app and modelfi will organize a custom dashboard with insights on how to improve your ML model.
View a summary and individual entries
Custom visualizations for your data
modelfi supports flexible user feedback gathering and association with ML data. Your app only needs an internet connection to make a call to the modelfi servers.
Feedback entries are represented by strings in a json format.
Each feedback entry requires an identifier key, which should be unique for each one of your use cases.
{
"identifier": "your identifier",
"your_data_key_1": {
"<data type>": "<data value>"
},
"your_data_key_2": {
"<data type>": "<data value>"
}
}
Note: keys datetime, filename, and version are reserved for internal use.
Python example:
import requests
import json
body = {
"identifier": "<your identifier>",
"your_data1": {
"C": "your_data1"
},
"your_data2": {
"N": 1.234
},
"your_data3": {
"S": "hello world"
}
}
requests.post(
'https://api.modelfi.app/add_feedback_entry?api_key=<api_key>',
data=json.dumps(body)
)
Once you've uploaded the data, this entry will show up on your modelfi dashboard.
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