Say goodbye to lengthy PoCs with Customer Connect. Unlock the ability to make your data available for evaluation, without it needing to move. Allow your buyers to instantly assess your data’s characteristics, like match and fill rates, as well as evaluating model lift and feature importance, before entering into any legal agreements or sharing any data.
Expedite your sales process and connect with data buyers more easily.
Conduct 10x evaluations in the time it currently takes you to complete 1 PoC
Replace single vendor PoCs and simultaneously evaluate a suite of complementary vendors in a single project
et governance controls that dictate what can and can’t be done with your data
Showcase your data products to data buyers in a secure & neutral third-party environment. Identify the main features of your data, some of the common use cases for how it's being used by your customers today, and any other information that would be relevant to a data science team looking to evaluate a new dataset. Unlock a more scalable approach to selling your data and gain access to integrate.ai’s network of data buyers.
Include essential context for a successful and fool-proof experimentation job. With integrate.ai, you can build-out custom experimentation guides for your data product that walk prospective buyers through the testing process. Monitor exactly how your data product is being experimented, and recommend additional data science jobs that showcase the full impact of your data product.
Traditional data evaluations are restrictive, often forcing you to commit to a purchase decision due to all the time & resources spent evaluating a single product. Because data doesn’t move, Vendor Connect removes these barriers to experimentation, enabling you to test more datasets against your most critical models and identify which data investments will have a real positive impact.
Lightweight & easy to use with your existing data science technology stack. integrate.ai complements the data science tools you already use to power data experimentation
Use prepared datasets from Azure Storage in FL modeling and analytics. Use the best in cost efficient serverless technologies to run modeling and analytical tasks.
Use prepared datasets from Snowflake in FL modelling and analytics.
Use prepared datasets from Databricks in FL modeling and analytics.
Use prepared datasets from S3 in FL modelling and analytics. Use the best in cost efficient serverless technologies to run modeling and analytical tasks.
Use prepared datasets from Google Object Storage in FL modelling and analytics. Use the best in cost efficient serverless technologies to run modelling and analytical tasks.
Configure and control FL modelling and analytics using our SDK in your Jupyter notebook
Integrate.ai's federated data science platform enables collaborative data experimentation between data providers and consumers without compromising data privacy.
Unlike other privacy preserving methods in a federated data science system, raw data never moves out of the local environment, meaning the Guest and Host data will always remain separate.
The Host and Guest can never access individual data records from any participating dataset. Instead, they can only train models and perform analyses with full privacy-protection of the original data.
Both parties can decide what data can be used for which tasks at what time. They are able to grant or revoke permission to any dataset at any time.
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