Today, Squark released a RESTful API that enables deep control over functions in Squark. Squark’s API enables coders to call each discrete operation in the Squark AI engine. Now, only through Squark, the entire machine-learning and AI pipeline building process can be accessed using Squark’s powerful API.
Data scientists, data engineers, coders, and other technologists can now integrate Squark into their applications, round-tripping data from any application to Squark and back. Squark’s API can now provide our customers with methods for ingesting, cleaning, preparing, augmenting, debiasing, engineering, auto-modeling, explaining, and activating their data wherever it exists to wherever they want it to go. Squark’s machine learning API now better serves the needs of our growing set of Fortune 100 customers by further automating AI and data science end-to-end across systems. Predictive data and probability-based results can now be easily sent to and from various applications to power business automation.
The Squark API extends the same API our engineers use internally to operate our ML engine. Enterprises who want to apply automated AI outside of Squark’s elegant and nimble no-code UX can now close the loop with our public API. Command Squark’s massively parallelized GPU or CPU-optimized system at scale for your big data (and small data) to:
Creating an API that can send information between applications not only makes it easier to access new and updated data, but to quickly action the results. And when that data isn’t historical, but forward-looking such as predictive or forecasted data, being able to act upon those values almost immediately can be game-changing. Whether you’re a data scientist, an analyst, or perhaps an analytically inclined executive, more people having access to predictive data faster allows organizations to act swiftly and update strategies and processes that ultimately increase revenue.
Use the Squark API to automate the entire process of data science powered with augmented intelligence. Instead of clicking on an interface or doing visual drag and drop, simply code the API to connect to your data via our intelligent data connectors (or pass files), identify what you want to predict, and then control each step in the Squark process, finally sending and setting your data to other systems. For example, if you are predicting optimal portfolio allocations, you could use the API to ingest financial data, create a regression model or time series model, and send/schedule the delivery of the results to another system. By using Squark’s API to continuously deliver new predictive values as the data drifts, changes, and needs to be updated, you are always using the best model and results to make smarter decisions and take faster actions. The most forward-thinking companies in the world already use Squark for an automated 360-degree view (past, current, and forecasted) of their business data, customers, and performance. Now with Squark’s REST API, our leading enterprise customers can integrate Squark with custom and proprietary systems and applications, getting and sending ML-based AI predictive insights anywhere.
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Judah Phillips