Akkio updates no-code AI platform with Snowflake integration


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Headquarters in Cambridge, Massachusetts AkkioClaiming to provide a no-code platform to help businesses build and deploy AI in minutes, today announced notable product enhancements, including integration with major data platforms.

The performance of an AI model is only as good as the data it is trained on. Today, however, enterprises rely on different sources and applications for different data points. This makes training models a bit difficult. With this update, Akkio addresses this issue and provides organizations with a wide variety of options to connect to for training models and gaining insights, including Snowflake, Google BigQuery, Airtable, Hubspot, Salesforce, and Google Sheets.

“We are trying to make AI as easy to use in business as Excel spreadsheets. Now everyone can achieve rapid data gains — using AI to uncover patterns and optimize key business outcomes,” said Jon Reilly, co-founder and COO of Akkio.

Data preparation functions, anomaly detection

In addition to integrating with a wide range of data sources, Akkio’s platform also provides capabilities to help enterprises better prepare their data to get accurate model results and detect anomalies in those models.

For the first, the company said it will add filtering and merging capabilities, allowing companies to remove unnecessary rows of data and match records without unique identifiers. Meanwhile, for the latest, it provides custom models that can detect anomalies in data, enabling preventive maintenance on IoT devices and detection of fraudulent transactions, among other things.

Akkio is also introducing time series models, which view collections of observations in chronological order to reveal data patterns over time and predict likely future outcomes. This usually helps with use cases such as churn reduction, forecasting quarterly sales figures, and weekly inventory figures, making any organization’s data more valuable.

Ten times faster insights

In addition, the platform provides the ability to help analysts see the most predictive factors in their data and understand the combination of factors that can drive results. Clusters are automatically created that group cohorts of data around an outcome, which can then be used by companies to target specific cohorts with different offerings. This, Akkio says, can optimize their conversion and generate insights ten times faster than before.

The updates bolster Akkio’s offerings in the no-code AI development space, which has grown especially in light of the pandemic and the shortage of data science talent. Other players operating in the same segment include Google AutoML, Clear AI, and Fritz AI.

Gartner predicts that 65% of app development will be low-code/no-code by 2024.

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