Next Pathway Uses AI to Enhance its Code Translation Platform

Next Pathway launches the next generation of their SHIFT Product Platform enabled with Generative AI to improve migration planning, translation coverage and testing

Next Pathway Inc., the Automated Cloud Migration company, is pleased to announce its ground-breaking innovations that are changing the landscape on how legacy data warehouses and ETL pipelines (Extract, Transform, and Load) are being migrated to leading cloud platforms such as the Microsoft Azure Platform, Microsoft Fabric, the Snowflake Data Cloud and the Google Cloud Platform.

Companies are investing heavily in preparing their organizations to take advantage of generative AI, which is founded on the principle that everyone can create and consume AI-ready data. However, AI models require vast amounts of data running on a modern data infrastructure.  An incredible amount of code and data reside on legacy systems.  This institutional knowledge and asset base must be migrated to the cloud in order to take advantage of the data infrastructure and compute power that is only available on modern cloud architectures.

Recommended AI News: Sumsub Unveils Industry-First Deepfake Detection in Video Identification

There is more competitive pressure than ever before for organizations to use data to work smarter, be more cost effective, promote productive collaboration and identify untapped potential. Moving legacy systems to the cloud in an accelerated manner allows organizations to access their data in new ways, ultimately allowing them to achieve their corporate goals.

Recently Next Pathway launched SHIFT Cloud, putting the power of automatic code translation directly in the customer’s hands.  Continuing with this track record of innovation, Next Pathway is excited to announce the launch of its next generation AI-enabled SHIFT Product Platform which incorporates generative AI to improve the speed, coverage, and accuracy by which legacy workloads are migrated to cloud targets.  “Our innovations are geared to the practical and strategic demands of our customers, we are excited to play a role in helping our clients to enable AI transformation in their businesses.”, said Chetan Mathur, Chief Executive Officer at Next Pathway.

Recommended AI News: Alcion Modernizes Data Protection with New AI-Driven Partner Program for MSPs

Next Pathway is using generative AI to improve the complex engineering tasks involved in completing the 3 fundamental steps in cloud migrations:

1. Step 1 – Migration Planning Intelligence.  Next Pathway’s migration planning tool, CRAWLER360, now has improved capabilities to quickly rationalize legacy data warehouses and ETLs to identify which exact workloads can be decommissioned.  In addition, CRAWLER360 has been enhanced to use AI to predict the optimal migration wave plan based on data dependencies and the criticality and urgency of downstream consuming reports.
2. Step 2 – Code Translation.  Next Pathway has improved the speed at which SHIFT is able to translate transformation logic within ETL pipelines and SQL code.  Complex ETL platforms along with SQL Code can be translated faster than before, with improved accuracy.
3. Step 3 – Testing.  Next Pathway’s automated code translation is complemented by superior testing. By leveraging the generative capabilities within LLMs Next Pathway has enhanced the accuracy and quality of its code translation.  Next Pathway’s testing capabilities go beyond the generation of vast amounts of simulated test data, to test the logic within the embedded SQL being employed by the ETL jobs.

“Our mandate at Next Pathway is to make cloud migrations more straightforward and accessible while maintaining a high degree of coverage, performance, and quality. ,” said Chetan Mathur, Chief Executive Officer at Next Pathway. “Our engineering breakthroughs are game changers in legacy code migrations.  Making it easier, faster, and cheaper for organizations to AI-ready their data.”

Recommended AI News: Zendesk Completes Acquisition of Klaus

[To share your insights with us as part of editorial or sponsored content, please write to sghosh@martechseries.com]