• Gen AI fabric brings data engineering discipline to Gen AI application development practice

• Gen AI fabric streamlines development with built-in connectors for data acquisition, Gen AI-assisted data transformations, ready LLM integrations, and more

Gathr Data Inc proudly announces the launch of Gen AI fabric – an integrated platform approach to building Gen AI solutions over a unified visual canvas.

The new Gen AI capabilities enable enterprises to effectively streamline operations, workforce training and customer interactions. Gathr’s Gen AI fabric powers the next level of evolution of data products. Gathr offers data engineering, machine learning, action analytics, and process automation capabilities. With Gen AI fabric, enterprises can now leverage Gathr’s strong data engineering and Gen AI capabilities to efficiently process large data volumes and create AI applications over a single pane.

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“Gen AI has quickly become a top priority for businesses across the globe. Recognizing the acute need for enterprise-ready Gen AI platforms and infrastructure solutions, Gathr is launching Gen AI fabric, which will significantly simplify and accelerate Gen AI innovations,” said P.C. Kiran, CEO, Gathr Data Inc. “Gen AI fabric brings a paradigm shift by providing users an intuitive, unified approach to seamlessly manage their AI journey by bringing together data asset discovery, data engineering & Generative AI technologies,” he added.

Gen AI fabric will allow users to leverage copilot assisted data pipelines, plug-and-play Gen AI operators, reusable solution templates, and distributed environments for deployments. It will enable them to swiftly create enterprise-grade Gen AI solutions such as document summarization, sentiment analysis, chat support, and more at scale.

Gen AI fabric unifies data acquisition, data preparation, Gen AI integration, prompt refinement, deployment, and more. Teams can leverage out-of-the-box integrations with LLM providers, on-prem ML, and LLM deployments. Moreover, they can use 250+ connectors and built-in operators for data parsing, chunking, and other transformations to streamline Gen AI journeys.

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