Rivery unveils integrations with Amazon Q & Snowflake
Rivery has launched new data integration capabilities with Amazon Q and Snowflake, designed to enhance enterprises' utilisation of internal data for advanced AI applications and immediate business insights.
The introduction of these integrations aims to facilitate businesses in managing their data more efficiently across various platforms. Itamar Ben Hemo, Rivery's Chief Executive Officer, stated, "With the launch of these integrations, Rivery continues to enable seamless data management across platforms, empowering organisations to deploy powerful AI applications with fewer hallucinations and derive actionable insights. With Snowflake as a Source and Amazon Q integration, we're enabling our users to unlock the full potential of their data — from streamlining migrations to building data-driven, GenAI solutions that meet today's business needs with flexibility and security."
The first integration, Amazon Q, enables companies to craft personalised Generative AI (GenAI) chat assistants utilising comprehensive internal data. These AI systems address challenges such as limited access to proprietary data and susceptibility to errors, such as hallucinations, in large language models. Through Retrieval Augmented Generation (RAG) workflows, enterprises can construct secure, enterprise-specific chatbots capable of delivering accurate summaries, answering questions, and generating content.
The platform allows for the synchronisation of all enterprise data sources, enabling the development of AI applications utilising a complete data spectrum. Further features include preparing enterprise data with a structure optimised for RAG workflows, triggering automated Amazon Q synchronisations for the latest data usage, and building secure data flows using an organisation's designated S3 file zones, thus preventing data exposure to third parties.
The second integration, Snowflake as a Source, assists data engineers and analysts in replicating and migrating data efficiently between Snowflake and other platforms. This capability is designed to simplify cross-platform data management, reflecting a growing need to reintegrate data from warehouses back into operational systems to enhance decision-making and align data insights with business processes.
Key capabilities offered by this integration include syncing data across multiple data warehouses and platforms such as BigQuery, Databricks Lakehouse, and Amazon Redshift, as well as facilitating Snowflake account synchronisations. Organisations can also migrate data to alternative data lakes or warehouses while expediting complex migrations with a straightforward lift-and-shift method. The activation of Snowflake data in transactional databases or AI applications, such as Amazon Bedrock, is simplified, supporting reverse ETL processes and data syncing into AI uses.
Destinei Simpson, Data Analyst at Good Apple, a digital marketing agency, shared her experience, "Our team needed to migrate Google Search Ads 360 data to Snowflake and consolidate with older data from the same source, already stored in Snowflake. With Rivery Snowflake as a Source, it took us just a few clicks to set up a pipeline to replicate the data from one Snowflake dataset into another that would have otherwise required manual scripting and management. This made our job much easier and helped speed up our delivery time dramatically."
