Astera 11.2 Debuts With Built-in RAG and Faster Data Processing

The latest release focuses on reducing the manual labor associated with data ingestion. By implementing batch job submission, the company reports a 50% reduction in per-job overhead, a change designed to maintain throughput during peak processing periods. For document management, the new Auto-Generate Layout feature slashes configuration time, enabling users to create extraction templates in roughly five seconds, a process that previously required over ten minutes of manual setup.

Beyond speed, the update introduces LLM Generate, a tool that allows teams to classify, extract, and enrich data using models from OpenAI, Anthropic, and Llama within their current dataflows. The platform also includes built-in RAG capabilities, enabling organizations to anchor AI responses in their own internal datasets. According to Ayesha Amjad, an AI product architect at Astera, this allows a single platform to handle the entire lifecycle of a document—from initial extraction and embedding to storage and final query response. The update is currently available across Astera's suite, including Centerprise, ReportMiner, and EDIConnect.