Watch an AI agent in Astera Centerprise map data from Dynamics CRM to Snowflake, field by field, with data transformation, in a no-code interface. This demo walks through a real data mapping scenario: a sales team's pipeline in Dynamics CRM (accounts, deal stage, close date, and deal amount in multiple currencies) needs to land in Snowflake every night for revenue and forecast dashboards. See how the agent reads both schemas, matches fields automatically, standardizes currency, and schedules the pipeline to run unattended.

This video shows how Astera ReportMiner extracts structured data from PDFs in two ways: a reusable template for consistent layouts, and an AI-driven pipeline for documents that vary. Working from a mix of PDFs, digital and scanned, that vary in layout and quality, you can build a custom extraction logic in ReportMiner: Whether a PDF arrives with a known layout or a new one, it runs through the same pipeline into the same output, with fewer manual exceptions and less setup.

Most AI pilots never make it past the demo phase. AWS Machine Learning Lead Praveen Jayakumar has seen plenty of promising AI projects get stuck between a successful demo and production. Teams often define what success looks like without deciding what failure looks like, leaving underperforming projects alive long after they should have been shut down. As Praveen puts it, they become “zombie” AI projects.