Agentic data engineering is a next-generation approach where AI agents are embedded throughout the data engineering lifecycle from, development to deployment. These agents help with building, montioring, optimizing, and maintaining data pipelines, allowing teams to automate low-level work and focus on high-value decisions. Ascend launched this model to improve speed, scale, and reliability across modern data workflows.
Agentic software engineering often focuses on developer productivity, using AI co-pilots to help write, debug, and refactor code. Agentic data engineering takes a broader view: it applies autonomous agents to not just assist with code, but to continuously monitor, maintain, and optimize data systems — often without human prompts. While AI co-pilots help developers in the moment, agentic data engineering uses always-on agents to reduce operational load across orchestration, documentation, incident response, and more.
Yes. Ascend gives you a lightweight agentic framework that lets you define custom agents and rules, and automate your agents using an event-driven model. These agents can listen for changes in your pipelines and act on your behalf — like flagging anomalies, updating metadata, or triggering actions in tools like Slack or Jira. Many teams use custom agents to automate repetitive tasks and enforce pipeline standards according to their internal policies and practices.
Yes. With Ascend's FlexCode approach, Data teams use Ascend to build their data pipelines in SQL and Python with form based components available for lower code users. All code is version controled and Git-backed.
Absolutely. Ascend has native integrations with Snowflake, Databricks, BigQuery, and more. It supports both ingestion and transformation workflows directly within these data clouds, with built-in security and version control.
Yes. Ascend provides real-time observability, schema change detection, dependency tracking, and complete lineage views, data quality tests, and more out of the box. You can troubleshoot, roll back, or fork pipelines instantly, without writing custom monitoring scripts.
Ascend supports enterprise-grade security including RBAC, SSO, audit logs, and isolated compute environments. AI agents only access metadata and actions within the user's permissions, ensuring zero data leakage or unauthorized access.
Yes. Ascend enables teams to build modern CI/CD workflows for data engineering through Git-based version control and environment management. You can integrate with tools like GitHub, GitLab, Bitbucket, and other Git providers to enable structured development workflows. This allows your team to automate testing, promote changes across environments, and manage your data pipelines like software code.
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