AI agents are reshaping how we build and run data pipelines. The current wave blends agent-driven platforms with AI-augmented databases, spotlighting Yorph AI, Echos, and the clickhouse-openapi-bridge.
• Yorph AI is an agentic data platform that helps you join sources, build version-controlled data workflows, clean, analyze, and visualize data, and even sanity-check logic with dry runs. It adds semantic layer creation and starts with file connectors, with databases coming soon. [1]
• Echos gives you pre-built AI agents—database queries, API calls, web search, data analysis, code generation—assembled in YAML workflows. It ships fast, with built-in guardrails like SQL injection protection and SSRF blocking, plus per-agent spending limits and visual traces to show what happened, where it failed, and how much it cost. Guardrails catch 80% of dangerous operations. [2]
• clickhouse-openapi-bridge lets you run queries against ClickHouse databases from ChatGPT Custom GPTs via OpenAPI. It’s a neat example of AI agents bridging databases with conversational tooling. [3]
Closing thought: AI-enabled data workflows are nudging us toward auditable, AI-assisted DB interfaces that blend exploration with guarded execution. Watch these patterns mature as more databases get agent-friendly tooling.
References
Show HN: Yorph AI – Agentic data platform
Show HN: Yorph AI Agentic data platform; integrates sources, versioned workflows, cleaning/analysis, semantic layer; also extending into databases soon globally.
View sourceShow HN: Echos – A lightweight multi-agent AI system with pre-built agents
Show HN: Echos pre-built agents, YAML workflows, SQL guardrails, Postgres traces, seeks feedback on database-related features and use cases.
View sourceShow HN: Query ClickHouse Databases from ChatGPT Custom GPTs via OpenAPI
Show HN demonstrates querying ClickHouse databases from ChatGPT custom GPTs using an OpenAPI bridge.
View source