From First Pipeline to Production at Scale
dlt is the open-source Python library for data pipelines. dltHub Pro is the agentic platform that deploys, monitors, and scales them. Together, they cover every phase of data engineering.
dltHub Pro launches in full this May. The window to move first is now.
"What I didn't expect is how much it unblocks the team. A mid-level engineer can spin up a prototype, browse the raw data in dltHub Pro's local DuckDB workspace, validate the SQL schema - all without pulling in a senior. That loop of prototype, inspect, fix, re-run - that's the real unlock."
Marcello Victorino
Staff Data Engineer, Tasman Analytics
Marcello Victorino
Staff Data Engineer, Tasman Analytics
Agentic Workflows
Complete agentic workflows for every phase of data engineering
Not autocomplete, not a chatbot on a dashboard. A guided sequence of skills, commands, rules, and MCP - with guardrails agents can't skip. Maintained by dltHub, controlling the infrastructure agents and pipelines operate on.
Agentic Workflows in Detail
Discover individual skills per agentic workflow
See how each workflow guides your agent - step by step, from first prompt to production deployment.
Find a dlt source for a given API or data provider. Use when the user asks about a source, wants to find a connector, or asks to implement a pipeline for a specific data source.
Sonnet 4.6 · REST API Pipeline · ~/pipelines
Connect to any API and load data automatically
Deploy to production with one command
Explore data locally, build notebooks, ship Marimo dashboards
Transform raw data into a Canonical Data Model
Cross-toolkit rules, secrets management, and agent routing
Find a dlt source for a given API or data provider. Use when the user asks about a source, wants to find a connector, or asks to implement a pipeline for a specific data source.
Sonnet 4.6 · REST API Pipeline · ~/pipelines
THE AGENTIC DATA WORKFLOW
Describe it. The agent ships it. You verify it.
Build a pipeline that loads CRM contacts and deals into my warehouse using dlt
Agent-deployed pipelines are growing 10x year over year
Pipelines built and shipped by AI agents are on an exponential trajectory. Human-authored pipelines still grow steadily - but agents are scaling production workloads 10x faster.
Learn agentic data engineering
Free, self-paced course. From first prompt to production deployment.
Frequently Asked Questions
What is dlt?
dlt (data load tool) is an open-source Python library for building data pipelines. It handles schema inference, incremental loading, nested data normalization, and works with 9,700+ sources. Apache 2.0 licensed and always free to use.
What is dltHub Pro?
dltHub Pro is the agentic platform for deploying and operating dlt pipelines in production. It provides scheduling, alerting, observability, and complete agentic workflows - from coding to deployment. Agents build your pipelines from a prompt, and Pro handles the rest.
How is dltHub Pro different from a Claude skill or tools like Replit?
Tools like Claude skills or Replit are great for writing and running code. But they are not built for data engineering workflows end to end. dltHub Pro gives your team complete agentic workflows that cover every phase: coding, running, deploying, and debugging pipelines, on infrastructure you control.
How is dlt different from Fivetran or a Python script that uses the request library?
dlt is the perfect match between standardization and customization. You get the automation that matters: schema inference, incremental state, normalization, and loading, while keeping the full flexibility and portability of plain Python. And with agentic dltHub workflows, your team can code, run, deploy, and debug pipelines faster.
How do I get access to dltHub Pro?
dltHub Pro is currently in public preview. Fill out the form above and we'll get you set up.