Data pipelines are broken.
We're fixing them.
Epiphany turns a plain-English description of the data work and the modeling goal into a production pipeline, interactive analysis, and a trained model — on one managed runtime.
The Problem
Building a data pipeline still takes days. It shouldn't.
A data analyst spots an opportunity. They need orders in Snowflake tonight — and a churn baseline they can defend in a meeting. Simple enough to describe in one sentence.
But actually building it? A data engineer writes Python, configures cloud infrastructure, wires up scheduling, manages credentials across three systems. That's days — sometimes weeks.
The bottleneck isn't intelligence. It's translation: turning the analyst's clear intent into working infrastructure.
Our Answer
Natural language → pipeline, lab, model.
Epiphany's four-agent AI crew — Planner, Ingestion, Transformation, Orchestration — works in parallel to plan your pipeline, write connector-aware Python, and deploy it to Epiphany Cloud.
You get a scheduled pipeline, a Data Lab session on the output, and a one-click path into ML Lab. No YAML. No second platform. No waiting.
→ Pipeline live · Data Lab ready · baseline trained.
How we think
What Epiphany stands for
Plain English, Real Infrastructure
You describe the data work and the modeling goal. Agents plan the pipeline, open Data Lab on the output, and can train a baseline in ML Lab — no YAML, no separate ML platform.
Built for Speed
A data analyst shouldn't wait two weeks for a pipeline, then two more for a notebook and a model. Epiphany closes that gap on one runtime.
Production-Grade by Default
Every generated pipeline runs on managed Epiphany Cloud with native cron scheduling, automatic retries, and secure credential handling — no clusters for you to operate.
Connector-Aware Intelligence
The AI agents understand the specifics of Postgres, Snowflake, S3, BigQuery, and more — generating idiomatic, optimised code for each target, not generic boilerplate.
Ready to ship pipeline, analysis, and a model?
Start free. No credit card required. Describe the work once — pipeline, lab, and a first model.