One managed platform for collecting and processing data at scale. Run scraping on Go Scrapy, workflows on GoFlow — DagFlows handles the scheduling, retries, and durable execution. More engines on the way.
Three simple steps from zero to production data pipelines
Link the GitHub repository that holds your Go Scrapy scraper or GoFlow workflow. DagFlows clones your code, builds a versioned artifact, and deploys it to production — no local setup, no infra to wire up.
DagFlows resolves your DAG, schedules every run, and executes each node with leases, retries, and concurrency limits — on infrastructure you never have to provision or babysit.
Watch every run in real time. Inspect per-node state and logs, get alerts on failures, and export clean data to your warehouse or downstream APIs.
Go Scrapy for scraping, GoFlow for orchestration, and more engines on the way — all running on one managed platform. DagFlows handles the durable infrastructure so you can focus on the data.
Run web scrapers and API collectors as managed jobs. Go Scrapy handles pagination, throughput, and retries — you just write the extraction logic.
Chain jobs into a DAG of nodes with dependency resolution, conditional branches, per-node retries, and durable error handling built in.
Store, preview, and version your collected data. Export to CSV, JSON, Parquet, or push directly to databases and data warehouses.
Set cron-based schedules with timezone support. Track next runs, frequency, and execution history across all pipelines.
Every node is leased and tracked in Postgres. If a worker dies, the reaper requeues it; retries have hard caps and finalization is exactly-once — so runs recover instead of silently dying.
Connect to Slack, webhooks, S3, BigQuery, Snowflake, and more. Pipe structured data anywhere — including LLM fine-tuning pipelines.
Join the waitlist and be among the first to try DagFlows when we launch. Built for data engineers, by data engineers — your feedback shapes the product.
We'll notify you when early access opens. No spam, ever.