Now you can do analytics without ETL

Your data lives in 5 different places. The traditional path to analytics is: build ETL pipelines, load everything into a warehouse, model the data, then query it. That takes weeks. You can start getting answers right now.

The ETL tax

Before anyone at your company can ask “what's our revenue by channel this month?” someone has to:

1. Set up a data warehouse (BigQuery, Snowflake, Redshift)
2. Build ETL pipelines from every source (Stripe, Amplitude, GA, your database)
3. Handle schema changes, deduplication, incremental loads
4. Model the data so tables make sense together
5. Connect a BI tool and build dashboards

That's weeks of engineering before a single business question gets answered. For many startups, the pipeline is never “done.” It's always breaking, always behind, always missing the one source someone needs.

Meanwhile, the founder is still asking the engineer: “Can you pull our Stripe revenue and compare it to what Amplitude shows for paid conversions?” The engineer writes two queries, pastes them into a spreadsheet, and manually joins the data. Every time.

What if you could skip straight to the answers?

Contextflo connects directly to your data sources (your database, Stripe, Amplitude, Google Analytics, HubSpot) and lets you query across all of them in one conversation. No warehouse required for API sources. No pipelines to build first.

Get started right now

The biggest advantage of skipping ETL isn't the engineering time you save. It's that you can start getting answers today instead of waiting weeks for pipelines.

Connect your Postgres database in 10 minutes. Add Stripe. Add Amplitude. Your team starts asking questions across all of them immediately. No warehouse to provision, no schemas to design, no transforms to write.

Real example: a PE fund querying across systems

One of our customers is a private equity fund. Their deal data lives across multiple systems: different databases, different formats, different teams managing each one. Before Contextflo, getting a unified view of their portfolio meant asking someone to manually pull data from each system and stitch it together in a spreadsheet.

Now, a director at the fund (someone who doesn't write SQL) asks questions across all their data sources in one conversation. No ETL pipelines were built. No data warehouse was provisioned. They connected their sources and started asking.

When you still need ETL

This doesn't replace ETL for everything. If you're processing millions of events, need deduplication, or have complex transformations that feed ML models, you still want proper pipelines and a warehouse.

But if your immediate problem is “I need answers from data that lives in 5 different places and nobody has time to build pipelines,” you don't need to wait. Connect your sources, start asking, and build the warehouse later when it makes sense.

Start now, optimize later

The best analytics setup is the one your team actually uses. Connect your data sources in 10 minutes and let your team start asking questions across all of them today.