Case Study · Saturn

How Saturn shipped its data platform in two weeks.

One RevOps lead. No analytics engineer. No warehouse to staff, no data stack to assemble.

Saturn
Industry
AI for UK financial advice firms
Headquarters
London, UK · YC S24
Stage
Series A · $15M (Singular, 2025)
§ In their words

“Every data tool I’ve used needed a data team to make it work. Definite is the first that didn’t.”

Antonio Worner
Antonio Worner
RevOps Lead
§ 01 — The problem

A data platform, not a hiring plan.

Saturn had clear product-market fit and great ARR. What they didn’t have was a data foundation, or any intention of building a team to stand one up. Antonio inherited RevOps four days before the first call with Definite.

01
No data team, and no plan to build one

Saturn had Series A funding, but Antonio didn’t want to spend his first quarter writing the job specs for a data team. He wanted answers, not headcount.

02
282 columns and counting

Metabase plugged directly into Attio meant a single deals table with 282+ columns. Every new attribute added three or four more. No data modeling == not sustainable.

03
Internal tools duct-taped together

GTM analytics was being stitched together from multiple sources. It worked, but it wasn’t a foundation. Antonio wanted a real platform underneath.

04
The default stack is wrong

The orthodox answer is to buy a modern data stack (Fivetran, Redshift, etc.). Antonio knew that meant months of setup, and a hiring loop, before anyone got an answer.

“We had the budget for the modern data stack. I didn’t have the patience for it.”

Antonio Worner
Antonio WornerRevOps Lead
§ 02 — The solution

Fi did the typing.

Antonio wanted something nimble he could pick up and go with. Instead of assembling Fivetran, Redshift, dbt, and a BI tool, he plugged Attio, Postgres, Mongo, Typeform, Stripe, Xero, and Google Workspace into Definite and started building.

Fi, Definite’s AI data agent, became Antonio’s building partner. He one-shots dashboards, iterates on semantic models, and debugs his own pipelines without filing tickets.

fi · prompts from antonio
01Aggregate client call recordings into the lake; analyze transcripts for themes.47.8s
02Flag deals that have stalled in the same stage for more than two weeks.12.4s
03Pipeline ARR by stage; make stage_group multi-select.18.6s
04Across GTM Intelligence, add the ability to click into a deal and jump to Attio.38.1s
05Find sentiment scores of 4+ where the deal had blockers.23.2s
06

“I don’t want to have 7 sales calls. I want something nimble we can pick up and use today.”

Antonio Worner
Antonio WornerRevOps Lead
§ 03 — Adoption

One person built it. Then thirteen showed up.

Antonio shipped the first dashboards solo. The founders, the analysts, and the AEs followed. Within three weeks, the entire Saturn team was in Definite.

Definite didn’t box them into one BI tool’s chart types or colors. The same data layer powers internal dashboards, client-facing views, and the deck they share with investors. Their flagship dashboard was shared directly with investors within two weeks. Analysts picked up Fi and started building. When the team needs data, they go to Definite.

Five new viewers were added in the last week alone; the rollout to leadership, ops, and AEs is in motion.

“No one internally was expecting this level of polish.”

Antonio Worner
Antonio WornerRevOps Lead

“It’s so easy to change and iterate. All the code is in one place and the agent can see it all.”

Antonio Worner
Antonio WornerRevOps Lead

“This is just crazy how quick you guys have shipped features.”

Antonio Worner
Antonio WornerRevOps Lead
§ 04 — Support

Same-hour fixes, same-week features.

When Antonio asked for something, it shipped the same week. Often before he asked.

“Legend, thanks mate.”

Antonio Worner
Antonio WornerRevOps Lead, after a same-day fix
§ 05 — Greenfield to gold in 22 days

A clean medallion, from day one.

Most companies Saturn's size are six months into picking vendors. Saturn chose to spend that time shipping instead. They chose wisely.

The same RevOps lead who would have spent a quarter waiting on a warehouse hire instead built the warehouse, the models, and the dashboards on top of it. Fi did the typing.

00
0 data engineers hired
01
0 vendors stitched
02
0 quarters spent on warehouse setup
What they built
  • 29 schemas in a clean medallion (raw → silver → gold) across 8 data sources
  • 16+ active integrations: Attio, Postgres, Mongo, Typeform, Stripe, Cube, Slack, Granola, Claap, Google Workspace, Joiin, Xero, internal tools
  • Each integration set up in ~5 minutes, custom or prebuilt
  • 106 docs and dashboards built in 22 days
  • Fi as a building partner across every dashboard
  • Data resident in europe-west2 (UK)

“I’m annoyed I didn’t find you guys earlier.”

Antonio Worner
Antonio WornerRevOps Lead
§ 06 — Results

What changed, in numbers.

01 · Time to data infrastructure
2 weeks, one person
02 · Headcount required
One RevOps lead
03 · Dashboards built
106 docs in 22 days
04 · Fi sessions
250+ threads
05 · Integrations
16+ active sources
06 · Data model
29 schemas · clean medallion
07 · Sync reliability
1,500+ syncs in 30 days
08 · Time to first dashboard
Days, not months

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