# Silicon | The Data Partner for High-Growth Startups

URL: https://meetsilicon.com/

> Silicon partners with high-growth startups to build and maintain their data foundation, with an AI analytics platform anyone in the company can ask.

Your Silicon data team
This week
- Product events and Stripe connected Mon
- Activation and churn defined with product Tue
- Growth dashboard shipped Wed
- Broken signups model fixed before the 9am report Thu
- Onboarding funnel by signup source In progress
Monthly metrics review
Thu, 10:00
Our work
Answers
Alerts
# The data partner for high-growth startups
We bring your company's numbers into one place, define each one with the team that owns it, and let anyone ask questions in Slack.
- Your company's data in one place
- Key metrics defined with each team
- Dashboards and an AI analyst in Slack
- Live in about ten weeks, maintained after
Talk to Sujay
30-minute call with the founder
Companies with an existing data team can use the platform on its own.
Works with the stack you already run.
dbt
Snowflake
BigQuery
Databricks
Redshift
Postgres
ClickHouse
GitHub
Slack
dbt
Snowflake
BigQuery
Databricks
Redshift
Postgres
ClickHouse
GitHub
Slack
dbt
Snowflake
BigQuery
Databricks
Redshift
Postgres
ClickHouse
GitHub
Slack
Data work today
Somebody at your company is already doing data work. Usually it's someone in ops, finance or growth, in spreadsheets, late in the evening, on top of their actual job. We'd rather they didn't have to.
- CSV exports
- Revenue tracker v7
- Copy-paste
- Production database
- "Is this number right?"
- Three churn definitions
- Stripe export
- Board pack final_v3
- CRM report
- Broken formulas
- Late evenings
- Manual fixes
Problem
## What companies usually try first
High-growth startups need reliable numbers well before a data team fits the budget. Each of these works for a while.
- 01
### Keep running on spreadsheets
Every team exports its own numbers, so sales and finance end up with different revenue for the same month. Someone loses Monday morning to the weekly report, and the board deck gets checked by hand the night before.
58%
of leaders say key business decisions are based on inaccurate or inconsistent data most of the time.
Source: DevPro Journal
- 02
### Hire a data team
Eventually the right call. A first data hire usually spends their early months building infrastructure before anyone sees a dashboard, and experienced data engineers are slow to find.
$150k
average total pay for one data engineer in the US.
Source: Built In, Data Engineer salaries, 2026
- 03
### Buy a dashboard tool
Looker or Metabase will chart whatever you give them. Someone still has to get the data into shape first and fix it when a field changes upstream, which brings you back to hiring.
65 days
median time to hire a senior data engineer at a US company, from opening the role to a signed offer.
Source: KORE1, Time to fill a data engineer role
Silicon takes on that work as your data partner. The foundation we build stays in place as your team grows.
How the data partnership works ->
Two ways to work with us
## Start from where your company is today
We can build and maintain your company's data for you, with the platform included. Or, if you already have a data team, they can use the platform on its own.
No data team We do the work
### Data partnership
We build your company's data foundation and maintain it as the company grows. Your team has dashboards and the AI analyst from launch, both built on the Silicon platform.
Your team's part
Explain how the business runs, sign off each key metric, and tell us what you need next.
How the data partnership works -> Priced after discovery - monthly or annual
A typical start
Depends on how many tools you run
- Weeks 1-2 Discovery
We map where your data lives and which numbers your leadership team relies on. You get a written plan and a quote.
- Weeks 3-8 Build
We bring your company's data into one place and define each key metric with the person who runs that team.
- Weeks 7-10 Launch
Dashboards for each team and the AI analyst in Slack, all built on those definitions.
- After launch Maintain
New tools, new metrics, requests from any team, and fixes when something in your data changes.
metrics/net_revenue.yml
1 # Reviewed in pull request #318 2 metrics: 3 - name: net_revenue 4 label: Net revenue 5 model: ref('fct_invoices') 6 measure: sum(amount_usd - refunds_usd) 7 filter: status = 'paid' 8 dimensions: [plan, region, month] 9 owner: finance
You have a data team Your team does the work
### Silicon platform
Our AI analytics platform, connected to the warehouse and dbt project your team already maintains. They define each metric once, and everything below runs on those definitions.
- 01 Define each metric once
Your team writes metric definitions in YAML next to the dbt project and reviews them like any other code. Every answer and dashboard reads from them.
Semantic layer ->
- 02 Answer questions in Slack
Anyone in the company asks in plain English. The answer comes back with a chart, the metric it used and the SQL behind it.
AI analyst ->
- 03 Build dashboards and reports
Save any answer as a chart, group charts into dashboards, and send them to Slack or email on a schedule.
Dashboards & reports ->
- 04 Catch breaking changes
Silicon reads each pull request and comments when a change would break a dashboard or metric, with a drafted fix.
Schema protection ->
See the platform -> From $1,499 a month - unlimited users
Security
## Security built into Silicon from day one
Read-only access, queries that run in your warehouse, AI that respects every permission, and no training on your data.
How we handle data
### Data stays in your warehouse
Silicon connects with read-only credentials and runs queries in your warehouse. Results are cached briefly to keep dashboards fast.
### Your data never trains models
Customer data is never used to train AI models. Answers are built from your semantic layer, not memorised.
### AI inherits your permissions
The AI analyst runs every query as the person asking, so row- and column-level rules apply to every answer.
### Deploy your way
Hosted in the US, with an EU region on Pro. Enterprise can run Silicon privately in your own VPC.
On every plan
- Row- and column-level security
- Read-only warehouse access
- SSH tunnels to private warehouses
- Private spaces for work in progress
On Pro and Enterprise
- User groups Pro
- SSO, SAML and SCIM 2.0 Enterprise
- Custom role builder Enterprise
- Private deployment in your VPC Enterprise
Signs it's time
## Signs a company has outgrown its spreadsheets
Talk to Sujay
- 01 The board deck is assembled from three spreadsheets.
- 02 Product analytics and billing report different numbers for the same month.
- 03 Someone spends Mondays rebuilding the same report.
- 04 The CEO wants AI on company data, and nobody trusts the data yet.
- 05 A product question takes a week to answer.
You'll be talking to the person building Silicon. Bring whatever you have, even if it's mostly spreadsheets.
Sujay SN Founder and CEO Talk to Sujay
FAQ
## Questions? We've got answers
### What is Silicon? +
Silicon partners with high-growth startups to build and maintain their data foundation. Our AI analytics platform runs on that foundation, and anyone in the company can ask it a question in plain English and see where each answer comes from. Companies with an existing data team can use the platform on its own.
### Do we need a data team to use Silicon? +
No. When we partner with you, we build and maintain your data foundation as the company grows: connectors, warehouse, models, key metrics and dashboards. If you already have a data team, they can use the platform on its own.
### What does the data partnership include? +
Data pipelines, warehouse setup, dbt models, metric definitions, dashboards and reports, the AI analyst in Slack, reliability monitoring and fixes, and a monthly review of your numbers. It's scoped to your needs, runs monthly or annually, and always includes the platform.
### Can we use just the platform? +
Yes. Team is $1,499 a month and Pro is $2,399 a month, with unlimited users on both. Your data team connects Silicon to your warehouse and dbt project, and you can partner with us later if you need more hands.
### Is Silicon secure? +
Silicon connects with read-only access, runs queries in your warehouse and never uses your data to train models. AI answers respect row- and column-level permissions. Enterprise adds SSO, SCIM and private deployment in your VPC. We haven't completed a SOC 2 or HIPAA audit yet; the Security page describes how we handle data today.
## Tell us where your data lives today
Book 30 minutes with the founder. Tell us where your data is today, and see Silicon running on sample data.
Talk to Sujay
30-minute call with the founder