Snowflake AI analytics: dashboards in minutes, no Looker required.

Connect camelAI to Snowflake and replace your entire BI stack with one conversation. Dashboards, reports, and data apps — built by AI, published in minutes.

The BI stack you can delete.

Your analytics pipeline doesn't need four vendors, six contracts, and a dedicated team to maintain. It needs one connection.

Your current stack

With camelAI:

• Snowflake: Your existing data cloud
• camelAI: Queries, dashboards, reports — from conversation
• Annual cost: Pay for what you use

First dashboard live in under 10 minutes.

From warehouse to dashboard in one prompt.

Snowflake

Data Cloud

• Terabytes of structured and semi-structured data across databases, schemas, and warehouses.

camelAI

AI Agent

• Writes Snowflake SQL, builds interactive dashboards, deploys live applications — all from your description.

Live Dashboards

Published Apps

• Published to *.camelai.app. Share with stakeholders, embed anywhere, schedule automated refreshes.

What your stakeholders actually see.

Not a notebook. Not a CSV export. A live, interactive dashboard — built from your Snowflake data, published at a shareable URL.

Monthly Revenue

• $2.4M (+12.3%)
• Daily Active Users: 184K (+8.7%)
• Churn Rate: 2.1% (-0.4%)
• Net Promoter Score: 72 (+3)

Monthly Revenue Trend

Credit Usage by Team

Snowflake SQL. Natively.

camelAI doesn't translate to generic SQL. It writes Snowflake-native queries — Time Travel, QUALIFY, FLATTEN, semi-structured data, and every dialect feature your warehouse supports.

-- Time Travel: compare this week vs last week
WITH current_week AS (
  SELECT
    product_category,
    SUM(revenue) AS total_revenue,
    COUNT(DISTINCT customer_id) AS unique_customers
  FROM ANALYTICS.SALES.TRANSACTIONS
  WHERE transaction_date >= DATEADD(day, -7, CURRENT_DATE())
  GROUP BY product_category
),
last_week AS (
  SELECT product_category,
    SUM(revenue) AS total_revenue
  FROM ANALYTICS.SALES.TRANSACTIONS
    AT(OFFSET => -86400 * 7)
  WHERE transaction_date >= DATEADD(day, -14, CURRENT_DATE())
  GROUP BY product_category
)
SELECT
  c.product_category,
  c.total_revenue,
  c.unique_customers,
  ROUND((c.total_revenue - l.total_revenue)
    / NULLIF(l.total_revenue, 0) * 100, 1) AS wow_growth_pct
FROM current_week c
JOIN last_week l USING (product_category)
QUALIFY ROW_NUMBER() OVER (ORDER BY wow_growth_pct DESC) <= 10;

Features

• Time Travel
• FLATTEN & VARIANT
• QUALIFY
• Window Functions
• Zero-Copy Cloning
• Snowpark
• Semi-structured Data
• Stored Procedures
• External Tables
• Streams & Tasks

Do the math.

Your BI layer costs more than your warehouse. That doesn't make sense.

Looker

• $50–150k per year
• 6–12 months to implement
• Requires LookML developer
• Annual contracts, per-seat pricing

Tableau

• $35–70k per year
• 3–6 months to set up
• Desktop license + Server/Cloud
• Extract scheduling headaches

camelAI

• Pay for what you use
• No annual contract
• First dashboard in under 10 minutes
• No modeling language to learn
• Iterate with conversation, not tickets

Enterprise-ready. Zero compromises.

camelAI is built for the same security and governance standards your Snowflake deployment already meets.

• Snowflake RBAC integration
• Read-only by default
• SSO & team management
• Full audit trail
• Warehouse isolation
• Role-based dashboards

Reports that write themselves.

Set up a cron job in one message. camelAI wakes up on schedule, queries your Snowflake warehouse, generates a formatted report, and delivers it to Slack or email — no human in the loop.

Schedule Setup

• Standard cron syntax — any schedule you need
• Full agent turn — queries, charts, analysis, delivery
• Accumulates context — compares against previous runs

camelAI — scheduled tasks

you > Every weekday at 8 AM, query our Snowflake warehouse for yesterday's revenue, top 10 products, and any anomalies. Post it to #revenue-updates in Slack.

camelAI > Done. Here's what I set up:

Schedule Details

• Schedule: 0 8 * * 1-5 (Mon–Fri at 8:00 AM)
• Warehouse: ANALYTICS_WH
• Tables: ANALYTICS.SALES.DAILY_REVENUE, ANALYTICS.PRODUCTS.CATALOG
• Delivery: #revenue-updates via Slack

Slack preview — #revenue-updates

Daily Revenue Report — Mar 17, 2026

• Total Revenue: $847,293 (+14.2% vs. prior Monday)
• Top Product: Enterprise Plan — $312,450 (36.9% of total)
• Anomaly: APAC region down 23% — possible data delay in RAW.APAC_ORDERS

What will you build on Snowflake?

• “Connect to our Snowflake warehouse and build an executive KPI dashboard. Pull revenue from ANALYTICS.BILLING, DAU from ANALYTICS.EVENTS, and churn from ANALYTICS.SUBSCRIPTIONS. Publish it for the leadership team.”

• “Query our Snowflake data — we have 2TB of clickstream data in RAW.WEB_EVENTS. Build a conversion funnel with drop-off analysis by device type and geography. Use Time Travel to compare against last month.”

• “Build a Snowflake cost optimizer dashboard. Show credit usage by warehouse, query volume by team, and flag any queries scanning more than 1TB. Set up daily cron alerts to Slack.”

• “Create a data quality monitoring app from our Snowflake warehouse. Check row counts, null rates, and freshness across our top 20 tables. Alert in Slack when anything drifts beyond thresholds.”

Petabytes of insight.

One conversation.