Private Beta

You don't need to know
what to ask.

It tells you.

Upload your data. AI explores every possible angle.
Wake up to: here's what's happening, here's what to do.

Not a dashboard. Not a chatbot. Just answers.

See Sample Output

Snowflake · BigQuery · Redshift · CSV

Sample Output
Daily Briefing3 Confirmed1 Refuted
  • TikTok customers have 34% lower 90-day LTV than other channelsTikTok customers show $127 vs $192 avg LTV—significant gap confirmed.
    92%
  • Checkout drop-off correlates with page load timeNo significant correlation found (r=0.08, p=0.34).
    88%
  • Premium subscribers churn less in the first 30 daysPremium shows 2.3x better retention (94% vs 41%).
    95%
  • Weekend traffic converts at a different rate than weekdayMixed signals across segments, need more data.
    45%
  • Organic search users refer friends more than paid acquisitionOrganic users refer 3.1x more than paid acquisition.
    91%
1,247 hypotheses tested · Top 5 shownClick row for details →
H-001
Surprising

TikTok customers have 34% lower 90-day LTV than other channels

Potential Savings
$47K/mo
Test
Two-sample t-test
p-value
0.0023
Effect
d = 0.67 (medium)
Sample
n = 2,847 vs 12,403
Comparison
TikTok
127
Google
185
Meta
192
Organic
241
Evidence

Based on 15,250 customers acquired Jan-Nov 2025. LTV calculated at 90-day mark with 95% CI.

Recommended Action

Consider reducing TikTok acquisition spend or optimizing for higher-intent audiences.

The Problem

What is your data telling you
that you can't hear?

Dashboards show you what you expected to see. But the most valuable insights are the ones you didn't expect.

You only see what you think to look for

The real opportunities hide where you never look.

Your data has thousands of possible patterns. You can only check the ones you think of. What about the correlations, segments, and trends you never imagined?

There's never enough time

Deep analysis takes weeks. Decisions can't wait.

A thorough exploration of your data would take months of analyst time. So you check the obvious things and hope you're not missing something big.

You don't know what you don't know

The biggest risks are the ones you haven't thought of.

The most valuable insight isn't the answer to a question you asked. It's the answer to a question you didn't know to ask.

What You Get

Your AI data analyst.
Works while you sleep.

Connect your data once. Every day, get a briefing: what's happening, what's unusual, what you should do.

Exhaustive exploration

AI tests every reasonable hypothesis across your data. Thousands of combinations that would take a human analyst months to check. Nothing slips through.

1,000+hypotheses tested per run

Statistically validated

Every finding is tested with proper statistical methods. False positives filtered out. Effect sizes measured. You only see what's actually real.

95%confidence threshold

Actionable recommendations

Not just 'here's a pattern.' You get: here's what it means, here's the impact, here's what you should do about it.

insight to action
How It Works

You sleep. It analyzes.
You wake up to answers.

No prompts. No queries. No waiting. Just connect your data and let it work.

1

Connect your data

Snowflake, BigQuery, Redshift, or just upload a CSV. Read-only connection—your data never leaves your warehouse.

5 min setup
2

AI explores everything

It doesn't wait for you to ask. It proactively tests every reasonable hypothesis. Thousands of combinations, overnight.

3

Statistical validation

Every finding is tested with proper statistics. False positives filtered. Only what's actually significant makes it through.

4

Wake up to answers

Risks, opportunities, recommendations—all in one briefing. Click any finding to see the evidence and suggested action.

For Data Teams

We know you don't trust black boxes.
Neither do we.

Every finding is inspectable, reproducible, and exportable. See the code, run it yourself, verify the results.

Full code transparency

Every finding comes with the Python code and SQL queries. Run it yourself. Verify the results. No black box.

# Hypothesis: Regional order value differs
from scipy import stats

query = """
  SELECT region, order_value
  FROM orders
  WHERE order_date >= '2025-01-01'
"""
df = run_query(query)
result = stats.ttest_ind(
    df[df.region=='North']['order_value'],
    df[df.region=='South']['order_value']
)

Statistical rigor

Benjamini-Hochberg false discovery rate control. Effect size thresholds. Sample size requirements. We filter out noise before you see it.

Test
t-test / χ²
p-value
< 0.05
Effect Size
d > 0.2
FDR Control
BH

Your data stays yours

Read-only connections. Your data never leaves your warehouse. All queries run in your environment. Full audit trail.

Read-OnlyNo Data EgressQuery LoggingSOC2 In Progress
Access

Private Beta.

We're onboarding a small group of teams who need to find what they're missing.

Now Accepting Applications

Founding Member Access

Join the private beta and shape the future of autonomous data discovery. Founding members get priority access, direct support, and pricing locked for life.

Snowflake, BigQuery, or Redshift
Hands-on onboarding with the founding team
Founder-level pricing, locked forever

Limited spots. We'll reach out within 48 hours.

What is your data
hiding from you?

Find out tomorrow morning.

Private Beta. Limited spots available.