Why Scoop

Customers everywhere are figuring out that generic AI bolted onto conventional BI doesn't work. It doesn't know your business. Scoop's domain intelligence does—it's built on top of those layers and delivers real results.

Built on Years of Analytics Expertise

Capabilities That Required Ground-Up Design

These four capabilities sit on top of an analytics engine built from scratch by experts who've spent decades in BI and data analytics. You can't bolt these onto existing platforms—they require fundamental architecture designed for autonomous investigation.

Domain Intelligence with Persistent Learning Loops

What it does
Built on business-specific knowledge, not generic AI. Captures YOUR investigation patterns and business context. Progressive learning improves from 45min to 5min.
Why it's hard
Requires persistent learning loops and business-specific context understanding—not just generic AI responses.
Requires deep analytics expertise to build learning systems. Dashboard vendors don't have this foundation. ChatGPT resets every session.

Autonomous Discovery Engine

What it does
Multi-pass reasoning that tests 15+ hypotheses simultaneously. Discovers insights without being asked—like having an army of analysts working on your behalf.
Why it's hard
Requires AI architecture built from ground up. Can't bolt onto single-pass SQL systems.
Requires analytics engine designed for investigation from the ground up. Dashboard tools use single-pass SQL. ChatGPT has no analytics foundation—just file analysis.

Analysis at Scale

What it does
Hundreds of analyses running simultaneously across your live data. Proven at 156M rows in production—like an army of analysts working 24/7.
Why it's hard
Requires enterprise-grade data infrastructure and real-time connection management at scale.
Enterprise analytics infrastructure built by experts who've scaled BI platforms before. ChatGPT has no data infrastructure. Dashboard AI is bolted on, not built in.

Explainable ML-Based Data Science

What it does
Deep, powerful analysis that goes way beyond conventional BI. Looks across multiple variables simultaneously. Not a black box—can be explained to end users.
Why it's hard
Scoop's AI preps data sets for you—normally hard in traditional data science. Multi-variable analysis is impossible with conventional BI.
Years of production analytics experience building sophisticated ML systems. Dashboard tools can't do multi-variable analysis. Generic AI can't prep enterprise data sets.
See the Difference

Same Question, Different Outcomes

When you ask "Why did revenue drop at Store 523?" — here's what you get.

Traditional BI / ChatGPT / Copilot

Q1 Q2 Q3 Q4 Now
Revenue at Store 523: Q1: $245K → Now: $198K Change: -19%

Then YOU investigate for 2 hours: checking segments, products, timing, competition, seasonality, staffing changes...

Scoop Domain Intelligence

Store 523 Revenue Analysis:

Root Cause: 35% decline in 25-34 age segment

Driver: Electronics category down 58%

Pattern: Started 3 months ago, accelerating

Investigation Depth: 3 layers deep across segments, categories, and timing

Confidence: 89%

Investigation completed in 45 seconds. We were able to investigate 3 layers deep and surface this pattern months before you'd see it in standard reports. All 1,279 stores investigated automatically every day.

Honest Comparisons

How We Compare

Side-by-side comparisons with AI-powered dashboards, generic AI, and data warehouse platforms. Here's what each does well and where domain intelligence built on analytics expertise wins.

Scoop vs AI-Powered Dashboards (like Copilot)

What They Do Well

Slapping AI onto existing dashboard tools (PowerBI Copilot, Tableau AI, etc). Makes it easier to build charts and query your dashboards with natural language. Good for teams already invested in traditional BI platforms.

Where Scoop Wins

AI-powered dashboards help you use tools better—they're reactive assistants. Scoop investigates autonomously—it's proactive intelligence. Copilot helps you ask better questions of your dashboard. Scoop discovers insights without being asked. When your AI-powered dashboard shows revenue dropped 19%, Scoop tells you the root cause is a 35% decline in the 25-34 age segment with electronics down 58%. Different paradigm: augmenting tools vs augmenting thinking.

Scoop vs ChatGPT / Generic AI

What It Does Well

Accessible conversational interface. Great for one-time analysis of uploaded files. Good for simple questions and general knowledge tasks.

Where Scoop Wins

ChatGPT doesn't know your business. Its context window is very narrow—it can only look at a few things at once and over-indexes on the last thing you said. Scoop dynamically constructs context based on the situation and your business, extending what AI can actually do. ChatGPT analyzes files you manually upload. Scoop investigates your living business automatically across all connected systems. If you're an enterprise with ongoing investigation needs, ChatGPT fundamentally can't help.

Scoop vs Snowflake Cortex

What It Does Well

AI capabilities integrated directly into your data warehouse. Good if you're heavily invested in Snowflake infrastructure and have technical teams.

Where Scoop Wins

Data warehouse AI requires 6-month implementations, technical expertise to configure and maintain, and serves technical users building AI into pipelines. Scoop configures in one session with zero coding and serves executives who need autonomous investigation. Different audiences, different complexity levels, different use cases.

See How We Investigate

Bring your toughest investigation challenge. We'll show you exactly how Domain Intelligence handles it—no sales pitch, just an honest demonstration of what makes us different.

Book Your Discovery Call