They’re not short on data. They’re drowning in it.
What they’re missing is the ability to find what matters, understand why it’s happening, and know what to do next—without relying on a data team or spending hours slicing spreadsheets.
That’s why we built Scoop.
Scoop is your AI data scientist. It’s not a chatbot bolted onto a dashboard. It’s a fundamentally new approach to analytics—powered by agentic analytics—that actually does the work for you. It discovers, explains, and recommends. In real time. With your real data.
This is the origin story.
The Problem I Kept Seeing
Back when I was building analytics tools for enterprise clients, I noticed the same cycle play out again and again:
- A team would spend weeks defining metrics.
- Another team would wire up dashboards.
- Everyone would stare at those dashboards, hoping to find insight.
- Nobody knew where to look or what to ask.
Eventually, someone would export the data to Excel. Again.
And maybe—just maybe—a data scientist would come in three weeks later, run a model, and tell you what already happened.
By then, the quarter was over. The customer churned. The campaign missed.
What good is data if it’s always lagging?
BI Isn’t Intelligent
Let’s call this out: the "modern data stack" is broken.
We’ve been told that stringing together 10 different tools—one for ETL, one for warehousing, one for modeling, one for visualization—somehow makes analytics easier.
But in practice? It makes everything harder.
You need specialized skills just to maintain the stack. You need analysts to interpret static dashboards. And even the most well-meaning exec is still asking: "What am I supposed to do with this?"
That’s not intelligence. That’s presentation.
What if, instead, your analytics system worked like a teammate—scanning your data, finding patterns, calling out what changed, and telling you what to do next?
What Agentic Analytics Means
We didn’t just slap AI on top of old BI.
We rebuilt the entire experience around what we call agentic analytics. That means:
- Autonomous Agents: Scoop uses AI agents that actually run analysis workflows. They look at all your data—not just a chart—and decide what’s worth highlighting.
- Machine Learning at the Core: These aren’t gimmicks. We’re using real, production-grade ML models that can identify segments, forecast outcomes, and detect shifts.
- Interactive Discovery: Instead of dropping you in a dashboard maze, Scoop lets you chat, explore, refine, and go deeper. All with full context.
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Why Now?
Because AI has finally caught up to the problem.
For years, business data moved faster than tooling. BI couldn’t keep up with complexity. Data teams were overwhelmed. Non-technical users were sidelined.
But with the rise of foundation models, real-time processing, and cloud-native ML, we saw a chance to flip the paradigm:
What if business users could skip the SQL, skip the dashboard config, and get to answers instantly?
What if they could ask:
- "What changed in my funnel this week?"
- "Why are win rates dropping in Europe?"
- "Which leads are most likely to convert?"
And get a presentation-ready answer—complete with charts, context, and recommended actions?
That’s what Scoop delivers.
How We Built It
We’ve integrated every piece:
- Structured Ingestion: Scoop connects to CRMs, finance systems, ad platforms, databases, and spreadsheets—cleanly and reliably.
- Automated Data Prep: Our system profiles, cleans, and models data in minutes. No data engineer required.
- Real-Time Discovery Models: We run multiple model types across your data: segmentation, prediction, time-series analysis, behavioral clustering.
- Interactive Agent Layer: The Scoop AI agent doesn’t just chat—it executes. You can ask follow-up questions, drill down, compare groups, explore KPIs—all without losing context.
- Live Reports: Insights can be saved into dynamic, always-up-to-date reports and presentations. Not static PDFs. Actual business intelligence.
A Word on Data Science
You might ask: Is Scoop as good as a PhD data scientist with weeks to run models in Python?
No.
But here’s the truth: 99% of businesses don’t need that.
They need directional clarity. They need to see what’s changing. They need to act fast.
Scoop outperforms manual models not because it’s more precise—but because it’s faster, broader, and endlessly repeatable. It runs 100 models while your analyst runs one.
Even if your data has no signal, Scoop will tell you that. And even that is valuable.
What’s Next
We believe AI won’t just help with data. It is the new data team.
With Scoop, every operator, marketer, finance lead, and RevOps manager can explore data like an analyst, think like a data scientist, and act like a strategist.
No SQL. No Python. No wait.
Just insight. Now.
And that’s why we built Scoop.
Want to see Scoop in action? Try the AI Data Scientist for free and experience agentic analytics firsthand.
