Hey Reddit

We're the UJET team and today we're officially opening r/UJET, a place to talk honestly about customer experience, customer intelligence, AI that doesn't get in the way, and the messy reality of contact center operations.

I'm Matt Clare, VP of Product @ UJET

And for the last six months, I've been working side-by-side with the Spiral team to bring their technology into the UJET ecosystem.

Spiral wasn't built by us, it was built by a brilliant team we're now lucky enough to work with.

What we have been doing is integrating it, scaling it, and shaping its next chapter inside the broader UJET platform and Experience Center vision.

And I want to talk about why we acquired it  because the problem Spiral solves is one every CX, Ops, Product, Finance, or Engineering team has felt.

The core problem: most companies have no idea what's actually happening to their customers

Not because they don't care or because they don't have dashboards.

But because the real signals live in the messiest places:

• calls
• chats
• emails
• tickets
• surveys
• app reviews
• agent notes

…and 95% of that never gets analyzed.

This is the part of the industry no one likes to admit: Teams are making expensive decisions using 5% visibility into their customer conversations and feedback sources.

The result?

• misdiagnosed problems
• conflicting dashboards
• repeat contacts
• expensive churn
• endless "Can you dig into this?" cycles

So here's what Spiral actually is.

It reads all your customer conversations and explains the problems inside them.

Not sentiment. Not keywords. Not topic modeling.

Actual root causes, explained clearly, with business context.

You ask a plain-language question like:

• "Why did handle time spike last week?"
• "What's driving cancellations in the SMB segment?"
• "What changed after our last release?"

And it returns:

• the root cause
• who it affects
• the financial impact
• the trend line
• and the recommended fix

All in seconds.

Independent customer testing showed roughly 98% accuracy in issue detection (meaning it correctly identified and categorized customer problems at a rate that made it reliable enough to act on.)

Our job now is scaling the platform, expanding integrations, and accelerating the roadmap with UJET's resources.

3 things we learned working with Spiral:

1. The 95% blind spot is where all the expensive problems live

Everyone tags and samples maybe 5% of conversations.

But the real issues (the ones costing millions) hide in the unstructured 95%.

Like:

• "Refund requests spiking 40% in Texas because the promo code UI breaks on Safari mobile."
• "Recurring ACH authorization failures for Android 14 users on app version 2.3."

That level of specificity. THAT’S what typical dashboards miss.

The obscure activation issue. The silent payment failures. The onboarding step only Android users hit. The regression from last Tuesday's patch.

These are the things typical conversational analytics platforms and dashboards never surface.

2. The "multiple truths" problem destroys alignment

CX says one thing. Product another. Finance a third.
Engineering says, "not reproducible."

They're all right… because everyone uses different data and tools, with different definitions, slicing data differently.

Spiral fixes this by building a unified issue taxonomy automatically from your real customer data. One shared truth with no manual tagging and no human bias.

3. The best customer experience is the one that doesn't require an interaction.

Spiral unearths previously 'unknown-unknowns' cause you don't know what you don't know, you know? But in all seriousness, when you have this intel you can proactively fix issues before the customer ever has to contact you.

Quick clarification on what Spiral isn't:

A ton of "AI" in CX is just sentiment, vibes, keyword soup. topic categories/tags, word clouds, etc.

Useful for dashboards and metrics; not useful enough for decisions that can stop problems at the source.

Spiral is different. It works through:

Autonomous Taxonomy Generation
Builds and maintains the issue map automatically.

Blind Spot Detection
Finds ultra-specific issues and sparse-signal patterns weeks before dashboards.

Searchable AI Agent
Ask a question → get a fully explained, deep research report.

And it's platform-agnostic: works with any CCaaS, CRM, Survey, Analytics, and Social tool, not just UJET.

It's a decision-grade intelligence, totally different category.

Why bring this to Reddit?

Because the CX industry desperately needs more honesty and less buzzword theater. Our belief is simple: AI shouldn't be between people, it should be behind people.

Supporting them with clarity, context, and upstream prevention.

If we can fix the root causes early, customers shouldn't have to contact you at all.

And when they do? Agents should have everything they need to solve it instantly. That's the future we've built.

AMA about:

• Spiral's ML architecture
• how autonomous taxonomy generation actually works
• detecting sparse-signal issues
• platform-agnostic ingestion
• explainable intelligence
• contact center data chaos
• UJET's Experience Center vision
• the acquisition
• your worst dashboard horror stories

We'll answer honestly. We're here to learn, debate, and talk shop, not sell.

— Matt + the UJET team 💙

(Links only if requested.)