ChangelogDecember 14, 2025

From Assumptions to Revenue Impact: Forecasting the Decisions That Drive Growth

You’re making high-stakes revenue decisions with half-tested assumptions and a deadline you can’t move. This release is built for exactly that moment.

Forecast Studio: From Questions to Revenue Impact

Forecast Studio is built for the moments when someone asks, “If we do this, what happens to revenue?”, and you don’t have weeks to find out.

For example:

Launching a Q2 marketing campaign targeting 18–34 year olds in the Midwest and measuring its projected revenue impact for the rest of the year
Modeling how temperature changes affect regional beverage sales
Simulating the impact of a new AI competitor entering the mid-market by adjusting win rates and pipeline outcomes

On Riley, you can now deploy agents to generate charts and statistical model based projections in seconds, work that previously required weeks of manual analysis, custom modeling, and cross-team coordination.

This makes Forecast Studio especially useful during early-year planning, when teams need to pressure-test assumptions quickly and align on a realistic path forward.

Watch the full demo of Forecast Studio

The Interface You’ll Actually Want to Work In

We redesigned the Riley experience to get out of your way and let you move faster, especially when you’re exploring data, pressure-testing ideas, or preparing for decisions.

What’s new:

Dark Mode, for long sessions and late-night thinking
One-page workflows, so everything you need lives in a single, focused view
Your data, in one place, without jumping between tabs or modals
Faster load times (2.5x improvement), even with large datasets
Faster search, so answers show up when you’re actually looking for them

Watch a complete walkthrough of the new interface

Model Updates: Faithful to Your Data, and Its Context

The model that analyzes your data is now more accurate and more precise.

We’ve improved how Riley processes and interprets large, messy datasets so it can pick up on subtle signals that were previously easy to miss; small mentions, side comments, and low-frequency patterns that often carry outsized importance.

This means Riley is better at:

Picking up on small but relevant mentions that materially change the interpretation of your data
Connecting related details across long conversations, documents, and datasets, even when they’re not repeated or emphasized
Preserving context so insights reflect what was actually said or observed, not just the most frequent or obvious signals

The result is analysis that stays faithful to your data and its context, so subtle but important signals aren’t lost, averaged away, or misinterpreted when you’re making decisions.

You’re committing the roadmap and the number at the same time. This release helps you defend both.

“What happens to revenue if we do this?”