From questions to clarity: Our year at DecisionX

Great decisions don't come from choosing between speed and clarity. They come from eliminating the trade-off altogether.

Over the last year, we spoke with hundreds of CXOs, decision-makers, and strategy leaders across enterprises and fast-growing companies. Across roles, industries, and geographies, one problem kept surfacing:

Decision trade-off: speed vs. clarity.

This trade-off exists everywhere. Heavy analyst dependency. Costly context hand-offs between teams. Reasoning bottlenecks created by BI tools, SQL limitations, and dashboard sprawl. Insights arriving late, fragmented, or stripped of business meaning.

Leaders were forced to choose: Move fast with shallow answers, or go deep and wait months.

We built GREEN, our AI Analyst, to remove that choice. To reason at the pace of human thinking, without sacrificing depth.

What Followed Exceeded Expectations

Since opening our beta a few months ago:

• 120+ enterprise conversations and pilots
• 240 signups across data teams, strategy teams, and CXOs
• Consistent engagement across roles, not just analysts, but operators and leaders

One thing became clear: Agentic analytics has arrived. Ontology is the inflection point.

What We're Seeing in Practice

Across early deployments:

• Forecasting, root-cause analysis, and strategic planning cycles compress from 3 months to a few days
• Teams moving from 40 analysts to the effective productivity of 2
• Hundreds of BI dashboards, built to answer questions, becoming redundant
• Users engaging in 5–6 meaningful conversational turns per day, not one-off queries

This isn't analytics consumption. It's decision-making, continuously.

What's Winning for Enterprise

A few fundamentals are proving decisive:

1. Ontology that carries contextAnswers that understand your business, not generic responses. This is the difference between curiosity and adoption.

2. Trust and explainability by designFrom day one, we focused on implicit explainability and enterprise-grade guardrails. Clarity builds trust. Trust drives usage.

3. Self-learning systemsBuilding context once is table stakes. Maintaining and expanding a living system as data, decisions, and organizations evolve is where real value lies.

4. Multi-layered strategic reasoningNot just "create a chart," but "I want to increase sales by 20%. What should I do?" And receiving answers grounded in causal understanding of historical data and organizational structure.

Looking Ahead to 2026

From Our Writing

A few pieces that shaped how we think about decisions and AI:

Going Forward

Starting this year, we'll share two regular newsletters:

• Product Updates — Bi-weekly. What shipped and what improved.
• Monthly Recap — Product progress, new writing, and market signals we're paying attention to.