About KPI Tree

What should we do differently tomorrow to grow revenue?

It is the question every business runs on, and the one a dashboard cannot answer. We built KPI Tree to answer it, for your team and for the AI agents that work alongside them, with the evidence to act on it.

Everyone had dashboards. Nobody had answers.

I spent years as a Chief Data Officer, brought into private equity portfolio companies after an acquisition to make sense of the chaos. We would consolidate the data, build the modern stack and stand up the dashboards. Dozens of them. And every Monday morning the same scramble played out anyway: the CFO rebuilding a master spreadsheet before the exec meeting, tab after tab, revenue from Tableau, pipeline from Salesforce, customer metrics from Mixpanel. Every number told part of the story. None of them told the whole one.

Richard Oastler

Founder & CEO

Shadow dashboards. Rebuilt in Excel.

CEOs kept their own version of the numbers in a spreadsheet, because nothing they were given showed cause and effect.

What changed, never why.

Leaders could see that a number had moved. They could not see what caused it, or who needed to act. Revenue is down 8%. Is that pricing, churn, or a pipeline problem that started six months ago? The dashboard showed the symptom and never the cause.

Teams pulling apart. Without knowing it.

Whole departments spent months optimising a metric that turned out to be irrelevant, or inversely related to the goal the company actually cared about.

“The problem was never the data. It was that every metric lived on its own.”
Richard Oastler
Founder & CEO, KPI Tree

First, for people

A business is one system. So we modelled it as one.

Revenue was divorced from marketing spend. Product usage sat apart from churn. Customer satisfaction floated free of renewal rates. But a business is not a collection of separate numbers. It is a living system, and that system has logic that can be mapped. KPI Tree connects every outcome to the drivers beneath it, tests each connection against your data every night, puts a named owner on every metric, and checks whether the actions your team takes actually move the number.

Explore the platform

Liverpool Street

CausalModerate

Revenue

£384k

4.2%

AOV

£7.25

5.8%

Orders

52,998

2.1%

Then, for AI agents

The agents arrived, and hit the same wall.

AI assistants made an answer cheaper to get. They did not make it right. Point a model straight at a warehouse and it returns a number, then has to work out the why from scratch, because the warehouse does not hold what explains the number: what drives it, who owns it, what was tried last time and whether it worked. People and agents turned out to need exactly the same thing. So the causal model we built for your team became Canopy, the business context layer your agents read from.

Meet Canopy

zsh

~ % claude mcp add --transport http kpitree https://mcp.kpitree.co/mcp

Added HTTP MCP server kpitree with URL: https://mcp.kpitree.co/mcp to local config

~ % claude

> Why is revenue below target?

⏺ kpitree - analyze_metric (MCP)(metric: "Revenue", comparison: "month_over_month")

⎿ Revenue £425k against a £500k target, 15% below. Primary driver: conversion rate, down 23%, Granger-causal at a 3 day lag. Sarah Chen is Accountable.

⏺ Revenue is below target because checkout conversion dropped after Monday's release, not because fewer people arrived. Sarah Chen owns it. Shall I file the rollback as a task?

Decision Intelligence for humans and AI agents. One causal model, serving both.

Today KPI Tree is the company brain for how your business makes decisions. A metric moves, its owner is notified, the action is tracked and the impact is verified. The same evidence grounds every AI agent you run, so the answer to the founding question arrives with the proof to act on it. The film tells it in two minutes.

Canopy, KPI Tree's business context layer, in a two minute film

For humans · AI Analytics

For your team, a personalised action plan.

Everyone sees the whole system and the few things that fall to them, each with the driver attached and a window to measure it in.

Sarah Chen

Accountable · Conversion

Fix checkout payment errors, worth £31.5k/day

Checkout fix verified at +£32k, scale it

David Mitchell

Responsible · Paid traffic

Meta CPL up 40% since Monday, pause three ad sets

Organic steady, nothing needs you

Emma Thompson

Accountable · Cash collected

DSO drifted to 46 days, four invoices worth £118k

Collections push verified, DSO back under 40

For agents · Canopy

For your agents, context they can't get anywhere else.

Canopy records how your metrics drive each other, who owns them, what actually worked and the plan it all serves, and answers over MCP or in Slack.

Active Customers

Context

New pricing went live on Tuesday

eventon the timeline

Head of Sales out this week

absenceowners only

CRM migration blocked on security review

blocker

Chose annual billing push over discounting

decisionrationale kept

On the metric’s Context tab, in every agent answer.

Experience That Matters

Built by a team that's been in your shoes

Our team brings deep experience from leading Data, Growth and People teams at some of the fastest growing scaleups in Europe through to IPO and beyond. We've faced the same challenges you're facing now.

Built to sit inside an enterprise. From the first day.

We have sat on the other side of the security review and the procurement call. So the platform reads your data where it already lives, and it fits the stack you already run.

Your data stays yours. Read-only by design.

KPI Tree reads your warehouse with scoped, read-only credentials and computes every comparison and correlation in its own encrypted in-memory engine. Nothing is copied into a lake and nothing sits at rest. Anything briefly cached is encrypted with keys unique to your workspace, or with your own HSM-backed key.

How we handle your data

SOC 2 Type II. Continuously monitored.

Controls independently examined for Security, Availability and Confidentiality and monitored every day, with CREST penetration testing, single sign-on, directory sync and audit logs streamed to your SIEM.

KPI Tree for enterprise

On top of your stack, nothing to rip out.

KPI Tree starts alongside your warehouse, your semantic layer and your BI tool. It syncs the definitions you already govern and adds what none of them holds: cause, ownership and proof.

Integrations

The company brain for how your business makes decisions.

Understanding changes behaviour. Dashboards don't. Understand and automate every decision, with a name on every number.

Book a demo⌘B

The manifesto

People change when they see the system, see their place in it, and see what moves when they do.

Read why we built KPI Tree