Why we are building Materi

Decisions are the new bottleneck

AI has changed what a small team can produce. Engineers ship more in a week than they once shipped in a month. Sales and marketing teams reach prospects at a volume that used to take a whole department.

The constraint that remains is deciding what to do with all that output: which market to enter next, whether to raise prices, when to hire, how much runway to keep in reserve.

Our mission at Materi is to help high-growth teams make those decisions with speed and reliability.

Most decisions follow the same pattern. Someone asks a question. The team pulls the data and research, builds an analysis in a spreadsheet, drafts materials that set out the case, then debates until it decides.

Take a question that sounds simple: should we raise prices on our mid-tier plan? Finance models revenue under different churn assumptions. Operations works out what changes in billing and support. Strategy checks how competitors price comparable plans. Each input sits with a different person, in a different system, on a different timeline.

So one decision stretches into days or weeks. Nobody in the chain is doing anything wrong. Every step just depends on moving information between people and tools by hand.

Built for files, not decisions

The office suite was built for people producing files, not for agents running decisions. For an agent to handle the decision process reliably, it has to understand how your team works: the data you rely on, the choices you've already made, the way you do things. Legacy platforms were never designed to give it any of that, so an agent dropped into today's tools starts blind.

It has no context. It can't see your CRM, your finance system or last quarter's board pack, so every piece of background has to be carried in by hand. It has no memory either. Why growth was held at 10%, which margin definition the board agreed, how your team does things: that reasoning lives in inboxes and people's heads, well out of its reach, and it leaves when they do. And what it makes are dead documents, cut off from their source, impossible to trace and stale the moment the model moves on and next week's actuals land, so nobody can verify what it did or where a number came from.

Layer agents on top of these tools and you get work made quickly that you can't trust. A draft that arrives in minutes still has to be checked line by line against the spreadsheet, the inbox and whoever built the model, and then much of it is redone by hand, so the bottleneck stays exactly where it was.

What we're building

Materi reimagines the office suite as a single platform where agents and teams collaborate on the analysis and materials behind company decisions.

The spreadsheet, the document and the slides are three views of one connected artifact. A figure in a board paper links to the cell that produces it. A chart is bound to the range it plots. When the analysis changes, the materials know.

Your team does the thinking; Materi handles the mechanics. Five things make that work:

• Company context: agents draw on your data embedded from email, Slack, Google Drive and Notion, so nothing is approximated.
• Traceability: every figure, table and chart links to its source, and one click re-syncs anything that has drifted.
• Provenance: a full trail of who changed what, when and why, kept in the artifact instead of in someone's memory.
• Learns from iteration: Materi remembers your conventions, metrics and agreed assumptions, so each cycle builds on the last.
• Collaboration: agent edits arrive as pending changes you accept or revert. The agent drafts; the human decides.

What changes

Agents proactively pull together research, build structured analysis and draft materials as your team would. They hand you finished work with a full provenance trail and traceable data you can review and refine together.

Questions that used to kick off a week-long process can be answered while they're still being discussed:

• What happens to runway if we delay this hire by a quarter?
• Why did this margin figure change since last month's board pack?
• How would a mid-tier price increase affect revenue under our current churn assumptions?

The team then does the part that needs people: challenging assumptions, sharpening the argument and deciding. A change made in review flows through to every figure that depends on it. Nobody rebuilds the deck.

We'll know it's working when:

• A question raised in one leadership meeting is answered with sourced analysis before the next.
• Finance and strategy teams spend their time on judgement instead of copying and pasting.
• Every number in a board pack traces to its source in one click.
• Teams trust agent-drafted work enough to refine it rather than redo it.

Why now

Language models can now do real analytical work. They can read a model, reason about its assumptions and structure an argument. Generation has stopped being the hard part.

Trust and context are what's left, and those are problems of platform design. A better model plugged into the same disconnected tools won't solve them.

Meanwhile the rest of the company keeps speeding up. The decisions that direct that work have to keep pace, or they become the limit on growth.

For most companies, a well-founded decision has meant a slow one. We built Materi so teams no longer have to choose between speed and rigour.