For lean leadership teams

Win support for the decision with numbers your team can check.

Resource allocation, hiring, pricing, the board proposal. The information sits across teams and approval needs credible numbers. Tegy consolidates what you have, checks the numbers, and writes a case the room can review.

See an example

Why it matters

Other people have to approve the decision.

In a leadership team, the work is assembling the evidence, agreeing the assumptions, and handing the decision to whoever executes without losing the reasoning on the way.

Decisions Tegy is built for

Resource allocation and hiring
Pricing and packaging
Board proposals and the narrative
Product and go-to-market priorities

What you get

Less preparation, a reviewable case, an easier handoff.

Time back

Less preparation before the meeting that decides.

A defensible business case

Reasoning, numbers, and sources the room can check.

Clean handoff

The recommendation and next steps ready for whoever owns execution.

Why the usual choices fall short

Generic AI leaves the assembly with you. A consulting project is disproportionate.

Where it breaks

Tegy

A general AI assistant

Agrees with you. You still choose the method, push back on weak logic, manage the context, and turn a chat into a decision artifact.

Runs a repeatable process, shows the evidence and assumptions, and writes a recommendation ready to review and share.

A large consulting engagement

Gets it right, months and six figures later. The fees, setup, and staffing can be a poor fit for a decision you need this quarter.

Senior-grade research, analysis, and reasoning you can use immediately and inspect.

What Tegy does

The work behind the decision, done in the open.

Reads what you already have

Notes, spreadsheets, decks, call transcripts, research. Bring it as it is. No clean brief required.

Finds what is missing

The facts your current thinking skips and the risks it hides. Tegy stops to ask you about the assumptions the decision depends on instead of quietly guessing.

Compares the real options

Side by side, with the second-order effects and the numbers checked.

Writes the recommendation

Evidence, assumptions, and next steps shown. Ready to review, share, and hand to the next owner.

See it on a real decision

One pricing call, start to finish.

A normal AI chat agrees with you. A consulting firm gets it right, months and six figures later. Tegy gives you the rigor now.

The question

We think we're underpriced. Do we raise prices, and by how much, without losing customers?

A normal AI chat

Good question. There are arguments on both sides. Raising prices could grow revenue, but it might push some customers away. A small increase is safer; a big one is riskier. It really depends on your goals and your market.

Sounds good. Agrees with you. Says nothing.

How it's thinking

Mapped what each segment will actually pay
Modeled the revenue gain against the churn risk
Found the assumption you hadn't tested

Stops to ask youYour biggest accounts may be far more price-sensitive than the rest, and you haven't tested it. Confirm it, fix it, or flag it as unknown.

What you walk away with

An executive summary
A pricing playbook
A market map
A board-ready deck
A financial model
An investment memo
An action plan

Done in minutes, not weeks.

Founding user program

Bring a real decision.

Founding users get 3 days free. After that, $39 a month per seat covers 10 decisions (solve, review, brief), or $19 a month per seat covers 3.

Larger team? Get in touch