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How it works

How does Deepify work?

Every plan rests on a guess about how the market will react to it. Deepify replaces the guess.

The models your customers consult are where the market's knowledge of your category now gets synthesised and handed out — every product, every price, every comparison, every complaint, pulled together and delivered as an answer to whoever asks. That layer knows things about your market. It just doesn't volunteer them.

So Deepify goes in and works it. Dozens of structured exchanges per run, across the assistants your customers actually use, live and web-connected — interrogated from angles a customer would never think to try, and mined for what the market wants, what it already has, and how it would react to the thing you're about to fund.

That's the raw material. What gets built from it depends on which question you're asking, so Deepify runs two engines.

Service 01 · Liquid GTM

Test a move before you make it

A launch, a price, a feature, a whole proposition. The engine mines the layer for real demand signal and web-verified comparables, then projects how each segment would respond — with what the read rests on, and what would prove it wrong.

Service 02 · The Audit

Check a product already in market

Once it's live, what the layer says about it becomes a fact you can measure. Every answer is graded against your own verified figures, scored with a confidence interval, and sealed into a record anyone can check.

This is not a ranking. Where you place in a list is a scoreboard for something that already shipped — it cannot tell you whether the thing you are about to build is wanted, priced right, or already owned by someone else.

1

Take the question

Your plan or move, or your product, exactly as you put it. No forms, no taxonomy to learn — a sentence is enough.

2

Read it back

We restate what we understood and name anything you left open, so a gap is visible rather than quietly filled in.

For a plan, every part is sorted by how new it is: what already exists, what's an upgrade to something you offer, what's new to the market, and what's new to the world. That sorting decides how the rest of the run is evidenced — a product that exists can be measured, and one that doesn't has to be reasoned about from things that do.

3

Establish the ground truth

Before we ask anyone anything, we establish what's actually true — from documents, not from a model's memory. Every fact keeps its source link and how confident we are in it.

For Liquid GTM, it's the live market around the move — who else is doing it, what they charge, how it landed — established by web search and kept with its sources. Any figure that can't be traced back to one of them is flagged in the briefing.

For an audit, it's your own pages: the real rate, the fee, the terms. The benchmark every answer is graded against is a document we can show you.

4

Ask the assistants

We put the questions your customers actually ask — phrased the way a person types them, not the way an analyst writes them — to the live, web-connected assistants. Several times each. Every answer is kept.

A Liquid GTM run asks about the demand your move depends on — does anyone want this, what would they pay, who already does it well. An audit asks about your product against a versioned set of intents: the rate, the catches, is it worth it, how to open one, how it compares, what you'd recommend.

Every answer we work from came from a real assistant answering a real question.

5

Weigh every projectionLiquid GTM

There is no verified truth to grade a projection against — the thing hasn't launched. So instead of a score, every projected response carries what it rests on: a live demand signal, a web-verified comparable, or reasoning.

And it carries a falsifier — the specific thing that would prove it wrong. A read that cannot be wrong isn't a read.

5

Grade every answerAudit

A separate model, running with no creative latitude, marks each answer against the verified truth: right, partly right, different, or it never gave a figure at all.

That last one matters more than it sounds. An assistant that simply omits your rate when a customer asks isn't wrong — it's absent, which is often the more expensive outcome.

6

Cap the confidence to the evidenceLiquid GTM

Confidence on a projection isn't the model's opinion of itself. It's a ceiling computed from how much evidence the run actually gathered — applied afterwards, in code, and it can only ever lower a number.

Thin evidence, low ceiling. No exceptions, and nothing reaches certainty, because nothing about an unlaunched product is certain.

6

Score it — with the uncertainty attachedAudit

Accuracy is never a bare number. Every score carries a 95% confidence interval and the number of answers behind it.

Ask three questions and the interval is wide, and we show it wide. Ask more and it tightens. That's the only honest way to buy confidence, and it means you always know how much weight a number will hold.

7

Put it in context

A number alone doesn't tell you what to do. Both engines establish where you stand against a real competitor set, sourced from the web rather than assumed.

An audit adds two things a score can't give you. Whether the assistants recommend you when a customer asks the category question without naming you — the question that decides whether they ever reach you at all. And how it compares to your last run, so you can see what moved, with a change only called a change when the intervals don't overlap.

8

Report it

Written for whoever needs to read it — board, executive, or analyst. Same evidence underneath, three altitudes on top. Every figure traces back to something you can open.

9

Seal the recordAudit

Everything behind the run — the questions, the models, the answers, the grading, the arithmetic — is fingerprinted and written to our ledger as it happens, before you see the result.

Anyone you hand the audit to can check it themselves — no account, no login, no need to take our word for anything.

An audit you can't check is an opinion with a logo on it. Every measured number traces back to the answer it came from, and any audit can be verified by someone who has never met us.