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Ad teardown

Break a live ad into hook, offer, CTA and awareness stage — the tagging behind teardown of 724 ads across 37 brands.

724 live ads · 37 brands · ~40s · $0.09@TheMattBerman

Matthew Berman had Jev break down 724 live ads from 37 brands in about 40 seconds for 9 cents of tokens — every hook, format, offer, CTA, awareness stage and landing-page mismatch. It doesn't write a report first; it turns 724 ads into data you can filter and compare.

Live toolRun this on your own data with the Ad Analyzer

Try it live

This is the real thing, not a mockup. Edit the input, hit Run, and Jev returns every typed answer in one round trip — free, no signup. Now picture the same call fired across thousands of items in parallel.

POST api.typesafe.ai/v1/systemone
state — the input software gives Jev289c
questions — the typed decisions you want back
choicehook
What is the primary hook style?
one of: problem_agitate, question, bold_claim, social_proof, offer
scoreawareness
What customer awareness stage does this ad target (Schwartz)?
→ 0…4 · 5 levels
choiceoffer_type
What is the main offer?
one of: free_trial, discount, lead_magnet, demo, none
noulclear_cta
Is there a single, clear call to action?
probability 0.0 … 1.0
noulfriction_low
Does the ad reduce sign-up friction (e.g. free, no card, fast)?
probability 0.0 … 1.0
real API · free · no signup
Typed, calibrated output appears here.
Pick a demo, tweak the input, and hit Run Jev.
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The decisions Jev makes

In a single call, Jev evaluates each of these — in parallel, against the same input:

choicehook

What is the primary hook style?

picks one of these options:

  • problem_agitate — names a pain the reader feels
  • question — opens with a question
  • bold_claim — a big/contrarian claim
  • social_proof — leads with proof or numbers
  • offer — leads with the deal itself
scoreawareness

What customer awareness stage does this ad target (Schwartz)?

rates it on an ordered scale:

  1. unaware
  2. problem-aware
  3. solution-aware
  4. product-aware
  5. most-aware
choiceoffer_type

What is the main offer?

picks one of these options:

  • free_trial — a free trial
  • discount — a discount or price cut
  • lead_magnet — a free download/resource
  • demo — a demo or call
  • none — no explicit offer
noulclear_cta

Is there a single, clear call to action?

returns a calibrated yes/no probability.

noulfriction_low

Does the ad reduce sign-up friction (e.g. free, no card, fast)?

returns a calibrated yes/no probability.

The exact request

This is the real payload behind the live demo — copy it, change the state, and you're building:

{
  "model": "jev-latest",
  "state": "Facebook ad creative:\n\nHeadline: \"Still doing your books in a spreadsheet?\"\nPrimary text: \"Founders waste 6 hrs/week on bookkeeping. Our AI does it in 10 minutes. Try free for 30 days — no card needed.\"\nCTA button: \"Sign Up\"\nImage: split screen of a messy spreadsheet vs a clean dashboard.",
  "questions": {
    "hook": {
      "type": "choice",
      "instructions": "What is the primary hook style?",
      "criteria": {
        "problem_agitate": "names a pain the reader feels",
        "question": "opens with a question",
        "bold_claim": "a big/contrarian claim",
        "social_proof": "leads with proof or numbers",
        "offer": "leads with the deal itself"
      }
    },
    "awareness": {
      "type": "score",
      "instructions": "What customer awareness stage does this ad target (Schwartz)?",
      "criteria": [
        "unaware",
        "problem-aware",
        "solution-aware",
        "product-aware",
        "most-aware"
      ]
    },
    "offer_type": {
      "type": "choice",
      "instructions": "What is the main offer?",
      "criteria": {
        "free_trial": "a free trial",
        "discount": "a discount or price cut",
        "lead_magnet": "a free download/resource",
        "demo": "a demo or call",
        "none": "no explicit offer"
      }
    },
    "clear_cta": {
      "type": "noul",
      "instructions": "Is there a single, clear call to action?"
    },
    "friction_low": {
      "type": "noul",
      "instructions": "Does the ad reduce sign-up friction (e.g. free, no card, fast)?"
    }
  }
}

Wire it into your code

Read the typed answers and branch in plain code — no parsing. Auto-handle the high-confidence cases and route the uncertain ones to a bigger model or a human. It's one API call and output is free, so ask every question you need at once.

Build your own

Every scenario above is a single API call. Try any of them free in the playground, then get a hosted key to ship it — no waitlist.

Run this demo ▶Get an API key →
Ad teardown — a Jev use case with a live demo · Jev by TypeSafe AI