Build vs buy

Building your own AI ASO vs Appeak Pro

Rolling your own AI ASO pipeline — LLM prompts, scrapers, scoring, guardrails, and a UI — is a multi-quarter engineering project. Appeak Pro is the production version, already tuned to the store algorithms.

It's tempting to wire ChatGPT or Claude into a few scrapers and call it AI ASO. In practice, a reliable pipeline needs keyword expansion, volume and difficulty scoring, store-policy guardrails, and a UI — plus ongoing maintenance as the stores change.

Appeak Pro is that pipeline, built and maintained for you: keyword targeting, metadata rewrites, and creative direction with store-policy guardrails baked in.

  • Build-your-own AI pipeline
    Cost
    1–2 engineers + LLM credits
    Time to production
    1–2 quarters to build, ongoing maintenance
    Coverage
    What you have time to build — usually keyword expansion only
  • Generic LLM prompted manually
    Cost
    Subscription only
    Time to production
    Same day
    Coverage
    Generic suggestions — no store data, no scoring, no guardrails
  • Appeak Pro
    Cost
    Flat subscription, no eng cost
    Time to production
    Minutes per audit
    Coverage
    Keywords + metadata + creative direction with store-policy guardrails
Why teams switch

What you get with Appeak Pro

No pipeline to build

Skip the quarters of engineering and the ongoing maintenance as store algorithms shift. It's already in production.

Store-policy guardrails baked in

Character limits and store guidelines are enforced in the output, so you're not shipping metadata that gets rejected.

Beyond keyword expansion

Most home-grown pipelines stop at keywords. Appeak Pro covers metadata rewrites and creative direction too.

When building your own makes sense

If ASO tooling is a core product bet — you're a large publisher with unique data and spare engineering capacity — building in-house can pay off. For everyone else, the build-and-maintain cost rarely beats a production engine that's already store-tuned.

FAQ

Common questions

  • A general LLM gives generic suggestions with no store data, no volume/difficulty scoring, and no policy guardrails. Appeak Pro combines the LLM step with real store data and scoring, then enforces character limits and store rules in the output.

See it on your own app

Run a free audit and get scored keywords, metadata direction, and an AI-visibility read in minutes — no agency ramp, no stack to stitch together.

Run a free audit