[verdict][curated prompt][source: tryprofound.com]
Can I vibecode Profound?
// buildable in a weekend, but real gaps stay open
The tracking loop is genuinely weekend-buildable: send a fixed prompt set through four model APIs on a schedule, count brand and competitor mentions, normalize the citations, and parse your access logs for AI crawler and AI referral traffic. That gets you most of the dashboard for one brand. The gaps are the honest part. API answers are not the answers the ChatGPT app or Google AI Overviews actually serve, you cannot measure what real people ask AI, and a number with no history behind it tells you nothing on week one.
confidence: medium
what it is: Tracks how ChatGPT, Perplexity, and AI Overviews describe your brand, and what AI crawlers do on your site
Buildability index · an editorial game
- Price 99 $/month weight: plus 3
- Time multi-day weight: plus 1
- Category seo and marketing no weight
- Moat proprietary data · integrations · execution quality weight: minus 4
- Confidence medium weight: zero
- What you lose 5 items weight: minus 2
- Site tryprofound.com (si apre in una nuova scheda) no weight
The moat outweighs the price: rebuilding this is a project, not an evening.
Gioco editoriale: il verdetto dice se un agente può, l’indice se conviene.
What you build
Run a fixed prompt set daily through the answer engine APIs, score brand and competitor mentions plus cited sources, and parse server logs for AI crawler and AI referral traffic.
what you need
- OpenAI, Anthropic, Gemini, and Perplexity API keys
- each provider's web search or grounding tool
- server access logs
- durable per-run storage
- a scheduler for daily runs
- an API budget that scales with prompts x engines x days
The dashboard is a weekend project. The prompt volume dataset behind it is not.
The prompt
A weekend with a coding agent. The gaps that stay are right below, under “what you lose”.
Build me a local AI answer engine visibility tracker for one brand. Requirements:
- Node 22, TypeScript, SQLite via better-sqlite3, a CLI, and a plain server-rendered
dashboard. Local only, no accounts, no telemetry.
- brand.json holds my brand name, aliases, domain, and competitor names. prompts.json
holds up to 40 buyer questions.
- `track run` sends every prompt through OpenAI, Anthropic, Gemini, and Perplexity with
each provider's web search or grounding tool enabled. Keys live in .env.
- Store one immutable row per run, prompt, and provider: raw answer, cited URLs, model
id, latency, and error text. Never overwrite an existing run.
- Cap concurrency at 3 per provider, retry twice on 429 and 5xx with backoff, and keep
failed cells visible in the report instead of dropping them.
- Detect brand and competitor mentions case-insensitively using the alias list, and
record the first-mention character offset as a crude prominence proxy.
- Score the sentiment of each brand mention in one cheap structured pass over stored
answers, after the run, never inline.
- Normalize citations to hostname plus canonical path, strip tracking parameters, then
compute owned-domain citation share and a top 25 sources table.
- `track serve` renders visibility per provider over time, share of voice against each
competitor, the sources table, and the prompts where competitors appear and I do not.
- `track crawlers --log access.log` parses server logs for GPTBot, OAI-SearchBot,
ClaudeBot, PerplexityBot, Google-Extended and friends, plus referral hits from
chatgpt.com and perplexity.ai, and reports which URLs they touched.
- Keep the bot user agent list in an editable JSON file. Log lines matching nothing get
counted as unknown agents, not silently discarded.
- `track export` writes runs, mentions, and citations to CSV.
- Fixture tests for mention detection, URL normalization, and log parsing.
- Out of scope: real consumer surface answers, prompt volume estimates, content
generation agents, teams, and hosted scheduling. Do not scrape the consumer web UIs.
- README: setup, per-run cost estimate, a cron line for daily runs, and a plain note
that API answers only approximate what users actually see.Curated prompt: written and reviewed by hand for this app. In English on purpose — it is the language coding agents work best in.
What you lose
- prompt volume data: what people actually ask AI is not measurable from outside
- the real consumer surfaces, since AI Overviews and the ChatGPT app have no API that matches what users see
- months of history and competitor baselines, without which a single week's visibility number means nothing
- upkeep as engines, crawler user agents, and citation formats keep changing
- the agent, recommendation, and product visibility layers stacked on top of the tracking
Why people still pay
Because the tracking is the cheap half. Profound sells the two things a personal script cannot produce: prompt volume data drawn from real conversations, so you know which questions are worth ranking for at all, and a maintained panel across nine answer engines including the consumer surfaces with no usable API. Marketing teams also want a number somebody else vouches for before it goes in a board deck.
moat: Proprietary data Integrations Execution quality what a moat is
prompt volume dataset, plus the upkeep of nine answer engines and their crawlers
Free alternatives
Not in the mood to build it? These already exist, they are free or open source, and we checked them one by one.
Rejected (3) — and why
- GEO/AEO Tracker (si apre in una nuova scheda) — Tracks answers, not crawlers; 221 stars and a required Bright Data account do not rescue the missing half.
- OneGlanse (si apre in una nuova scheda) — Broad AI monitoring, no crawler-log product, no releases and far too much infrastructure for 141 stars.
- OpenSEO (si apre in una nuova scheda) — Mature SEO software, but two AI surfaces and no crawler-log analysis do not replace Profound.
Who has already built it
Starting from here is still vibecoding: the prompt is for when you want it exactly your way.
- Elmo (opens in a new tab) — MIT-licensed self-hosted AEO/GEO tracker: runs your prompts across the major answer engines and records mentions, competitors, and cited sources (alive)
- llm-brand-tracker (opens in a new tab) — Small research-grade toolkit for monitoring brand visibility in LLM search; useful as a starting point, last commit mid-2025 (alive)
Do you agree?
The vote balance
Ancora nessun voto: il tuo è il primo.
Nessun voto ancora — il primo pesa.
