Replace Profound?
KINDA · weekend projectThe 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.
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.
$ open in your agent (prompt prefilled, you press enter) or copy it raw
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.
xprompt volume data: what people actually ask AI is not measurable from outside
xthe real consumer surfaces, since AI Overviews and the ChatGPT app have no API that matches what users see
xmonths of history and competitor baselines, without which a single week's visibility number means nothing
xupkeep as engines, crawler user agents, and citation formats keep changing
xthe agent, recommendation, and product visibility layers stacked on top of the tracking
What does the Profound verdict mean?
The core job looks buildable, with meaningful gaps: 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. Read the full tradeoff list before committing. This research record is not a hosted IVCIFY tool.
What price does this directory record show for Profound?
The directory records $99/month for Starter, checked 2026-08-04. Verify the source before making a purchase decision. This reference stays outside retail Stack Math unless current matched evidence supports the comparison.
What do I lose by replacing Profound?
Honestly: 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. If any of those are load-bearing for you, keep paying.
Is there an open-source alternative to Profound?
The listed prior art includes Elmo (MIT-licensed self-hosted AEO/GEO tracker: runs your prompts across the major answer engines and records mentions, competitors, and cited sources), llm-brand-tracker (Small research-grade toolkit for monitoring brand visibility in LLM search; useful as a starting point, last commit mid-2025). Inspect those projects before starting from a blank prompt.