Peec AI Alternative: on-demand AI visibility audit

Run a current, prompt-level AI visibility audit for one public brand. This Actor sends a bounded set of buyer-intent prompts to the AI answer engines you select and returns one source-linked observation per prompt and platform: brand mention, approximate first-mention position, heuristic sentiment, competitor share of voice, owned-domain citation, source domains, answer excerpt, model route, and collection time.

Use it for a reproducible API-based snapshot you can export or rerun. It is designed for current prompt evidence and pairs well with specialized Google AI feature measurement or a multi-user monitoring suite when those are the next workflow step.

What it replaces and what it does not

This is a workflow alternative for the narrow job of running a small, current, source-linked AI visibility audit from structured input. It does not replace Peec AI's dashboard, daily historical tracking, prompt/topic management, agency workspace, campaign reporting, product-shopping monitoring, crawlability checks, Google AI Overview/AI Mode coverage, or its broader MCP project-management surface.

Quick start input

{
  "brandName": "Apify",
  "targetDomain": "apify.com",
  "industry": "web scraping tools",
  "competitors": ["Bright Data", "Octoparse"],
  "queryTemplates": ["recommendations", "alternatives", "category_leaders"],
  "platforms": ["perplexity", "chatgpt", "gemini"],
  "maxQueries": 3,
  "responseFormat": "concise"
}

brandName is the only required input. Add targetDomain to separately measure whether an owned page appeared in the returned sources. maxQueries is a hard input cap: the Actor creates at most that many unique prompts, then checks each selected platform. Start with one platform and one prompt when you are validating a new topic.

Output: what each row means

Field	Meaning
platform	The requested answer-engine route for this observation.
query	The exact buyer-intent prompt sent during the run.
brandMentioned	Whether the answer text named the tracked brand.
brandPosition	Approximate first-mention position in that answer; it is not a search-result rank.
brandShareOfVoice	Tracked-brand mentions divided by the tracked brand plus the supplied competitor mentions in this answer.
sentiment	Positive, neutral, or negative heuristic from the mention context.
domainCited / citedUrls	Whether the supplied owned domain was among extracted source URLs, plus all available URLs.
sourceDomains	Deduplicated domains derived from citations or grounding metadata.
checkedAt	UTC timestamp for this observation.

Each completed row is a dated sample of an AI answer. Compare matching prompts, platforms, and settings across runs; use the row as prompt-level evidence rather than a durable ranking or causal explanation.

{
  "runId": "exampleRun123",
  "platform": "perplexity",
  "query": "Which web scraping tools should a data team consider?",
  "queryCategory": "custom",
  "brandName": "Apify",
  "targetDomain": "apify.com",
  "brandMentioned": true,
  "brandMentionCount": 2,
  "brandPosition": 1,
  "brandShareOfVoice": 0.5,
  "sentiment": "positive",
  "domainCited": true,
  "citedUrl": "https://apify.com/",
  "citedUrls": ["https://apify.com/"],
  "sourceDomains": ["apify.com"],
  "competitorMentions": ["Bright Data"],
  "competitorMentionCount": 2,
  "aiAnswerExcerpt": "Apify is a common choice for structured web data workflows.",
  "modelUsed": "perplexity/sonar",
  "checkedAt": "2026-08-31T12:00:00.000Z"
}

Price and cost boundary

The proposed pricing contract is Pay per event plus Apify platform usage: $0.10 for each validated ai-visibility-check row and $0.00005 for Actor start. Platform usage is additional. A run with three prompts across three selected engines has a maximum of nine value events before any account-level charge cap.

Check the live Pricing tab after private deployment for the effective event record and exact per-run charges. Provider routes that produce useful observations create the documented value-event rows.

API usage

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('khadinakbar/peec-ai-alternative').call({
  brandName: 'Apify',
  targetDomain: 'apify.com',
  industry: 'web scraping tools',
  competitors: ['Bright Data', 'Octoparse'],
  platforms: ['perplexity'],
  maxQueries: 1,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

After any run, read OUTPUT for the terminal outcome and RUN_SUMMARY for provider attempts, charges, completion counts, source-domain aggregates, and workflow guidance. COMPLETE, PARTIAL, VALID_EMPTY, and INVALID_INPUT are distinct successful terminal states; UPSTREAM_FAILED and CONFIG_ERROR preserve the diagnostic needed to configure the next run.

Agent prompt card

Audit Apify's visibility for one buyer-intent question about web scraping tools. Check Perplexity only, compare Bright Data and Octoparse, and return the mention flag, share of voice, owned-domain citations, source domains, timestamp, plus the terminal RUN_SUMMARY outcome.

Keep an agent's call bounded by supplying the brand, a real prompt or one clear template category, selected platform(s), and a small maxQueries. The Actor is read-only with respect to the public brands and prompts supplied, so it works cleanly as a focused data-collection step.

How this workflow compares with Peec AI

Decision dimension	This Actor	Peec AI
Scope	A bounded current snapshot for supplied prompts and selected routes.	A broader AI-search analytics platform with ongoing projects, dashboards, and reporting.
Input workflow	JSON input: one brand, optional domain and competitors, bounded prompts, and selected engines.	Project setup, tracked prompts, topics, and organization workflows.
Output contract	One flat record per prompt x platform plus explicit OUTPUT and RUN_SUMMARY records.	Product-level analytics, trends, prompt management, source analysis, and reports.
Billing and cost	Proposed event pricing is transparent in the Actor contract but awaits live charge verification.	Published subscription and credit plans; check Peec AI's current pricing before comparing a workload.
Effective efficiency	No same-job cost or time advantage is claimed until both products are observed on the same workload.	Better fit when a team needs its maintained historical dataset and dashboard workflow.
Integrations and automation	API-shaped runs and storage are declared; named MCP-client integrations will be added after an observed end-to-end test.	Peec documents its authenticated MCP server and project-level tools.
Freshness and provenance	Each observation declares a prompt, provider route, extracted sources, and UTC checkedAt timestamp.	Peec documents ongoing per-engine monitoring and trend analysis.

Choose this Actor when the decision is specifically to obtain a small, machine-readable visibility sample at a known input boundary. Choose Peec AI when the decision requires its broader monitoring, analysis, collaboration, or engine coverage. This independent Actor is not affiliated, associated, or endorsed by Peec AI.

Focused standalone workflow

This Actor is designed as a focused standalone workflow. Start with a small prompt set, then pass the dated rows to your reporting, content-review, or analytics workflow. For a public multi-engine dashboard, use the AI Search Brand Monitor after this snapshot when that broader reporting step is the decision need.

Best results and workflow guidance

• Use buyer questions that your prospective customers actually ask. Keep an identical prompt set for trend comparisons.
• Use responseFormat: "detailed" only when a human needs more answer context; concise rows keep downstream agent output smaller.
• Include only unambiguous competitor names. Share of voice is limited to the supplied names and the response text; it is not market-wide share.
• AI providers and their web grounding can change. Review a missing citation as a current observation and pair it with the prompt, source list, and timestamp.
• Treat the recommendations generated in RUN_SUMMARY as suggestions for human review and use the underlying evidence to guide the next content or source-coverage decision.

Builder's note

I designed this Actor around prompt-level evidence because a visibility percentage without the prompt, answer route, source list, and collection time is hard to review responsibly. My goal is to make a small audit easy to rerun and export while keeping each observation clear enough for an analyst or agent to trace back to its exact input.

Responsible use

Use public brands and prompts you are authorized to analyze. Keep prompts limited to public business context, and review provider terms, your organization's policies, and the underlying prompt, sources, response excerpt, and timestamp before making external claims.