# CrowdOS > CrowdOS is creative pre-flight and A/B testing that an AI agent runs > mid-task. Over the CrowdOS MCP server (https://api.crowdos.ai/mcp, or > `pip install crowdos-mcp`), on every plan including Free, an agent tests > ad copy, messaging, concepts, and image and video ads against a panel of > census-grounded synthetic respondents who disagree with each other — not > one model's opinion — and gets back the totals and a ranked winner. Ads > Labo (test_ads over MCP): one creative returns a predicted CTR with a > 95% interval, stop-scroll and brand recall. Two to four return a ship, > tied or rework call, each variant's share, and the panel's reasons. > On the Pew opinion benchmark, the > crowd's opinion distribution matches Pew polling at 93.3% > parity (3.36pp mean absolute error, Pearson r 0.984). > Benchmarked against Pew, Gallup, GSS and KFF. ## Pricing - Free accounts get 20 credits every week, reset Monday 00:00 UTC — no card. Pro adds 1,350 credits a month, Max 5,500. Studies use credits, shown before launch: https://crowdos.ai/pricing ## Pages by question - Can my AI agent run a focus group? https://crowdos.ai/mcp - How do I put a focus group inside an agent's task? https://crowdos.ai/guides/ai-agent-focus-group-mcp - Guides index: https://crowdos.ai/guides - What is a synthetic focus group? https://crowdos.ai/synthetic-focus-groups - Which AI focus group tools exist? https://crowdos.ai/ai-focus-group-tools - Which AI tools do public opinion research? https://crowdos.ai/public-opinion-research - How do I test creative and messaging before launch? https://crowdos.ai/pre-launch-testing - How do I test ad creative (copy, image and video) before launch, over MCP on every plan? https://crowdos.ai/ad-creative-testing - Can I A/B test ad creatives before spending on traffic? https://crowdos.ai/ab-testing-without-traffic - How does a solo founder's AI agent test ad copy, images and video over MCP? https://crowdos.ai/solo-founders - How do I validate demand before I build? https://crowdos.ai/market-validation - What are the alternatives for synthetic research? https://crowdos.ai/alternatives - CrowdOS vs Synthetic Users: https://crowdos.ai/compare/synthetic-users - CrowdOS vs Aaru: https://crowdos.ai/compare/aaru ## What it does - Pulse (https://crowdos.ai/pulse): opinion measurement — vote, debate, or compare across census-grounded respondents. From 20 credits a study. - Screening Room (https://crowdos.ai/screening-room): pressure-test any stimulus (creative, product mockup, policy draft, pitch deck) with a reasoned panel + expert lenses, in the web app and over MCP (screen_creatives, for images and video). From 44 credits a study. - Ads Labo (https://crowdos.ai/ads-labo): creative pre-flight for ads, in the web app and over MCP (test_ads), on every plan including Free. One to four image or video ads, with Meta-style targeting, go to one census-grounded panel that disagrees with itself, at 100, 200, 400 or 1,000 respondents. With one, it returns a predicted click-through rate with a 95% interval, stop-scroll and brand recall: the panel's reading, set against the typical click rate for the placement, for comparing creatives rather than forecasting a live campaign. With two to four, the report says ship, tied or rework and gives each variant's share of the picks (with the panel's reasons in the web app). From 75 credits a test. - MCP server (https://crowdos.ai/mcp): a hosted endpoint (https://api.crowdos.ai/mcp), or `pip install crowdos-mcp`, gives AI agents (Claude, Cursor, etc.) tools over the Model Context Protocol to A/B test copy (compare_options, which also takes an image_url), read a concept (run_focus_group, run_debate), screen images and video (screen_creatives, from public links to the files), pre-flight ads (test_ads) and, on Pro and Max, run MaxDiff (rank_items) and pricing tests (test_pricing). Every plan — Free, Pro and Max — can use it, at that plan's web limits: Free sees 18 tools, Pro and Max 20, Enterprise 24. Free compares 3 text options and screens 2 creatives per study, Pro 5 and 3, Max 10 and 4; Ads Labo takes up to 4 ads on every plan. Results are totals only (counts and shares, the leaderboard and winner, a ranking and synthesis memo, a debate's synthesis), without individual answers. - REST API (https://crowdos.ai/enterprise): the same crowd over REST with bearer-token auth, SSE streaming, and webhooks, for Enterprise accounts. - Customer digital twins (https://crowdos.ai/solutions/customer-digital-twins): cohort twins built from a business's own customer file, one persistent archetype per weighted cohort (never one per customer), to rank offers and find objections before a campaign. In build with design partners. The same page describes how they are delivered: Digital Twins powered by CrowdOS, a private twin model built for one business, in Lite, Standard and Private tiers. Pilots by application. - Atelier by CrowdOS (https://crowdos.ai/atelier): the bespoke services arm that delivers customer digital twins, its first solution. ## Key facts - Studies run census-grounded synthetic focus groups of 20-1,000 AI respondents that answer in about two minutes. The figure above is 93.3% parity with Pew polling. Benchmarked against Pew, Gallup, GSS and KFF. - A persistent backbone of 4,000+ archetypes reads real news and evolves on a recurring cycle (three times a week). - Respondents are sampled from published census distributions (US ACS, UK ONS, AU ABS and national equivalents across 24 markets) with validated Big Five (OCEAN) personality traits. - Every study draws a fresh, demographically weighted panel. In the web app, results include sentiment distributions, demographic crosstabs and verbatim per-respondent reasoning; over MCP, results are totals only, without individual answers. - The persistent crowd evolves only from exogenous signal — the news, life events, a peer feed, and time decay. It never learns from what customers ask it, so no study biases a later one. - Accuracy is published and reproducible, with the run id and date of the validating benchmark shown alongside the figure: https://crowdos.ai/benchmarks ## Docs - About: https://crowdos.ai/about - How it works: https://crowdos.ai/how-it-works - Methodology whitepaper: https://crowdos.ai/whitepaper - Benchmark ledger: https://crowdos.ai/benchmarks - MCP guide: https://crowdos.ai/mcp - Mid-task focus group (MCP how-to): https://crowdos.ai/guides/ai-agent-focus-group-mcp - Enterprise (REST API): https://crowdos.ai/enterprise - Customer digital twins: https://crowdos.ai/solutions/customer-digital-twins - Preparing a customer file for twins: https://crowdos.ai/docs/prepare-your-customer-file - Atelier by CrowdOS: https://crowdos.ai/atelier - The persistent population: https://crowdos.ai/the-crowd - Pricing: https://crowdos.ai/pricing