> For the complete documentation index, see [llms.txt](https://docs.aloop.icustomer.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aloop.icustomer.ai/getting-started/what-icustomer-is.md). # What iCustomer Platform is iCustomer Platform is the always-on Intelligence system above your channels: audience intelligence, signals, decisions, and causal measurement. You already have campaign tools. Paid media, email, programmatic: each runs its own bids, manages its own creatives, and reports its own results. The problem: every tool grades its own homework. Each shows you the numbers that flatter it, none sees your whole funnel, and none is accountable to your goals, target and outcomes. iCustomer is not some campaign tool, and neither a CDP. A CDP stores and segments your data and waits for you to decide. iCustomer is the "always-on intelligence system" that sits *above* your channels and does the deciding, and it is built around three things. ## Audience intelligence Who your audiences are: your ideal customer profile, personas, and fit, built from public information about your company and enriched by your connected tools like CRM and ad accounts. It stays fresh on its own. This is the **who**. ## Signals and decisions The buying signals your audiences throw off, captured and scored with FIRE (Fit, Intent, Recency, Engagement) so you know who is Hot, Warm, or Cold right now, and the decisions that follow. Decision-first: the system decides what to do for each audience before it picks a channel. A demo request, for example, lifts Intent, flips an account to Hot, and triggers the next move. This is the **why now** and the **what to do**. ## Unified measurement One honest scoreboard. Every event, decision, and outcome is tied together and graded independently of what each tool says about itself, across all your channels. This is the **what actually worked**. ## Three names to know * **iHarness**: the agent running your growth loop. It executes, within the guardrails you set, rather than only suggesting. * **Growth Brain**: the self-learning context iHarness runs on. Everything you connect accrues into it. It sits on your data infrastructure, your CRM and your warehouse, and does not replace it. * **iReveal**: identity, outcomes, and causal proof from your own site traffic. In one line: iHarness runs on your Growth Brain. It works where your team works: the web app, Slack, and agents connecting in. Enterprise runs in your cloud or warehouse. SMB runs in ours. Same architecture, different home. The full picture is in [System architecture](/concepts/system-architecture.md). ## What it doesn't do iCustomer doesn't run your media buys, send your emails, or make your creative. Those stay where they are: in each channel tool, with your campaign manager, agency, or with your GTM lead. You don't staff a full team. You get an AI data and decision scientist working on your data & outcomes, so your creative and brand people can keep doing what they do best. ## The thesis You can't grade your own homework. The tool that spends the budget shouldn't be the one telling you it worked. Audience intelligence and signals lead to decisions, decisions lead to actions & outcomes, and outcomes are measured honestly, so you win on the revenue you're after, not the vanity metrics each campaign tool reports about itself. Next: [The loop in one page](/getting-started/the-loop.md). --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.aloop.icustomer.ai/getting-started/what-icustomer-is.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.