INITE

What it is

INITE is an AI-native company that helps 10-200 person B2B businesses improve their visibility to AI assistants and deploy automated workflows. The company offers the AI Visibility Analyzer, a free audit tool that checks how ChatGPT, Claude, Perplexity and AI search engines understand a website by examining AI identity files, crawler policies, Schema.org markup and citation readiness. INITE also provides consulting and implementation services, deploying 1-3 automated workflows in production within 2-4 weeks through its INITE Solutions division and vertical products. The company operates a shared infrastructure platform with core components for identity, brain and billing, supported by the INITE Runtime. Founded in 2020, INITE serves companies worldwide, focusing on sales, support and operations automation with transparent ROI modeling before any work begins.

Quick answers

What is an AI visibility audit?

A check of whether AI assistants can reach, identify and quote your website. It is a different question from search ranking: a page can sit first in Google and still be invisible to an assistant that robots.txt blocks, or that cannot resolve which company the site belongs to.

What does this audit check?

Crawler policy for GPTBot, ClaudeBot and PerplexityBot; the AI identity files, ai.json and llms.txt; the Schema.org graph; canonical and hreflang; Open Graph; Core Web Vitals; and a citation test that asks live models what they say about your brand.

How long does it take, and what does it cost?

About sixty seconds, and nothing. Two runs a day need no card and no account, and the report is on screen when it finishes.

What do I do with the result?

Every finding names the file or the page it came from, so most are a change your own team can make in an afternoon. Where the work is larger — a schema graph to rebuild, pages an engine cannot retrieve — that is what the visibility engagement is for.

How are ROI and payback calculated?

Current time per task and fully-loaded salary cost are measured on your real data. The implementation cost is divided by monthly operational savings to determine payback in months. If projected payback is longer than the agreed window, the workflow does not enter the build backlog.