Autonomous AI agents don't just search. They browse, click, fill forms, book appointments, and complete purchases on behalf of real users. If your app can't be navigated by these agents, the task gets completed on a competitor's site instead.
If an AI agent hits a confusing navigation, a poorly labeled form, or a JavaScript-heavy page it cannot parse, it does not retry. It moves to the next option. The user never knows your business was passed over.
There is no notification when an AI agent fails on your site. No bounce in analytics. No error log. Revenue quietly drops before you connect it to the fact that autonomous agents have been routing tasks elsewhere for months.
OpenAI Operator, Claude Computer Use, Gemini agents, and Microsoft Copilot are already navigating real websites today. Most businesses have never tested whether their app works for these agents. Their competitors are starting to.
Accessibility audits, SEO, and even traditional AEO focus on human users and search crawlers. None of them test or fix how your app behaves when an autonomous AI agent tries to complete a real task inside it.
Your web app might work perfectly for a human user. But autonomous AI agents navigate differently. They traverse the DOM, read labels, follow links, fill inputs, and execute actions, all without a mouse or human judgment to fill in the gaps.
We audit your app the way an AI agent experiences it: checking semantic structure, navigation predictability, form labeling, and task completion paths. Then we fix what blocks agents and build what makes them choose you.
Most web apps fail on at least five of these. We audit every layer, prioritize the gaps by impact, and fix them in a single focused engagement.
Clean, meaningful HTML that AI agents can traverse without guessing which element does what. Proper heading hierarchy, landmark roles, and element labeling so agents understand your page the same way a human would.
Predictable, clearly labeled menus and page flows that AI agents can follow from landing to task completion. Agents fail when navigation is ambiguous. We make the path obvious.
Every input field, button, and checkout step clearly labeled so AI agents can complete actions accurately without human intervention. Unlabeled or ambiguous controls are the single biggest agent failure point.
A plain-language file at your domain root that tells AI agents what your app does, where its key pages and actions are, and what tasks it supports. The fastest way to help agents orient before they even start browsing.
Products, services, pricing, and contact data in structured JSON-LD that AI agents read instantly without parsing your prose. Agents making purchasing decisions on behalf of users rely heavily on this.
We simulate real AI agent sessions on your app, step by step, and document exactly where they succeed and where they fail. This is the only way to know your real agent-readiness score before a customer's AI agent finds out first.
JavaScript rendering barriers, lazy-loading issues, and robots.txt conflicts that block AI agents from accessing your content at all. We identify and resolve every technical obstacle before it silently costs you a task completion.
As AI agents mature, they prefer interacting with apps via API rather than browsing. We assess whether your app's key actions can be exposed through machine-readable endpoints and guide you on what to prioritize first.
We run real AI agent simulations on your web app and map every point where navigation breaks down, forms fail, or actions can't be completed. You get a clear report of what's blocking agents and the priority order to fix it.
We fix semantic HTML gaps, label forms and CTAs, set up your llms.txt, implement schema markup, and resolve crawlability issues. Every change is documented so your dev team knows exactly what was changed and why.
AI agent platforms update their navigation behavior constantly. As your app grows, new pages and flows need testing too. We retest against agent updates, optimize new features as they launch, and keep your app ahead of the curve.
Every engagement is scoped to the size and complexity of your app. These are starting points so you can plan a realistic budget before we talk.
All prices in CAD
Know exactly where you stand before you spend a dollar on fixes.
A full scan of your site's AI signal gaps: schema, entity clarity, crawlability, content structure, and llms.txt. Delivered as a prioritized action plan your team can act on immediately.
Full implementation for businesses that want the work done properly, once.
Complete AI visibility build: schema markup across all key pages, llms.txt creation, entity signal standardization, content restructuring for AI extraction, and a post-implementation report.
For businesses that want AI visibility maintained as the platforms evolve.
Ongoing monitoring of your citation footprint, schema updates as your content grows, new page optimization, and quarterly AI visibility reports so you always know where you stand.
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