Executive Summary

Many mid-market and enterprise product and marketing teams struggle to make canonical page content consumable for AI agents: public HTML is noisy, personalization fragments canonical sources, and teams end up building brittle scrapers or bespoke APIs to feed search, RAG pipelines, and chat assistants. The problem affects an addressable pool of roughly 250,000 mid-market and enterprise websites, where organizations already spend an estimated $30,000 ACV on DXP, content infrastructure, and integration services—a $7.5B market—because poor machine-readability translates directly into higher integration cost and worse automated customer experiences. You could build a developer-first service that exposes canonical marketing pages as clean Markdown endpoints with structured frontmatter, vector-friendly chunking, predictable canonical URLs and redirects, edge-deployable middleware, and connectors to major CMS/ DXP platforms. Offerings would include a lightweight runtime (edge functions/rewrites), a management plane for sync and access controls, and professional services to onboard enterprise sites; pricing could mirror existing DXP economics (target ACV ~$30k for full integrations) while also supporting a self-serve tier for developer adoption. Technical work will need to solve canonicalization without harming SEO, handle dynamic/personalized content safely, and keep latency low for real-time agent queries. This is an attractive moment: growth in LLM browsing and agents increases demand for clean, machine-readable canonical sources, headless and edge-first adoption lowers integration friction, and emphasis on structured content and semantic search makes Markdown-friendly endpoints a practical standard. Market score of 88/100 and revenue potential 82/100 reflect that opportunity, but competition is medium and you will face enterprise procurement cycles, incumbent DXPs, and the need to prove measurable agent improvements. To win, prioritize deep CMS integrations, demonstrable developer ergonomics, enterprise-grade security and SEO parity, and early pilot metrics that show tangible reductions in agent errors or retrieval latency—those will be the levers that convert developer interest into enterprise deals.

Executive Summary

Market Opportunity

Serve canonical marketing pages as markdown for AI agents targets a $7.5B = 250,000 mid-market & enterprise websites x $30,000 ACV (DXP + content infra + integration services) total addressable market with medium saturation and a year-over-year growth rate of 22% CAGR in headless CMS & developer DX tooling; 30%+ growth in AI content tooling adoption.

Key trends driving demand: LLM browsing & agents -- growth of agents that need clean machine-readable content drives demand for Markdown endpoints.; Headless + edge-first deploys -- more teams use middleware rewrites and edge functions, lowering integration friction.; Structured content & semantic search -- organizations want canonical sources that are friendly to vectorization and chunking.; Developers over marketers -- buying decisions are increasingly led by engineering teams who prefer code-first integrations..

Key competitors include Contentful, Sanity, GitHub Pages / raw.githubusercontent.com, ReadMe, Workarounds / Adjacent: LlamaIndex / web-scraping + ingestion stacks.

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Serve canonical marketing pages as markdown for AI agents

Executive Summary

Serve canonical marketing pages as markdown for AI agents

Executive Summary

Market Validation

Market Opportunity

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