
Otterly.AI
Profound
Am I on AI
Ahrefs
Attensira
Diploria AI
Promptwatch
AI SEO Search Visibility & AI Rank Tracking Platform for LLM Search Engines like ChatGPT - GEO/AEO/LLMO

DocRaptor
Turn templates, HTML or Markdown into PDFs, images and e-invoices via API.

Which is more popular?
Website, pricing, platforms and company facts side by side.
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| Website | llmrefs.com | dynamicdocumentapi.com |
| Pricing | ||
| Company | Startup from the United Kingdom · 1 - 9 employees · 2025 | — |
| Listed in |
In their own words, as submitted to SaaSHub.


LLMrefs is an AI search analytics platform that tracks brand visibility across generative AI search engines. It shows whether AI assistants like ChatGPT, Perplexity, and Gemini mention your brand when users ask questions about your industry. Supported AI Search Engines LLMrefs monitors 11...
Dynamic Document API renders PDFs and images from your own templates, from HTML and CSS or from Markdown. Use it through a REST API, SDKs for Node and Python, Zapier, Make and n8n, or an MCP server for AI agents like Claude and ChatGPT. It also creates validated e-invoices (XRechnung, ZUGFeRD /...
What each product offers, as listed by its team.


No features have been listed yet.
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
No analysis of DynamicDocumentAPI yet.
Walkthroughs and reviews on video.
LLMrefs - AI SEO Keyword Rank Tracker for LLM Search Engines
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How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing LLMrefs and DynamicDocumentAPI.
LLMrefs's answer
Track keywords, not prompts Most AI SEO tools make you manage individual prompts. LLMrefs lets you add keywords and automatically generates prompt variations based on real conversations users have with AI chatbots. This saves time and produces more realistic results.
Statistical significance, not magic numbers Many competitors show vague "visibility scores" that are hard to interpret. LLMrefs uses transparent metrics like Share of Voice and Position. Results are aggregated and weighted across every prompt variation to ensure statistical significance.
Affordable with no hidden fees LLMrefs Pro is $79 per month and includes all 11 AI search engines. Competitors often charge extra per engine or have tiered pricing that gets expensive quickly.
Agency-friendly from day one One subscription covers unlimited projects and unlimited team members. Agencies do not need to buy separate accounts for each client.
Data quality focus LLMrefs emphasizes being the only platform that takes data quality seriously. They continuously check prompts and only report results when they have enough data to be statistically significant.
Comprehensive engine coverage Eleven AI search engines tracked in one dashboard. You do not need separate tools for ChatGPT, Perplexity, Google AI Overviews, and others.
DynamicDocumentAPI's answer:
Most document APIs do one thing: convert HTML to PDF, or fill templates. Dynamic Document API does both, adds image templates, PDF merging and validated e-invoices, and offers them through a REST API, SDKs for Node and Python, Zapier, Make, n8n and an MCP server for AI agents. Data is processed and stored in the EU only, files come back as signed links that expire, and storing nothing at all is a supported option. Pricing is predictable: one published credit table, the same core features on every paid plan and a spend cap you control. We also publish a render-time benchmark with its method and raw data, so you can check our speed instead of trusting a claim. The free plan includes 50 renders a month without a credit card.
DynamicDocumentAPI's answer:
It covers the whole path from data to finished document in one API: you design a template in a visual or HTML editor (or send raw HTML, CSS or Markdown), send JSON, and get a PDF or image back. The same service also creates e-invoices (XRechnung, EN 16931, Factur-X / ZUGFeRD) that are validated against the official rules before they are returned, and can embed them in the PDF. Rendering is deterministic: the same template and data always give the same document, laid out by a headless browser, with no AI model generating content. Everything runs in the EU (Germany). It also ships an MCP server, so AI agents like Claude and ChatGPT can render documents directly.
DynamicDocumentAPI's answer:
Developers and product teams whose software has to send documents: invoices after a payment, certificates after a course, reports, labels and statements. Typical users are SaaS companies, marketplaces, e-commerce and learning platforms. A second group are businesses in Germany and the EU that need compliant e-invoices (XRechnung, ZUGFeRD) for the German B2B e-invoicing mandate and public-sector buyers. No-code builders use it through Zapier, Make and n8n, and teams building AI agents use the MCP server.
DynamicDocumentAPI's answer:
Almost every product eventually needs to produce documents, and most teams end up building their own rendering stack: a headless browser, fonts, page breaks, storage and retries. It works until an invoice splits a table row or a certificate shows the wrong date, and then it becomes a support ticket. We built Dynamic Document API to be that layer for them: templates, rendering and delivery as one service, hosted in Europe, treating pagination, fonts and formatting as engineering problems rather than edge cases. When e-invoicing became mandatory for B2B in Germany, we added validated XRechnung and ZUGFeRD output, and with AI agents producing more paperwork, an MCP server followed.
DynamicDocumentAPI's answer:
Rendering runs in Rust workers that drive headless Chromium over the DevTools protocol, with MiniJinja for templates. The API and control plane are built with Django and Django REST Framework, with Celery, PostgreSQL, Valkey and NATS JetStream for queues and events, and S3-compatible object storage for files. PDF/A output is checked with veraPDF and e-invoices with the official KoSIT validator. The dashboard and website are built with Next.js. Everything runs on Kubernetes in data centres in Germany.
DynamicDocumentAPI's answer:
Dynamic Document API is a young product. Our users are mostly developers and small SaaS teams, and we don't name customers without their permission.
Share your experience with using LLMrefs and DynamicDocumentAPI. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


On prompts: LLMrefs builds them from your keywords, GeoSuite generates them from your brand and market, and Profound's trial uses a fixed set. Everyone else lets you type the questions your customers actually ask.
We have no reviews of DynamicDocumentAPI yet. Be the first one to post
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