Overall AI readiness score
A combined result across all audit signals.
Average
AI readiness audit: 7/21/2026Public technical data
Overall AI readiness assessment
How ready deepset.ai is for AI systems
deepset was independently audited by llmsmap. deepset.ai currently scores 70/100 for AI readiness. The result combines AI-specific files, crawler policy, sitemap discovery, structured homepage data, and—when available—the mobile Google Lighthouse technical profile.
Audit context
llms.txt is accessible and contains 1,836 tokens. No accessible llms-full.txt was detected, so deeper context still has to be assembled from regular pages. No separate ai.txt policy was detected; it is optional, but can clarify training, retrieval, and attribution preferences.
robots.txt is available. 11 of 11 tracked AI bots are not blocked. Declared sitemaps: 1. No Schema.org type was detected on the homepage. 4 OpenGraph tags were found and markup completeness is 40%, leaving more entity interpretation to crawlers.
The mobile Lighthouse profile adds Performance 26/100, Accessibility 90/100, Best Practices 81/100, SEO 100/100, and experimental Agentic Browsing 57/100. These signals have a limited weight: they complement rather than replace llms.txt, robots.txt, and structured-data checks.
Confirmed strengths
- Accessible llms.txt
- 1 sitemap declaration
Priority improvements
- 1Add llms-full.txt for richer first-party context.
- 2Add JSON-LD for the organisation, website, and core entities.
- 3Complete OpenGraph and canonical homepage metadata.
- 4Reduce mobile rendering delay and main-thread work.
llms.txt tokens1,836
llms-full.txt tokens—
ai.txt
sitemap.xml
Google Lighthouse technical profile
A mobile Lighthouse measurement. Google’s experimental Agentic Browsing category is explained separately and does not replace the broader llmsmap AI-readiness score.
26
Performance
90
Accessibility
81
Best Practices
100
Technical SEO
57
Agentic Browsing
What these results mean
Mobile performance is 26/100, with the largest visible content block appearing in 6.5 s and the browser main thread blocked for 1,750 ms. Layout shift was 0.167. The main thread is where the browser runs JavaScript, calculates layout, and paints the page; long work there delays both user input and browser-agent actions.
Accessibility scored 90/100, Best Practices 81/100, and technical SEO 100/100. The experimental Agentic Browsing category scored 57/100. It measures signals Google currently tests for software agents and is shown separately from the llmsmap AI-readiness score.
1
Free the main thread and accelerate the first view
Split long JavaScript tasks, defer non-critical scripts and styles, and shorten blocking request chains. This helps the primary content appear sooner and makes controls usable earlier.
2
Reduce code that loads without helping the page
Remove unused CSS and JavaScript, load heavy widgets on demand, and limit third-party scripts. Less code means less parsing and background work on the device.
3
Optimise images and their loading order
Serve correctly sized modern formats, prioritise the primary visual, and lazy-load content below the first viewport.
4
Reduce network delay
Improve server response time, remove unnecessary redirects and repeat downloads, and use compression, caching, and selective preconnect hints.
FCP4.5 s
First content
LCP6.5 s
Main content
CLS0.167
Layout stability
TBT1,750 ms
Blocking time
SI8.9 s
Visual speed
Metric glossary
- FCP · First content
- When the first text or image appeared on screen.
- LCP · Main content
- When the largest visible element in the first viewport rendered.
- CLS · Layout stability
- How much content shifted unexpectedly while loading; lower is better.
- TBT · Blocking time
- How long the browser main thread could not respond quickly to input.
- SI · Visual speed
- How quickly the visible viewport filled with content.
7/21/2026Lighthouse 13.4.0Mobile profile
AI readiness checks
Machine-readable files, crawler policy, discovery, and homepage markup.
llms.txt
File found and accessible
https://cdn.prod.website-files.com/6752ed90ddf74c98d49aa0a4/685a9ba674294405a4666913_llms.txtllms-full.txt
Full version was not found
ai.txt
ai.txt file was not found
Sitemap in robots.txt1
1 sitemap found
Schema.org (JSON-LD)
Schema.org markup was not found on the homepage
OpenGraph40%
4 OG tags found
AI bot access
Based on robots.txt analysis
GPTBotNot mentioned
OAI-SearchBotNot mentioned
ChatGPT-UserNot mentioned
Google-ExtendedNot mentioned
ClaudeBotNot mentioned
Claude-SearchBotNot mentioned
Claude-UserNot mentioned
BytespiderNot mentioned
CCBotNot mentioned
PerplexityBotNot mentioned
Perplexity-UserNot mentioned
Sitemaps
Declared discovery routes for crawlers and agents.
OpenGraph tags
Social preview metadata found on the homepage.
og:typewebsiteog:titleThe Sovereign AI Platform for Agentsog:descriptionDeploy production AI with full control. Build agents and RAG systems using the Haystack Enterprise Platform, trusted by enterprise, defense, and regulated industries.# deepset > deepset builds production-ready, custom AI agents and LLM applications with unmatched time-to-value, powered by the trusted open-source Haystack framework used by thousands of enterprises worldwide. # This file provides structured information to support responsible LLM indexing and usage. Inspired by llms.txt emerging standard. Source: https://www.deepset.ai/ Contact: https://www.deepset.ai/contact-us Sitemap: https://www.deepset.ai/sitemap.xml Last Updated: 6/18/2025 ## Overview Deepset's mission is to make custom AI solutions accessible to every organization, driving adoption and impact. By combining innovation with expertise, we simplify the complexity of LLM agent and application development, empowering teams to solve their most mission-critical challenges with speed, trust, and control. ## About/Company Information - [About deepset](https://www.deepset.ai/about): deepset’s mission is to make custom AI accessible to every organization, empowering businesses to solve critical challenges with secure, scalable, and innovative solutions. - [deepset AI Platform](https://www.deepset.ai/products-and-services/deepset-ai-platform): Build, test, and deploy custom GenAI agents and applications with the deepset AI Platform, powered by Haystack. - [Haystack](https://www.deepset.ai/products-and-services/haystack): Haystack is the leading open-source framework for building custom, production-grade AI agents and applications. As the backbone of the deepset AI Platform, it powers scalable, secure, and enterprise-ready solutions. - [AI Case Studies](https://www.deepset.ai/case-studies): Explore deepset AI case studies for companies and organizations such as: YPulse, Airbus, creed, Zeit Online, Manz, and others. - [AI Reports & White Papers](https://www.deepset.ai/guides): Read deepset's white papers and reports on the AI Industry. ## Products & Services - [Product Overview (Custom AI Applications)](https://www.deepset.ai/products-and-services): Build, test, and deploy custom AI agents and applications with the deepset AI Platform, powered by Haystack. - [Building AI Agents](https://www.deepset.ai/solutions/ai-agents): Build AI intelligent agents and virtual assistants that streamline workflows, solve real business challenges, and deliver practical, effective solutions. - [Intelligent Document Processing Solutions (IDP)](https://www.deepset.ai/solutions/intelligent-document-processing-idp): Process documents at scale, accelerate insight extraction, and boost workflow efficiency with AI-powered intelligent document processing (IDP) solutions. - [RAG Systems & Architecture](https://www.deepset.ai/solutions/retrieval-augmented-generation-rag): Build extraction tools, chatbots, and knowledge apps for AI Agents with flexible retrieval augmented generation (RAG) systems and solutions. - [Text to SQL](https://www.deepset.ai/solutions/text-to-sql): Leverage text-to-SQL with LLMs & AI solutions to simplify data analysis, generate SQL queries from plain language, & boost business intelligence insights. - [AI Enterprise Search](https://www.deepset.ai/solutions/enterprise-search): AI enterprise search solutions, software, tools, and platforms for fast, accurate results and better information access across your organization. ## Industries - [AI in Finance](https://www.deepset.ai/industries/financial-services): Generative AI in finance transforms complex operations into smart workflows, automates decisions, and improves analysis and customer experience. - [AI in Media/Publishing](https://www.deepset.ai/industries/media-and-publishing): Empower your editorial teams with modern AI tools that enhance and amplify the value of your quality content. - [AI in Legal/Law](https://www.deepset.ai/industries/legal): Improve accuracy, compliance, and team efficiency with intelligent AI assistants. - [AI in Retail/Consumer Goods](https://www.deepset.ai/industries/retail-and-consumer-goods): Integrate trusted AI apps and agents into your customer experience and operations. With deepset, you can customize AI to perfectly support your brand, customers, and business. - [AI in Technology](https://www.deepset.ai/industries/technology): Transform customer experiences and streamline operations with trusted, fully customizable AI solutions tailored to your business needs. - [AI in Life Sciences](https://www.deepset.ai/industries/health-and-life-sciences): Accelerate the shift from Gen AI strategy to execution with applications and agents designed to meet the industry's highest standards for quality and trust. - [AI in Government](https://www.deepset.ai/industries/government): Empower public sector agencies with secure, efficient, and custom AI solutions to deliver better services, enhance transparency, and modernize operations. - [AI in Manufacturing](https://www.deepset.ai/industries/manufacturing): Accelerate the transition from Gen AI strategy to execution with applications and agents that are designed to meet the highest standards of quality and trust in the industry. ## Resources - [deepset AI Webinars](https://www.deepset.ai/webinars): Attend and watch recorded webinars related to the AI industry, targeting: Developers, Products, Solutions, Partnerships, Customers & more. - [deepset AI Blog](https://www.deepset.ai/blog): The deepset AI blog covers AI Architecture, AI Fundamentals, AI Best Practices, AI Trends, and AI Solutions & Products. - [How to Build a Semantic Search Engine in Python](https://www.deepset.ai/blog/how-to-build-a-semantic-search-engine-in-python): Search your large collection of documents in the most effective way using open source tools. - [Understanding the Model Context Protocol (MCP)](https://www.deepset.ai/blog/understanding-the-model-context-protocol-mcp): How MCP is standardizing context integration for AI applications. - [The Beginner’s Guide to Text Embeddings](https://www.deepset.ai/blog/the-beginners-guide-to-text-embeddings): Text embeddings represent human language to computers, enabling tasks like semantic search. Here, we introduce sparse and dense vectors in a non-technical way. - [What Is Text Vectorization?](https://www.deepset.ai/blog/what-is-text-vectorization-in-nlp): A guide to the history and the role of text vectorization in semantic search systems. - [The Role of Preprocessing in RAG](https://www.deepset.ai/blog/preprocessing-rag): Half of a Retrieval Augmented Generation project is data preparation and indexing. - [Evaluating LLM Answers with the Groundedness Score](https://www.deepset.ai/blog/rag-llm-evaluation-groundedness): Improve LLM security, trust, and observability with our pioneering Groundedness metric for RAG applications. - [Evaluating RAG Part I: How to Evaluate Document Retrieval](https://www.deepset.ai/blog/rag-evaluation-retrieval): A guide to the evaluation of components in retrieval augmented generation. - [GraphRAG: Using the Power of Knowledge Graphs to Improve Retrieval and Generation](https://www.deepset.ai/blog/graph-rag): Discussion of the graph-based approach to processing complex datasets for context-rich LLM responses. - [Intelligent Document Processing with LLMs](https://www.deepset.ai/blog/intelligent-document-processing-with-llms): LLM-powered IDP in action: Three real-world examples of intelligent automation of complex reports and portfolios.
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Added 7/19/2026