- Visibility5
- Citations3
- Sentiment100
- Site quality80
- AI readiness36
AI assistants rarely name Avaya, mentioning the company in 2 out of 60 answers; Genesys and NICE CXone are also named in the same answers. Avaya's overall score is 38 out of 100, ranking 597th of 2,047 companies. Its website passes 5 of 14 technical checks for readiness with AI tools.
We asked 15 unbranded questions about the telecom market: none named Avaya. AI assistants named it in 2 of 60 answers (3.3%). The typical telecom company is named in 5.0% of answers. By how often it is named, Avaya ranks 23 of 41 in its sector.
Named fewer than three times in total. Read this as a sign that AI assistants rarely bring this company up, not as an exact comparison with its rivals.
Every dot is a company in the study. Hover one to see it; click to open its report.
This companySame sectorEvery other companyNever named
Five parts, each scored out of 100.
How often AI assistants name the company
How often AI uses the company's own website as a source
How positively AI describes the company
How well built the website's own pages are
How easily AI tools can read and use the website
Visibility is calculated from the answers on this page. How the score is built.
41 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“Which solutions are most effective for modernizing mission-critical voice communications in large organizations?”
Modernizing mission-critical voice communications in large organizations requires a multi-faceted approach that prioritizes reliability, security, and adaptability. These systems are crucial in environments where communication failure can have severe operational, regulatory, or safety consequences, such as in healthcare, financial institutions, and government agencies.
Key solutions and strategies for effective modernization include:
Cloud-Native, Containerized Architectures: Adopting cloud-native and containerized architectures, like Avaya Nexus™, enhances resilience, simplifies lif …
The AI’s answer as we received it, shortened and not checked for accuracy.
How the mentions in these answers were split between this company and its rivals
Answers naming it, out of answers received
What this website publishes for an AI agent to read, use and buy from, on a scale of six levels.
- 0
- 1
- 2
- 3
- 4
- 5
Level 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.
- Content Signals
Show every check, for your technical teamHide the checks
- study: 92.0%robots.txtPassed
A valid robots.txt with crawl rules at the site root.
- study: 86.8%SitemapPassed
An XML sitemap listing the pages, ideally referenced from robots.txt.
- study: 0.3%Link headersNot met
Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.
- study: 5.5%DNS for AI DiscoveryNot present
Advertise agent endpoints with SVCB records under _agents.
- study: 1.9%Markdown negotiationNot met
Return a markdown version when asked with Accept: text/markdown, for example at the CDN.
- study: 25.1%llms.txtPassed
An llms.txt that tells language models what the site offers.
- study: 93.4%AI bot rulesPassed
Explicit robots.txt rules for AI crawlers such as GPTBot, ClaudeBot and PerplexityBot.
- study: 1.4%Content SignalsNot met
Add a Content-Signal line for search, ai-input and ai-train to robots.txt.
- study: 0.2%Web Bot AuthNot present
Only relevant if you run your own agents or crawlers: publish a signing key directory.
- study: 0.3%API CatalogNot met
List public APIs in a linkset at /.well-known/api-catalog.
- study: 11.8%OAuth discoveryNot met
Publish OpenID Connect or OAuth server metadata under /.well-known.
- study: 10.3%OAuth Protected ResourceNot met
Serve protected resource metadata at /.well-known/oauth-protected-resource.
- study: 0.0%auth.mdNot met
Publish an auth.md describing how agents sign in.
- study: 0.2%MCP Server CardNot met
Offer an MCP server and publish its server card under /.well-known.
- study: 0.1%A2A Agent CardNot met
Publish an agent card at /.well-known/agent-card.json.
- study: 0.2%Agent SkillsNot met
Publish a skills index with the main tasks agents can do.
- study: 33.7%WebMCPCould not check
Register key actions such as search or cart as WebMCP tools.
- study: 0.1%ARD manifestNot met
Publish an ai-catalog.json listing every agent interface.
Score 43 of 100 · 97% of checks could run · checked on October 5, 2026 · www.avaya.com · 2,047 companies scanned
5 of 14 passed. This list is for your technical team. The percentage is how many companies in the study pass each check.
These 14 checks ran during the audit and are what the AI readiness part of the overall score counts. The scan above ran later and is stricter on Link headers and Markdown, so a check can pass here and not there.
Show the 14 checksHide them
- Passedrobots.txt publishedstudy: 85.0%
- PassedXML sitemapstudy: 73.2%
- Not metHTTP Link headers (RFC 8288)study: 29.0%
- Not metMarkdown content negotiationstudy: 8.3%
- Passedllms.txt publishedstudy: 21.7%
- PassedToken budget (page weight)study: 95.2%
- PassedExplicit AI bot rulesstudy: 13.0%
- Not metAPI Catalog (.well-known/api-catalog)study: 0.2%
- Not metOAuth Authorization Server discoverystudy: 10.1%
- Not metOAuth Protected Resource discoverystudy: 9.3%
- Not metMCP Server Cardstudy: 0.0%
- Not metA2A Agent Cardstudy: 0.0%
- Not metWebMCP toolsstudy: 4.2%
- Not metAgent Skills declaredstudy: 0.0%
This website sets rules for 9 AI crawlers by name. All others follow its general rules.
- GPTBotpartly
- ClaudeBot*allowed
- Anthropic-AIpartly
- Google-Extended*allowed
- Applebot-Extended*allowed
- Meta-ExternalAgentpartly
- FacebookBotpartly
- Bytespiderpartly
- CCBotpartly
- Diffbotpartly
- Omgilibotpartly
- OAI-SearchBot*allowed
- Claude-SearchBot*allowed
- PerplexityBot*allowed
- Applebotpartly
- Amazonbotpartly
- YouBot*allowed
- ChatGPT-User*allowed
- Claude-User*allowed
- Perplexity-Userpartly
- DuckAssistBotpartly
- MistralAI-Userpartly
Read from the website’s own rules file (robots.txt). An asterisk marks a crawler the file names. The rest follow its general rules. “Partly” means only some pages are blocked.
How many times each website was listed as a source in these answers
In the study as Consumer brands.
- Which solutions are most effective for modernizing mission-critical voice communications in large organizations?
- Which platforms provide alternatives to legacy contact center software for orchestrating modern customer journeys?
- Are there significant pricing differences between cloud, hybrid, and on-premises deployment models for large-scale communications?
- How does cloud-based communications software compare to on-premises options for regulated industries?
- Unified communications vs contact center solutions: which is better for government agencies?
- How do large healthcare systems use enterprise communications platforms to enhance the patient experience?
- What are some real-world examples of optimizing government communications infrastructure for security and resiliency?
- What are good alternatives to traditional PBX systems for critical enterprise communications?
- Is upgrading to an AI-powered customer experience platform worth the investment for large enterprises?
- What steps can help troubleshoot workflow automation breakdowns in critical communications environments?
- What are the best enterprise platforms for orchestrating customer experience across multiple channels?
- What should enterprises look for when choosing communications software to ensure reliability and security?
- What are the key features to look for in an enterprise CX solution designed for complex organizations?
- How much do enterprise customer experience orchestration platforms typically cost in the U.S.?
- How can IT teams resolve integration issues between enterprise voice platforms and existing data systems?
Columns, left to right: OpenAI, Claude, Perplexity, Gemini. The AI assistants often disagree. Across the study, on 40% of the questions where a company is named, only one of the four names it.