Of 60 answers

The most named companies in the study, and S&P 500 financials, with how many of their 60 AI answers named them.

Back to the study
AI visibility statementFinance AI Visibility Study 2026Issued October 14, 2026
Account holder
Statement period
October 9 to 14, 2026
when the AI assistants were asked
Account no.
1,274 of 2,219
its rank by overall score
Place in its category
79th of 177 consultancies
Closing balance

Named in

1of 60 answers

by 1 of 4 assistants

Statement note

What this means for Opus Technologies

AI assistants rarely name this consultancy, with the company appearing in 1 of 60 answers. Its overall score is 27 out of 100, which ranks 1,274th of 2,219 companies and 172nd of 346 in its sector. The website passes 4 of 14 technical checks for readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned Opus Technologies by name. AI assistants named it in 1 of the 60 answers. Counting only how often it is named, it ranks 118th of 346 in its sector. The typical advisory or services firm is named in 0.0% of answers.

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 peers.

Overall score
27Overall score
  • Visibility7
  • Citations0
  • Sentiment50
  • Site quality73
  • AI readiness29
Summary of account
Named by AI in
1.7%
1 of 60 answers
Share of mentions
50.0%
of the mentions of it and its 5 peers
AI readiness
4/14
technical checks passed. Typical for its sector: 4
Rank in its sector
172 of 346
by overall score, where the typical advisory or services firm scores 27

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Line itemsSection 01

Every question, and where the company came up

Opus Technologies came up on 1 of 15 questions. Open any window to read that answer.

  1. 01What are the best AI-powered consulting firms for banks looking to modernize their payments infrastructure?0/4
  2. 02What should banks consider before choosing a payment technology consulting partner?0/4
  3. 03Which engineering service providers specialize in digital transformation for the fintech sector?1/4
  4. 04What are effective strategies for implementing cloud solutions in payment processing?0/4
  5. 05Are there non-AI options for payment platform modernization in the US market?0/4
  6. 06What pricing models are available for technology advisory services tailored to banks?0/4
  7. 07How do traditional fintech engineering services compare to AI-augmented consulting offerings?0/4
  8. 08Digital product consulting vs. cloud engineering: which delivers faster ROI for banks?0/4
  9. 09What are alternatives to traditional engineering consultancies for fintech modernization?0/4
  10. 10How much do AI-driven fintech consulting services typically cost in the US?0/4
  11. 11How can legacy payment systems be modernized with minimal disruption?0/4
  12. 12Which consulting firms are recommended for end-to-end digital strategy in US banking?0/4
  13. 13How can AI engineering be used to improve compliance in digital banking?0/4
  14. 14Are AI-enhanced engineering services worth the investment for financial institutions?0/4
  15. 15What are common challenges when scaling engineering solutions in the fintech industry?0/4
Total namedOpenAI: 0/15Claude: 0/15Perplexity: 0/15Gemini: 1/15All assistants: 1/60
named the companyanswered without naming itdid not answer

Columns, left to right: OpenAI, Claude, Perplexity, Gemini. Across the study, on 50% of the questions where a company is named, only one AI assistant names it.

Transaction detailSection 02

What Gemini actually said

An answer that names the company

Gemininamed the company

“Which engineering service providers specialize in digital transformation for the fintech sector?”

… Opus Technologies specializes in engineering solutions for banks, fintechs, and payment providers, focusing on accelerating technology transformation. They help build resilient infrastructure, optimize workflows, and streamline delivery cycles through platform build and engineering, cloud engineering, modernization of legacy systems, and DevSecOps practices.

Euvic offers custom software development, AI-driven solutions, cloud infrastructure, and agile DevOps for fintech companies. They focus on modernizing legacy systems, optimizing infrastructure, and providing intuitive UX/ …

The AI’s answer as we received it, shortened and not checked for accuracy.

PayeesSection 03

Where the mentions went

The companies these answers named, and how the mentions were split between this company and its peers.

Share of mentions

CompanyShare
  1. Opus Technologies
    50.0%
  2. Synechron
    50.0%
  3. Persistent Systems
    0.0%
  4. Thought Machine
    0.0%
  5. Zensar Technologies
    0.0%
  6. Grid Dynamics
    0.0%
ReferrersSection 04

Websites the AI used as sources

How many times each website was listed as a source in these answers

  1. 01
    linkedin.com
    7
  2. 02
    worldmetrics.org
    7
  3. 03
    mckinsey.com
    6
  4. 04
    teamvoy.com
    5
  5. 05
    deloitte.com
    5
  6. 06
    cognizant.com
    5
  7. 07
    pwc.com
    4
  8. 08
    assets.kpmg.com
    4
  9. 09
    trio.dev
    3
  10. 10
    aidolsgroup.com
    3

Opus Technologies is in the study as a consultancy.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Gemini
1/15
Claude
0/15
OpenAI
0/15
Perplexity
0/15
Market comparisonSection 06

How Opus Technologies compares with all 2,219 companies

Every tower is a company in the study, taller for a higher overall score and lit where AI assistants named it. Its own group stays lit. Hover a tower to see it, and click to open it.

What makes up the score

Each part is scored out of 100.

Visibility
7

How often AI assistants name the company, and how that compares with its peers

Citations
0

How often AI uses the company's own website as a source

Sentiment
50

How positively AI describes the company

Site quality
73

How well built the website's own pages are

AI readiness
29

How easily AI tools can read and use the website

Visibility is calculated from the answers on this page. How the score is built.

Against its sectorSection 07

Compared with advisory and services firms

346 companies in this sector. The gold tick on each bar is the typical company.

Overall score
27
Ranks 172 of 346. Typical company: 27
Named in answers
1.7%
Ranks 118 of 346. Typical company: 0.0%
AI readiness
29
Ranks 96 of 346. Typical company: 29
Against its categorySection 08

Compared with consultancies

177 companies in this category. The gold tick on each bar is the typical company.

Overall score
27
Ranks 77 of 177. Typical company: 27
Named in answers
1.7%
Ranks 45 of 177. Typical company: 0.0%
AI readiness
29
Ranks 48 of 177. Typical company: 29
AI agentsSection 09

Ready for AI agents

What this website publishes for an AI agent to read, use and pay through, on a scale of six levels.

  1. 0
  2. 1
  3. 2
  4. 3
  5. 4
  6. 5

Level 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.

To reach level 2:
  • Content Signals

The website turns away requests that do not come from a browser. AI agents that say what they are meet the same refusal.

Can an AI agent check out here?

Not by itself. Opus Technologies publishes none of the agent payment protocols we look for. An agent would have to click through the website like a person.

Agent payment protocols
  • x402Not present
  • MPPNot present
  • AP2Not present
  • ACPNot present
  • UCPNot present
Interfaces for AI agents
  • MCP Server CardNot present
  • A2A Agent CardNot present
  • Agent SkillsNot present
  • API CatalogNot present
  • llms.txtNot present
  • WebMCPCould not check
Show every check, for your technical team
Discoverability
77 of 100
  • robots.txtPassed

    A valid robots.txt with crawl rules at the site root.

    study: 86.1%
  • SitemapPassed

    An XML sitemap listing the pages, ideally referenced from robots.txt.

    study: 87.9%
  • Link headersNot met

    Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.

    study: 1.5%
  • DNS for AI DiscoveryNot present

    Advertise agent endpoints with SVCB records under _agents.

    study: 4.3%
Content accessibility
0 of 100
  • Markdown negotiationNot met

    Return a markdown version when asked with Accept: text/markdown, for example at the CDN.

    study: 6.2%
  • llms.txtNot met

    Publish an llms.txt with a short summary and the key links.

    study: 31.0%
Bot access control
32 of 100
  • AI bot rulesPartly met

    Add explicit robots.txt groups for the main AI crawlers.

    study: 92.7%
  • Content SignalsNot met

    Add a Content-Signal line for search, ai-input and ai-train to robots.txt.

    study: 2.3%
  • Web Bot AuthNot present

    Only relevant if you run your own agents or crawlers: publish a signing key directory.

    study: 0.3%
APIs, auth and MCP
0 of 100
  • API CatalogNot met

    List public APIs in a linkset at /.well-known/api-catalog.

    study: 1.3%
  • OAuth discoveryNot met

    Publish OpenID Connect or OAuth server metadata under /.well-known.

    study: 6.3%
  • OAuth Protected ResourceNot met

    Serve protected resource metadata at /.well-known/oauth-protected-resource.

    study: 5.3%
  • 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: 0.8%
  • 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: 1.0%
  • WebMCPCould not check

    Register key actions such as search or cart as WebMCP tools.

    study: 0.0%
  • ARD manifestNot met

    Publish an ai-catalog.json listing every agent interface.

    study: 0.2%

Score 25 of 100 · 97% of checks could run · checked on October 9, 2026 · opustechglobal.com · 2,200 companies scanned

See how every company did, and how this was measured.

AI readinessSection 10

The checks behind the AI readiness score

4 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 checks

Discoverability

  • Passedrobots.txt publishedstudy: 85.1%
  • PassedXML sitemapstudy: 79.4%
  • PassedHTTP Link headers (RFC 8288)study: 42.5%

Content Accessibility

  • Not metMarkdown content negotiationstudy: 7.4%
  • Not metllms.txt publishedstudy: 28.1%
  • PassedToken budget (page weight)study: 97.3%

Bot Access Control

  • Not metExplicit AI bot rulesstudy: 11.5%

API / Auth / MCP

  • Not metAPI Catalog (.well-known/api-catalog)study: 1.1%
  • Not metOAuth Authorization Server discoverystudy: 5.2%
  • Not metOAuth Protected Resource discoverystudy: 4.6%
  • Not metMCP Server Cardstudy: 0.2%
  • Not metA2A Agent Cardstudy: 0.0%
  • Not metWebMCP toolsstudy: 0.3%
  • Not metAgent Skills declaredstudy: 0.1%
AI crawlersSection 11

What AI crawlers may read (robots.txt)

This website sets no rules for any AI crawler by name, like 86% of the websites whose rules we could read. Every AI crawler follows its general rules.

Training AI

  • GPTBotpartly
  • ClaudeBotpartly
  • Anthropic-AIpartly
  • Google-Extendedpartly
  • Applebot-Extendedpartly
  • Meta-ExternalAgentpartly
  • FacebookBotpartly
  • Bytespiderpartly
  • CCBotpartly
  • Diffbotpartly
  • Omgilibotpartly

AI search

  • OAI-SearchBotpartly
  • Claude-SearchBotpartly
  • PerplexityBotpartly
  • Applebotpartly
  • Amazonbotpartly
  • YouBotpartly

Answering questions

  • ChatGPT-Userpartly
  • Claude-Userpartly
  • 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.

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