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Maze

Maze is a new type of security platform - built from scratch to use modern AI to make decisions, instead of pre-defined logic.

Agent scoredown 3.4
84.3/100Good
Rank
Top 9%
#48
Developer tools rank
Sector average 80.4
#5
Benchmark runs
6 providers
1
Where this site sits
Developer tools avg
80.4 (+3.9)
Market avg
76.8 (+7.5)

01

Latest results

Maze ranks #48 of 553 scored sites.

First run. The comparison starts after the next one.

Overall: 84.3 now
Brand awareness: 89.9 now
Discovery: 71.1 now
Information retrieval: 91.2 now
Market ranking: 63.0 now
Accuracy: 96.0 now
Task completion: 85.6 now
Contact & communication: 79.5 now
  • This site
  • Developer tools
  • Market

By category

  • Brand awareness
    90
  • Discovery
    71
  • Information retrieval
    91
  • Market ranking
    63
  • Accuracy
    96
  • Task completion
    86
  • Contact & communication
    80
Table view
RunThis siteDeveloper tools medianMarket median
22 Oct 202684.379.179.9

Monthly medians. Dates in UTC.

02

Performance

Site checks, then AI agents on real tasks.

Methodology

Automated checks probe the site before any agent runs. They count for 40% of each category. Strongest is Accuracy at 100.0, weakest is Market ranking at 36.0.

Site checks by category

Brand awareness
71.0
Discovery
87.0
Information retrieval
86.0
Market ranking
36.0
Accuracy
100.0
Task completion
63.0
Contact & communication
60.0

1 category does not apply to this site and is left out.

Agents

Each agent’s score over 30 days, and how its latest sessions went.

  • Excellent85+
  • Good72-84
  • OK58-71
  • Poor40-57
  • Critical<40

Latest run 22 Oct 2026 (UTC). Sign in to request a re-run from 23 Oct 2026, 21:02 UTC.

03

Potential improvements

Fix where agents got stuck, then lift your biggest categories.

MediumBrand awareness

Agents searching for "Maze" do not find mazehq.com (Exa).

Biggest wins

Projected

Lifting Market ranking to Good adds about +0.8 on its own, taking the overall from 84.3 to 85.1.

  1. Raise Market ranking from 63.0 to 72 (Good) to add about 0.8 to the overall score.

  2. Raise Contact & communication from 79.5 to 85 (Excellent) to add about 0.3 to the overall score.

  3. Raise Discovery from 71.1 to 72 (Good) to add about 0.1 to the overall score.

Each gain assumes only that category improves. Fix several and the total lands a little under their sum.

Where agents get stuck

7 improvements from the latest run.

High
0
Medium
4
Low
3
  1. MediumBrand awareness

    Agents searching for "Maze" do not find mazehq.com (Exa).

  2. MediumMarket ranking

    No Product/Service schema on the homepage. Agents can’t easily compare offerings.

  3. MediumTask completion

    No visible primary call-to-action in the server-rendered HTML. Agents have nothing concrete to click on behalf of a user.

4 more, and the evidence for each

Want to find these in your own flows before an agent does? Read how to test your product for AI agent users.

Technical readiness

2 of 8 essential checks fail. These are the files and signals agents read before they act.

Score

83/ 100

Ready with a few material gaps

Essential
6 of 8 pass
Recommended
12 of 21 pass
Bonus
+3.5 from 16 positive signals
Investigate
Markdown content negotiation (acceptmarkdown.com)essential
Investigate
Brand name discoverabilityrecommended
Investigate
CLI tool availablerecommended
29 checks · scanned 2 Sept 2026
Opportunity cost · developer tools

Maze could see ~$800,700 of new ARR exposed to agent-led journeys each year

Gap to leader
15.7 pts
Above developer tools avg
0.0 pts
Modeled new ARR at risk
$800,700

Badge

Show visitors your Good agent score

Add a live Index badge to your footer, docs or README. The badge updates after every run and links visitors to this scorecard.

mazehq.com Stunt Double Index agent score badge

Ask your agent about mazehq.com

Paste this into Claude, ChatGPT, Cursor or Claude Code. It asks the question and tells your agent how to connect to the Index. No account needed.

Prompt

Look up mazehq.com on the Stunt Double Index. Tell me why it scores the way it does for AI agents, what its biggest frictions are, and what it should fix first. Use the Stunt Double Index MCP server for this: https://app.stuntdouble.io/api/mcp/index (Streamable HTTP, no sign-in). Its tools are get_index_report, list_index_sessions and search_index_domains. If it isn't connected yet: - If you can add MCP servers yourself (Claude Code, Cursor, VS Code), add it as "stunt-double-index", for example: claude mcp add --transport http stunt-double-index https://app.stuntdouble.io/api/mcp/index - Otherwise, tell me how to add it here, then wait. In Claude: Settings, Connectors, Add custom connector, paste the URL and leave the OAuth fields empty. In ChatGPT: turn on developer mode under Settings, Apps & Connectors, Advanced, then create a connector with the URL and No authentication. - If you can't use MCP at all, read https://index.stuntdouble.io/d/mazehq.com instead.

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