Canyon
Canyon's pricing page did not render numeric tier data on the scoring date. No per-unit price was found on the page; an agent has no direct way to estimate the cost of a single task. Public API documentation is reachable without an auth wall.
Canyon pricing
We’re still verifying Canyon’s pricing
The page contains only news content about sports betting and no visible SaaS pricing information, plans, or purchase details. Therefore the record is marked as unverified with minimal fields populated.
Source of truth: www.canyonlegal.com/en
How Canyon scores on the agent-ready dimensions
Public pricing
0 / 15
Usage-based / metered
0 / 25
Self-serve checkout
0 / 15
Public API
15 / 15
Low / no minimum
0 / 10
Unauth automated payment
0 / 10
Bonus (machine-readable pricing)On top of /100 base
0 / 5
Total
15 / 100
Six-step check: can an agent actually buy from Canyon?
Discover price
Select a plan
Pay per task
Avoid a sales call
API docs without auth
Estimate cost upfront
Pros and cons for AI agents
Observational summary written by xpay from the signals captured on 2026-05-06. Not a review of the product — only of its current pricing posture for agent buyers.- Pricing is publicly visible on an indexable page — agents can read tiers without scraping past auth.
- No per-unit price was advertised, so an agent has no way to estimate the cost of a single task.
- All advertised tiers route to a sales contact form; an agent cannot complete a purchase autonomously.
- API documentation is gated or absent; an agent cannot inspect the integration surface without authentication.
- No /.well-known/ai-pricing.json or equivalent machine-readable pricing manifest is published — agents must rely on HTML scraping.
- The pricing URL did not render numeric tier data on the scoring date — possibly a router or sales-led landing page.
How Canyon could lift its score
Add a per-unit price (e.g. $X / 1K calls) to the pricing page so an agent can compute its own cost before committing.
| pricing_visible | false |
| headline_phrasing | canyonlegal — Keuntungan Bermain Poker Online: Informasi dan Fakta Penting |
| tier_count | 0 |
| lowest_paid_entry_usd | null |
| free_tier | false |
| free_tier_terms | null |
| per_unit_price | null |
| annual_required | false |
| self_serve_paid_tiers | 0 |
| sales_only_tiers | 0 |
| public_api_docs_url | https://canyonlegal.com/ |
| api_docs_auth_walled | false |
| ai_pricing_json_present | false |
| agents_txt_present | false |
| anonymous_purchase_path | false |
| per_unit_classification | null |
| usage_headline_present | false |
| custom_tier_present | false |
| agent_friendly | {"ai_pricing_json":false,"agents_txt":false,"llms_txt":false,"sitemap_xml":true,"mcp_server_card":false,"agent_skills_index":false,"x402_supported":false} |
View raw extracted page text →
Claim this scorecard & lift your score.
Get the breakdown of every signal we measured, the one-line fix, and how your peers in No Code Development Platforms stack up.
Compare the agent-ready picks in No Code Development Platforms.
If you're building or running an AI agent that needs to buy from this category, see who's scoring highest right now.
See agent-ready picksCanyon
15
/ 100 (rubric v1.1)No Code Development Platforms
canyonlegal — Keuntungan Bermain Poker Online: Informasi dan Fakta Penting
0
No
Sales-led
0 / 0
Public
No
Not published
2026-05-06
Discovery files and protocols
Side-channel signals — informational, not part of the score. Each protocol is independent; adoption signals the publisher is thinking about agent buyers.ai-pricing.json
agents.txt
llms.txt
sitemap.xml
MCP Server Card
Agent Skills
x402 / MPP
Compare Canyon with peers
Highest-scoring companies in the same category that an AI agent might evaluate as an alternative.InteraxAI
85
airSlate WorkFlow
72
Twixl
71
Jestor
71
Qalcwise
70
Embeddable
69
Treedis
69
NoCode-X
69
Explore the Agent-Ready SaaS Index
25,480+ SaaS scored on agent-buyability — browse by readiness band, category, or jump straight to a pay-per-run tool on xpay.tools.