Teach n Go
Teach n Go scores 46/100 on xpay's Agent-Ready Index v2: partial pricing visibility; self-serve checkout is available.
Teach n Go pricing
Up to 2,000 live students
Contact sales
How Teach n Go scores on the agent-ready dimensions
Public pricing visibility
15 / 15
Self-serve checkout
15 / 15
Public API + docs
0 / 20
Usage-based / metered pricing
0 / 20
Free entry path
4 / 7
No sales call required
7 / 7
Card / wallet / x402 payment
5 / 6
Machine-readable bonus (MCP / OpenAPI)
0 / 10
Total
46 / 100
Can an autonomous agent transact here?
Can create account
Can enter payment method
Can upgrade plan
Can buy more usage
Can cancel online
Payment methods
Human approval recommended
Pricing transparency
full
Purchase motion
self_serve
Demo required
Quote required
Annual commit required
Auto-renewal mentioned
Cancellation policy visible
Refund policy visible
Invoice payment available
Unknown
Purchase orders supported
Unknown
MSA required
Unknown
DPA available
Unknown
Security review required
Unknown
Trial
14 days (no card)
Positioning & ecosystem
“Simple pricing that scales with your school”
Buyer persona
Six-step check: can an agent actually buy from Teach n Go?
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.
- Every advertised tier is self-serve; no tier requires scheduling a call.
- A free tier exists, lowering the bar for an agent builder to prototype before committing budget.
- No per-unit price was advertised, so an agent has no way to estimate the cost of a single task.
- API documentation is gated or absent; an agent cannot inspect the integration surface without authentication.
- PPU requires account creation and an issued API key; a fully unauthenticated agent purchase is not yet supported.
- No /.well-known/ai-pricing.json or equivalent machine-readable pricing manifest is published — agents must rely on HTML scraping.
How Teach n Go 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 | true |
| headline_phrasing | Simple pricing that scales with your school — Real feedback from schools using Teach ’n Go day to day. |
| tier_count | 2 |
| lowest_paid_entry_usd | null |
| free_tier | true |
| free_tier_terms | null |
| per_unit_price | null |
| annual_required | true |
| self_serve_paid_tiers | 1 |
| sales_only_tiers | 0 |
| public_api_docs_url | null |
| api_docs_auth_walled | null |
| ai_pricing_json_present | false |
| agents_txt_present | false |
| anonymous_purchase_path | false |
| per_unit_classification | null |
| usage_headline_present | false |
| custom_tier_present | true |
| agent_friendly | {"ai_pricing_json":false,"agents_txt":false,"llms_txt":true,"sitemap_xml":true,"mcp_server_card":false,"agent_skills_index":false,"x402_supported":false} |
View raw extracted page text →
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See agent-ready picksTeach n Go
46
/ 100 (rubric v2.0)Training Management Systems
Simple pricing that scales with your school — Real feedback from schools using Teach ’n Go day to day.
2
Yes
Sales-led
1 / 0
Auth-walled
No
Not published
2026-05-09
Tier-based subscription
Start free trial
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 Teach n Go with peers
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62
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62
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55
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49
ProProfs Training Maker
49
Hickory
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Unified Training Tracking
49
Explore the Agent-Ready SaaS Index
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