sales-i
sales-i scores 2/100 on xpay's Agent-Ready Index v2: partial pricing visibility.
sales-i pricing
Sales-led pricing
Pricing is not publicly disclosed; page only offers demo request and sales contact, so model_type set to sales_only.
How sales-i scores on the agent-ready dimensions
Public pricing visibility
2 / 15
Self-serve checkout
0 / 15
Public API + docs
0 / 20
Usage-based / metered pricing
0 / 20
Free entry path
0 / 7
No sales call required
0 / 7
Card / wallet / x402 payment
0 / 6
Machine-readable bonus (MCP / OpenAPI)
0 / 10
Total
2 / 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
Unknown
Human approval recommended
Pricing transparency
contact_only
Purchase motion
sales_led
Demo required
Quote required
Annual commit required
Unknown
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
Positioning & ecosystem
“Sell smarter with instant customer insights”
Buyer persona
Six-step check: can an agent actually buy from sales-i?
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.
How sales-i 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 | Sell smarter with instant customer insights — Our sales tool analyzes hard-to-reach data and turns it into opportunities to upsell, cross-sell and reduce churn. |
| tier_count | 1 |
| 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 | 1 |
| 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":false,"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 pickssales-i
2
/ 100 (rubric v2.0)Sales Enablement
Not advertised
1
No
Sales-led
0 / 1
Auth-walled
No
Not published
2026-05-09
Sales-led pricing
Request a demo · sales-led
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
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Explore the Agent-Ready SaaS Index
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