CreditCore
CreditCore scores 4/100 on xpay's Agent-Ready Index v2: partial pricing visibility.
CreditCore pricing
Sales-led pricing
The CreditCore page provides no public pricing information; all CTAs lead to contact sales, indicating a sales‑only model with no disclosed tiers or costs.
How CreditCore 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
2 / 7
Card / wallet / x402 payment
0 / 6
Machine-readable bonus (MCP / OpenAPI)
0 / 10
Total
4 / 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
Unknown
Quote required
Unknown
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
Six-step check: can an agent actually buy from CreditCore?
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 CreditCore 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 | Our Platform Is — Improve your fair lending audit results and free up lenders from time consuming compliance tasks. Gain powerful business insights through dashboards and exportable reports. |
| tier_count | 2 |
| 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 | 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 | false |
| 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 picksCreditCore
4
/ 100 (rubric v2.0)Loan Origination
Not advertised
2
No
Sales-led
0 / 0
Auth-walled
No
Not published
2026-05-09
Sales-led pricing
Contact sales · 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
Compare CreditCore with peers
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70
Roopya
61
Hypercore
59
JMB Lending
49
ATLOS
47
LendingWise
42
LoanSifter
42
MBS Highway
42
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