18+ · EVIDENCE BEFORE THE CLICK
Evidence-first discovery and routing.
LarkMetric is a discovery and routing platform for the lawful adult and adult-AI economy. We help adults compare products, help businesses prepare for specialist payment review, and route qualified, consented cases to providers - while keeping evidence, eligibility and commercial incentives separate.
- No account required
- No behavioral retargeting
- Affiliate relationships disclosed
Core principles
- Evidence
Document what is known
Primary sources and account evidence outrank marketing.
- Unknown
Do not invent certainty
Missing or conflicting evidence remains explicit.
- Privacy
Collect less
No permanent intimate-interest profile is required.
- Commercial
Disclose the relationship
Affiliate payout never changes user-fit conclusions.
A working evidence and routing layer - not a placeholder landing page.
Partners can inspect the public comparison surfaces, privacy evidence, payment-readiness tools, operating boundaries and direct business contact before starting a relationship.
Live AI discovery
Current adult AI comparison surfaces with dated evidence and explicit unknowns.
Payment readiness
Browser-local preflight for lawful adult and adult-AI businesses before specialist review.
Privacy-first attribution
Opaque click attribution and source markers without raw intimate intent in partner fields.
Direct partner contact
partners@larkmetric.com and a structured partner enquiry form.
Compare the capabilities that actually change the experience.
Memory, voice, privacy, pricing and documented adult/romantic scope are easy to oversimplify. LarkMetric breaks them into specific questions and keeps evidence dates visible.
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Best AI Companion Apps for Adults
A current evidence-led comparison across product fit, documented features, privacy and pricing.
Open the comparison -
Memory that Persists
Separate current-context memory, cross-session continuity and user-editable memory controls.
Compare memory evidence -
Voice: Playback or Real Conversation?
Distinguish voice messages and TTS from genuine live voice interaction.
Compare voice capabilities -
Voice + Memory Together
See how two high-impact capabilities interact without turning missing evidence into a score.
Review the evidence -
Privacy, Deletion & Retention
Compare current policy evidence instead of trusting generic "private" marketing.
Compare privacy evidence
Find the readiness gap before the processor decides it for you.
Adult and adult-AI merchants can face provider-specific underwriting, billing-model, website-policy and operating-history questions. LarkMetric is an upstream readiness layer - not a processor and not an approval promise.
Payment-Processing Readiness
Identify objective gaps before specialist provider review. The browser-local checker uses FIX FIRST and UNKNOWN instead of predicting approval.
Start the readiness path →Adult AI Payment Processing
Understand why AI companion and generative-adult models can require a more explicit product, billing and controls story.
Read the adult-AI guide →Rejected or Terminated?
Separate fixable readiness gaps from provider-owned underwriting before applying again.
Diagnose the decline →Subscription + Token Billing
Make recurring, credit and token billing flows explicit before specialist review.
Review billing readiness →
Three labels are better than one opaque score.
- Documented
Current official product, provider, account, terms, pricing or policy evidence supports the claim.
- Observed
LarkMetric has reproduced the behavior under a defined test protocol. We use this label only when that test actually exists.
- Unknown
Evidence is missing, stale, contradictory or controlled by downstream underwriting. We say so instead of guessing.
Useful decisions without building an intimate profile.
- No consumer account required for the current public tools
- No behavioral retargeting based on adult interests
- No raw intimate search text in affiliate tracking fields
- No KYC/KYB upload channel in the readiness checker
Affiliate, payment and editorial partners can work with the same evidence layer.
We are interested in clean attribution, current eligibility, product-policy updates, co-marketing and outcome feedback - without turning payout into editorial ranking.