State and tone engine
Tracks relationship phase, engagement, tension, spend intent, buyer style, consent, and the next commercial objective.
The operating layer
The conversation, content, and control systems share one context.
FanLTV connects provider events, relationship state, memory, media, pricing, safety, delivery, and operator actions around each model and fan.
The decision path
Signals are interpreted before text is generated.
The system can wait, flirt, recall, sell, negotiate, recover, or hand the conversation to a person.
- 01Ingest
Webhooks, listeners, catch-up sync, message bursts, media, tips, subscriptions, and unlocks.
- 02Understand
History, language, sentiment, buyer style, safety, facts, media intent, and spend signals.
- 03Choose state
Rapport, flirt, presell, offer, negotiation, post-purchase, reactivation, or manual review.
- 04Act
Generate the reply, select contextual content, set price, preserve timing, or pause safely.
- 05Learn
Store outcomes, purchases, memories, blockers, and the next best action for the relationship.
Product workspace
See the operational context instead of switching between tools.
The same system supports the inbox, content commerce, runtime automation, and multi-model command center.
Conversation operations
See the whole relationship before you reply.
Filter by model, provider, live state, and safety status. Review message history, current mode, media, purchases, and operator actions without switching tools.
- Multi-provider conversation history
- Manual, handoff, and full-auto modes
- Conversation state, logs, and funnel context
Platform capabilities
The supporting systems that make the conversation believable.
Model bible and fan memory
Uses the facts needed for the current reply without flooding every prompt or inventing personal details.
Scripts, PPV, customs, and tips
Chooses a relevant script, respects step and media pricing, handles objections, deposits, and post-purchase care.
Proactive and reactivation
Reopens quiet conversations from history, reacts to platform events, and applies per-model limits and eligibility.
Media intelligence and FYP
Syncs or uploads media, describes it, organizes photosets, schedules posts, and preserves lock and preview state.
Multi-model operations
Role access, balances, plans, cloned configs, prompt permissions, model assignments, and agency-level visibility.
Layered review and handoff
Input and output checks, contextual second review, private-topic recovery, and explicit manual locks that automation cannot bypass.
Webhooks, listeners, and recovery
Idempotent processing, retry queues, catch-up sync, duplicate prevention, health checks, and traceable delivery failures.
Multi-channel by design
One fan relationship can continue across different surfaces.
FanLTV normalizes messages, media, purchases, events, and delivery status while keeping provider-specific rules where they belong.
FanvueOAuth, chats, media, webhooks
FanslyChats, media, PPV, FYP, events
OnlyFansProvider API integration
TelegramAccount listener, bot payments, Stars
InstagramDM webhooks and response routing
Web and APIAIGirlFactory and custom channels
Control remains visible
Automation should be reversible, explainable, and scoped.
Every model can run in manual, handoff, or full-auto mode. Safety locks remain explicit. Agencies decide who can edit prompts, manage configs, see logs, or change commercial settings.
- Pause immediatelyStop outbound automation per model without losing conversation state.
- Inspect the decisionSee state, effective mode, graph events, delivery attempts, and blockers.
- Protect high-risk momentsRoute safety, payment, custom, or uncertain cases to review.
- Separate each brandIndependent model bibles, style rules, sales logic, prices, and channel policies.
Practical questions
Start controlled. Expand after the behavior is visible.
FanLTV can begin as an assistant and take on more work only after voice, content, pricing, and safety are validated in real conversations.
Does FanLTV replace human chatters?
It can automate routine conversations, timing, memory, content selection, and recovery. High-value, sensitive, uncertain, or unusual cases can remain in handoff or manual mode.
Why not make an offer in every conversation?
Because readiness varies. A premature offer can reduce trust and price perception; waiting forever loses intent. FanLTV tracks the state and next commercial objective so the decision is contextual.
Can each creator keep a different voice and strategy?
Yes. Model bibles, facts, style rules, conditional prompts, prices, custom policies, media scripts, and channel rules are isolated per profile.
What happens when a webhook or provider fails?
Listeners, retries, idempotent processing, catch-up synchronization, and delivery traces are designed to recover missed work without sending the same reply twice.
Can operators see why the system did not reply?
Logs expose conversation state, effective mode, graph events, safety or manual locks, provider attempts, and blockers instead of leaving silence unexplained.
How does rollout begin?
Start with one model and one channel in manual or handoff mode. Validate voice, memory, content, pricing, and safety before enabling broader automation.
See the complete workflow