LLM
Writes the conversation- Understands the latest message
- Matches creator voice and fan tone
- Writes natural responses
- Handles language and phrasing
AI revenue operations for creator agencies
Turn every fan conversation into a relationship that remembers, adapts, and sells.
FanLTV combines AI chatting, persistent fan memory, content selection, PPV sales, reactivation, and human handoff in one operating system across your creator channels.
Most AI chatters know how to chat. They do not know how to sell.
The LLM writes the conversation. FanLTV decides what should happen next.
Start with one model and one channel. No password handoff required.
Works across your existing creator stack
- Fanvue
- Fansly
- OnlyFans via provider API
- Telegram
- Web / API
Why most AI chatters fail
Sexting is easy. Selling is hard.
AI is good at conversation.
AI is unreliable at sales decisions.
So we separated them.
Most AI chatters can flirt, sext, and answer messages. That is not the hard part. The hard part is deciding when to sell, what to sell, how hard to push, and when to stop. FanLTV does not leave those decisions to the LLM.
FanLTV Sales Engine
Decides the strategy- Relationship state and buying intent
- Resistance, purchase history, and previous offers
- Content, pricing, cooldowns, and next objective
- Human handoff conditions
Possible next movesRapport · Flirt · Presell · Offer · Wait · Back off · Handoff
The LLM writes the message.The sales engine decides the strategy.
We do not trust the LLM with the money.
See the decision systemProduction evidence, not a demo claimRecorded through 20 August 2026. Payment counts define the audited data set; they are not presented as revenue caused by FanLTV.
524recorded payment events
400with usable conversation context
8revenue and retention workflows
Where agencies leak revenue
Most chatter operations harvest existing intent. They do not create future buyers.
A strong shift can still damage the account's long-term economics when every conversation is judged only by what it sold today.
Chatters focus on fans who already want to buy.
Warm fans receive less attention even when trust, engagement, and future purchase potential are rising.
FanLTV tracks immediate readiness and nurture potential separately.The shift optimizes its own revenue, not average fan LTV.
An aggressive offer may improve today's number while lowering attachment, future conversion, and retention.
FanLTV chooses the next action for the relationship horizon.“I cannot buy tonight” is treated as “this fan has no value.”
Conversation warmth disappears, rapport stops developing, and a high-potential future buyer is quietly lost.
FanLTV can return to nurture and re-enter sales when the state changes.Memory resets between shifts, tools, and channels.
Fans repeat themselves, promises are missed, purchased content is offered again, and the creator's voice becomes inconsistent.
FanLTV keeps memory, purchases, content, and operating state together.Recorded production outcomes
See the commercial decisions, not just the dashboard.
Anonymized conversation evidence shows how FanLTV recovers trust, protects price, and turns stated intent into the right next action.
Case-linkedEach published result is tied to its recorded conversation and payment outcome. Aggregate database volume is never presented as bot-attributed revenue.
Recorded production casePPV price negotiation
- 01 / SignalFan asks to reduce $20 content to $15This is buying intent with price resistance, not a reason to restart rapport.
- 02 / ContextKnown buyer with earlier subscription and unlocksThe relationship and purchase history support a bounded counteroffer.
- 03 / DecisionHold the offer at $20A short, persona-native counter keeps the negotiation moving without accepting the floor.
- 04 / OutcomeUnlocked in 1 minute 53 secondsThe fan's recorded purchase history reached $44.99 after this unlock.
- 05 / RelationshipThe buyer kept buyingThe point was not the extra $5. It was protecting the price without losing the buyer. He remains subscribed, continues to spend, and his LTV is still accumulating.
The fan returned ten days later to plan the next chapter. The relationship and its value are still developing.
A budget-matched $29.95 offer became part of a four-purchase relationship rather than a one-off sale.
The $8 to $18 sequence sits inside $74.49 in recorded spend, with the fan still subscribed and buying.
Commercial workflows
One system for the ways creator relationships actually make money.
FanLTV does more than generate replies. It recognizes the commercial situation, applies model-specific rules, uses the right content, and records the outcome.
Match content to intent
Select the relevant script or content set, protect the price, use previews correctly, and avoid sending a paid step for free.
Explore PPV workflowsScope before promising
Qualify the request, calculate a bounded price, secure a configurable deposit through an in-platform tip, and hand exceptions to a person.
Explore custom salesRecognize the payment signal
Understand why a tip arrived, acknowledge it naturally, update the relationship, and choose whether the moment needs gratitude or a next step.
Explore tip handlingKeep the ask contextual
Use model-approved wishlist facts only where channel policy permits, without turning every warm exchange into another request.
Explore gift workflowsReturn with memory
Reach eligible followers from prior context, platform events, or inactivity rules with per-model limits and duplicate protection.
Explore retention workflowsRun publishing as an operation
Prepare media archives, hooks, captions, schedules, private-wall routing, lifetime rules, and performance review as one campaign.
Explore FYP automationChange the path after payment
Followers, subscribers, first-time buyers, and repeat buyers receive different pacing, recognition, and next-step logic.
Explore relationship tiersKeep uncertainty visible
Pause, review, approve, or take over when safety, payment state, negotiation, or provider delivery is ambiguous.
Explore operating controlHow it works
Configure the creator. Test privately. Then earn the right to automate.
FanLTV takes setup because every creator, catalog, sales style, and team is different. Your operators test the result before real fans see it.
- 01
Connect one model
Bring conversations, media, prices, and purchase context from one channel.
- 02
Configure the individual creator
Map her story, voice, boundaries, content, pricing, sales logic, and handoff conditions.
- 03
Test her privately
Your team challenges memory, tone, refusals, negotiation, content selection, and recovery before launch.
- 04
Launch under human control
Start assisted, automate proven routines, and keep unusual or high-value decisions with experienced chatters.
Agency capacity
Scale models, not chatter headcount.
Your best chatters may already sell well. The bottleneck appears when five models become ten, twenty, or fifty: every new group normally adds hiring, training, supervision, and shift coverage. FanLTV handles repeatable conversation volume while people stay available for VIPs, unusual situations, customs, and high-value conversations.
- ManualFanLTV stores context; the operator writes and sends.
- AssistedFanLTV proposes; the operator approves or edits before sending.
- HandoffAutomation pauses on a configured exception for human ownership.
- Full autoValidated, eligible routines send with safety and delivery checks.
The goal is not fewer good chatters. It is more models per operating team.
Explore the agency platformMessage bursts, memory retrieval, pacing, established sales paths, and eligible reactivation do not need to restart with every shift.
VIPs, unusual situations, complex customs, and sensitive or high-value conversations remain visible and available for human ownership.
More models can share the same monitoring, handoff, delivery, and quality-control infrastructure while keeping creator-specific configuration.
Repository inventory · 6 September 2026
Engineering depth behind reliable operations.
Conversation, commerce, integrations, safety, and agency control require more than a prompt wrapped in a chat window. These figures describe the maintained product surface.
One operating product across inbox, memory, state, content, pricing, safety, analytics, permissions, and provider integrations.
Benefit: fewer disconnected tools and fewer manual handoffs.Operational actions and data are exposed through structured interfaces instead of being trapped inside a reply generator.
Benefit: agency workflows can be connected, controlled, and audited.Synchronization, delivery, catch-up, proactive messaging, reactivation, and recovery continue beyond the open inbox.
Benefit: less missed work when operators are offline or providers are delayed.Conversation logic, providers, sales paths, safety controls, and admin behavior are checked as the system changes.
Benefit: safer releases with lower regression risk in live operations.Free tools
See the revenue leaks hiding in your conversations.
Audit conversation quality or model how stronger fan LTV changes your unit economics. No integration or registration required.
Live
ChatterScore / Revenue Leak Scanner
How good is your chatter, really?
Paste a Fan ↔ Chatter conversation and get a score, missed buying signals, offer-timing issues, pressure risks, and future-LTV leaks.
- No integration required
- Raw transcript is not retained by default
- Immediate revenue and future LTV scored separately
Live
LTV Profit Calculator
What is better retention actually worth?
Combine acquisition cost, paying-fan conversion, revenue, fees, lifetime, and fixed costs to see the profit impact of higher LTV.
- Current versus target unit economics
- Profit, ROI, and break-even CAC
- Calculations stay in your browser
Why relationship-first
Revenue follows trust. Trust depends on continuity.
Most chat automation optimizes the next reply. FanLTV manages the relationship: what was promised, what was purchased, how the tone changed, and whether now is the right moment to sell.
One-model benchmark
Do not trust the pitch. Measure it against your current operation.
Start with one average model. Keep your current workflow. Compare FanLTV with the same chatting baseline before expanding.
- Revenue per active fan
- PPV conversion
- Offer-to-purchase conversion
- Revenue per conversation
- Ghost-after-offer rate
- Human intervention rate
- Reactivation performance