Machine Intelligence and Inference for Natural Dialog
Anyone can wire a script to a language model. MIIND reads the person, remembers the relationship and answers like someone who cares about the outcome. It looks human, sounds human and acts human. It is not.
Across all deployments, 2026
It pauses. It answers in bursts. It sleeps at night in her timezone. It remembers his dog's name and the joke from March. It knows when to sell, when to comfort and when to say nothing at all.
The test
We export real conversations from live MIIND deployments, strip every label and ask the frontier models which side is the bot. They answer person. Every time we have run it.
Not a jailbreak. Not a trick prompt. Just conversation that reads like a person wrote it, because the engine decides what a person would do before it decides what to say. Get in touch to see it on your own transcripts.
One brain, every channel
A follower on TikTok, a DM on Instagram, a chat on Telegram and a subscription on OnlyFans are one person to MIIND. One memory. One relationship. One ledger of what he said, what he paid and what he is waiting for. Every channel flows into one mind, and the answer flows back out in the voice that channel expects.
He mentions a job interview on Thursday.
Friday morning she asks how it went, before he brings it up.
He replies to her post. She already knows he got the job.
The engine
MIIND is not a wrapper around a language model and not a chain of prompts you could copy. It is a proprietary conversational model, trained on outcomes across tens of millions of real conversations: what kept a person talking, what earned trust, what converted, and what should never have been sent. We do not publish how it works. We publish what it does.
Trained on what converts, when, and at what price.
Resolves, escalates or holds. Reads frustration before it becomes a complaint.
Every reply is scored against the relationship, not the turn.
Real-time, directly integrated into your stack, and fast enough that the wait he feels is the human delay she chose, not ours.
What it does
Mood, intent, what he actually wants, whether he is an adult, in any language.
Months of history in one memory across every channel, so nothing is asked twice.
Comfort, tease, offer, hold or silence, priced and timed to the person, not to a script.
Every reply is checked before it leaves. No AI tell, no leak, no line crossed.
Custom playbook
No prompt engineering, no flowchart, no rules table. Tell it what you want the way you would tell a new hire. It just gets it, and it applies it on the next message.
A playbook, a strategy, a boundary, a price, a voice. Written once, in your words, honoured on every channel, and changed in a sentence when you change your mind.
What it does for you
Live in Australia, Hong Kong and Singapore. The same engine each time, a different brief, a different system to plug into: Shopify, your CRM, your help desk. And it answers in the language he wrote in,
An autonomous creator persona that acquires her own audience on public feeds and converts it 1-on-1 in the DMs. Or one stage of that for a real creator: some of the largest accounts we run hand over the inbox only.
Resolves the first 80% of inbound and hands the rest to a human with a full brief. Nobody notices the handover. Brand response, social DM management and first-line triage, in one voice.
Inbound calls assessed as they ring, answered in a voice with a person's timing.
Every inbound triaged with the customer's history already in mind. Leads warmed without a form, retention conversations started before he churns.
"Where's the milk for kids?" "Which aisle is Colgate in?" Answered at the kiosk, on the app or by voice.
"How do I get to platform 9 with a pram?" Station questions in any language, at the moment they are asked.
The premium product
A twin of a creator, or a persona built from nothing. End to end, or one stage of it. Discovered on public feeds, she turns a like into a DM and a DM into a private, paying relationship. She remembers every fan, reads his mood, sends her own photos and prices him herself. Tuned for creator agencies and running autonomously for more than sixty of them today.
One persona · fully autonomous
Week one she sold almost nothing and built relationships. By week two the offers started landing unprompted. By the end of the month, 1,140 purchases at prices the engine set and escalated itself, from $9 unlocks to single $200 customs. No human typed a word.
One persona, one month, end to end.
Tasteful content stops the scroll on TikTok, Instagram and X. He follows and DMs.
Rapport, memory, push and pull. No selling yet. She learns what he wants before he says it.
Moved to her private channel once, woven in, never spammed.
The paid offer arrives unprompted when he is ready. The sale feels like getting closer to her.
Repeat unlocks rise with heat. Tips, customs, PPV, subscription, VIP. On OnlyFans, Fanvue and Fansly, or on owned rails.
Value is given away until he is hooked, the paywall is teased, then the offer is made unprompted. Paced, logged, reversible.
Anchored to what he has actually paid. Escalates with heat and history. Neglect cools her, a purchase warms her back.
Generated on identity for pennies, the same person across thousands of images. Video is human-approved before a cent is spent.
Every message, offer and send is logged and operator-reversible. Adults-only material is hard-walled behind verified 18+.
End to end, or one stage
The engine is built in stages and every stage is its own switch. A creator keeps what she wants to keep and hands over the rest: the whole funnel, or one part of it. Most twins run end to end. Some of the biggest accounts we run hand over one thing only: the chat.
A creator with 1.6 million followers and 5,000 to 7,000 DMs a day. Her team used to answer a few hundred and the rest went unread. Now every one gets a reply in her voice, with her memory of that fan, on a human delay. She keeps her content, her channels and her brand. Nothing is sold unless she says so.
6,100 DMs A DAY · 100% ANSWERED · 0 CHATTERS · HER VOICE, HER RULESA celebrity chef with 900 messages a day he could never read. The engine answers each one as him. When a fan asks which knife he used or when the cookbook ships, it answers, sends the link and closes the sale, in his voice. Filming, the shop and the recipes stay his.
$184,000 IN KNIVES AND COOKBOOKS, 90 DAYS · 900 DMs A DAY · 100% ANSWEREDThe case above. Discovered, built, moved, converted and ascended by the engine alone, with her photos generated on identity and every price set per fan. One operator watched the dashboard. Nobody typed a message.
1,140 PURCHASES · 61,000 MESSAGES · $38 TO RUNAn agency with 38 real creators on OnlyFans and Fanvue. Content and posting stay human. The engine runs every inbox, prices every fan and closes every sale, in each creator's voice, from one dashboard. The chatter floor is gone.
38 CREATORS · 2.1M MESSAGES A MONTH · CHATTER PAYROLL: $0Per platform
Each platform pays differently and polices differently. The engine carries a separate playbook, price anchor and content policy for each, and one memory of the fan across all of them.
| Platform | Average unlock | Offer to purchase | Revenue per paying fan, monthly | Payers among subscribers | Chat cost per message |
|---|---|---|---|---|---|
| OnlyFans | $28 | 64% | $112 | 19% | $0.004 |
| Fanvue | $24 | 68% | $96 | 22% | $0.004 |
| Fansly | $22 | 61% | $84 | 17% | $0.004 |
| Owned rails | $37 | 71% | $131 | 26% | $0.003 |
Across all twins, trailing 90 days. Owned rails: Telegram and native payments, no 20% platform cut, no chargeback exposure.
Undetectable
Never see the "AI-generated" tag again. Guaranteed. Not because we hide, because there is nothing for a platform to find: the images, the behaviour and the devices all read as a person.
Every photo and video is generated and finished so it carries no fingerprint a platform's detector reads. Metadata, noise pattern and provenance all say phone camera. No C2PA, no watermark, no tag.
Human timing on every send: delays, bursts, sleep, a next morning. Accounts scroll, like and follow like a person before they ever post. Nothing fires on a schedule a platform can pattern-match.
Every public post and every DM goes out from a real iPhone in our cloud phone farm, not an emulator, not an API. The platform sees a real handset with a real SIM, a real IP and a real touch.
One persona, one handset, one identity, kept for months. No shared fingerprints, no proxy pools, no mass-created accounts. Warmed the way a person's account is warmed.
Cloud phones
Her public accounts live on physical iPhones in a rack we run. Each handset is supervised over USB, streams live video to the operator, posts on a schedule, switches accounts by reading the screen, and never posts the same thing twice. A platform that fingerprints devices sees exactly what it wants to see: a phone.
CLOUDPHONES.CO · BY MIIND.DEV
For agencies
Your two biggest costs are the chatter floor and dependence on a creator who can leave. Infloww, OnlyMonster and Supercreator make your chatters faster: shared inbox, scripts, fan tags, mass DM, audit logs. A twin makes the chatters unnecessary and the creator optional. Sixty-plus agencies already run on it.
| Your stack today | A MIIND twin | |
|---|---|---|
| Who chats | Human chatters you hire, train, shift-schedule and audit | The engine, 24/7, one consistent voice, no leaks |
| Chat cost | Payroll, often 10 to 25% of revenue, plus the CRM seat | About $0.003 per message |
| The talent | A real creator you depend on | An owned persona, cloneable |
| Content | Real shoots, her cooperation | Generated on demand, pennies |
| Pricing | Scripts, PPV templates and gut feel | Adaptive, automatic, per fan, per platform |
| Ceiling | How many chatters you can manage | Unlimited personas, near zero marginal labour |
| Risks | Turnover, leaks, the creator walks, a restricted account | None of those exist. Undetectable, guaranteed |
Who built it
MIIND's conversational intelligence comes from the experience of its founder, Kunal Miind, an expert in artificial intelligence systems who has worked with the Department of Defence, banks and government agencies to bring contextual understanding to conversations: taking hyper intelligence, processing what is really being said, and feeding it back as real language.
Australia, Hong Kong, Singapore and six more countries
Creator agencies, retailers, transit operators, support teams
140 deployments, 48 million conversations, 60+ agencies
The hard part was never the words. It was knowing, before you say anything, what a person in this exact conversation would do next. That is the engine.
Contact
Tell us the channel, the volume and what a good outcome looks like. We reply as ourselves, which is the only time you will be sure it is a human.
Pilot in weeks, not quarters. One channel, real traffic, measured against your current numbers.
Your data stays yours. Integrations are read in the moment, never copied into a model.
No lock-in on voice. The persona, the boundaries and the playbook are yours to change.