AI customer focus layer
Your creator's DMs, running themselves.
Polylog replies to leads in your creator's own voice — texting rhythm, slang, typos and all — for as long as it takes to close. A human reviews every message until you trust it not to.
Today
hey! saw your story about the mentorship… is this actually you answering here? 😅
haha yes it's me. me on my third coffee, but me
what's up?
ok good 😂 how does the program actually work?
8 weeks, 1:1. we build your funnel from zero — want me to send how week 1 looks?
yes!!
Simulated conversation
You already know the problem.
A human team can only stretch so far.
Your funnel works because every lead feels like they're texting the person they followed. Keeping that feeling alive at scale takes a team of operators — and even the best team can't hold one voice, one memory, one rhythm across thousands of chats.
Cost & churn
Great operators are expensive to train — and when they move on, the next hire starts building the relationship from zero.
Inconsistent quality
Ten operators means ten slightly different versions of the same person. Leads notice the seams.
Leaked leads
When an operator leaves, the conversations they carried sometimes leave with them.
Nothing off-the-shelf fits
ManyChat, respond.io, SleekFlow only run bot accounts. Your creator's audience is talking to a personal number.
What if it never had to break character?
Polylog runs your creator's actual personal account and learns to sound like them — not a template of them — from their real chat history.
How Polylog works
How it stays convincing
Persona Engine
We analyze months of real conversation history — message length, emoji habits, slang, typing quirks, even typos — and build a style profile no generic prompt can fake.
Relationship memory
Every lead moves through a real relationship arc — curious, skeptical, convinced, closed — and Polylog tracks where each one is, so tone and pressure match the moment.
The human rhythm
Response delays, message chunking, the occasional typo, going quiet at 2am — Polylog paces itself like a person with a life, not a server with a queue.
Understanding, not scripting
Screenshots, voice questions, objections — Polylog reads what is actually being asked and pulls from a real knowledge base, not a decision tree.
One voice.
Every lead.
At once.
Try talking to Alex.
This is a demo persona, not a real customer conversation. Say hi.
Demo
hey 👋 i'm alex — well, a demo of me. ask me anything about how this whole "AI in your DMs" thing works
This is the part that matters most.
A human is always one tap away from taking over.
Every AI reply sits in review before it sends. In week one, that's every message. As trust builds, it narrows to the messages that matter. You decide the split.
Shadow review
A 30-second window where a human can cancel or rewrite any reply before it goes out.
Kill switch
If reply speed, repetition, or volume ever looks non-human, Polylog stops itself — automatically — until someone checks it.
Guardrails, twice
Anything the creator shouldn't promise is blocked in the prompt and filtered again after — belt and suspenders.
Full audit trail
Every message, every override, every state change — logged.
What changes when the DMs run themselves.
[X]%
reduction in operator headcount needed per creator
[X]×
more leads one persona can carry in parallel
[X]s
median response time vs. [Y] min human baseline
±[X]%
conversion held within [X]% of the human-operator baseline
Placeholders, on purpose — we publish pilot numbers only once they're real. Ask us where the current pilots stand.
Set up in days, not months.
Export the chat history
30–90 days of the creator's real conversations — that's the raw material for the voice.
Curate the voice profile
We build a style profile; you review and approve the few-shot samples that actually get used.
Load the knowledge base
FAQ, offer details, pricing, boundaries — everything the persona is allowed to say.
Go live in shadow mode
Every reply is reviewed by a human at first. Dial oversight down as trust builds — you set the pace.
Talk to us about a pilot.
We work with a limited number of teams at a time so every pilot gets real attention. Tell us about your funnel.
Got it. Talk soon.
Your request is in. Someone from the team — a real one — will get back to you within two business days.
Frequently asked questions
Long-form answers live on the FAQ page and the trust & security page.
Is this against Telegram's terms of service?
We answer this one first because you'll ask anyway: automating a personal Telegram account is not something Telegram's terms explicitly bless, and we won't pretend otherwise. Polylog is built to keep an account's behavior within human patterns — real response delays, human-scale message volume, hard rate limits, and an automatic stop if anything starts to look non-human. Every pilot starts with a frank conversation about this trade-off, and we never run an account without the owner's informed consent. [Draft answer — pending legal review.]
What happens if the AI says something wrong?
Several layers exist exactly for this. Anything the creator shouldn't promise is blocked in the prompt and filtered again after generation. During early weeks, every reply sits in a shadow-review window where a human can rewrite or cancel it before it sends. If something still slips through, a human can take over the conversation instantly, and the full audit trail shows exactly what was sent, when, and why.
Does this replace our operators entirely?
No — it changes their job. Instead of typing hundreds of messages a day, your best people review the conversations that matter: approving sensitive replies, stepping in on high-value leads, and closing. One reviewer can oversee the volume that used to take a full shift of operators.
What data do you store, and for how long?
To build a persona we process the creator's exported chat history; to run conversations we store the active dialog state and an audit log of every AI action. Data is retained for the duration of the engagement plus a defined wind-down window, is not used to train shared models, and is deleted on request. The specifics live on our legal page — and in the pilot agreement in plain language.
Which languages and verticals does this work for?
Any language the creator actually texts in — the persona is learned from their own history, not from an English-first template, so slang and mixed-language chats carry over. It fits any funnel where leads expect a personal 1:1 conversation over weeks: coaching, communities, info-products, expert services, personal-brand offers.