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For creators with content libraries
Q ingests your videos, podcasts, and docs, then answers subscriber questions in your voice — citing the exact moment you said it. On your domain, under your brand.
Live in production · 1,300+ videos indexed · 78,000+ searchable segments
01How it works
YouTube transcripts, podcast audio, docs, PDFs, web URLs. Q embeds every minute and every page locally. Your back catalog goes in once.
Your subscribers ask in plain language. Semantic search finds the exact passages — not keyword matches — across everything you’ve ingested.
Q assembles a reply in your voice, grounded in the retrieved passages. Every claim links back to the source moment in the video or page in the doc.
02How it feels
Across three episodes I’ve described a consistent framework: does the idea match a real pain I’ve seen; can I prototype the answer in a weekend; would I pay for it myself. I’ve called the third question the most load-bearing.
Illustrative. Click any citation to jump to the moment in the video or page in the doc.
03Already in production
Q isn’t a demo. A flagship podcast tenant runs in production today, with more in private testing.
1,300+
videos indexed
78,000+
searchable segments
100%
of answers cite source
~9
sources per answer
Real numbers from production tenants — not aspiration.
Every answer carries its receipts.
That’s the whole product.
04Accuracy
General-purpose LLMs are great for chat. They’re not built to answer questions about YOUR content with source-fidelity. Here’s where Q is different.
Sources cited per answer
From Q’s production tenants: every assistant message carries an average of nine source references with timestamp or page anchor. Real number, not aspiration.
| Capability | Q | ChatGPT, Claude |
|---|---|---|
| Every answer cites the source it came from | Only if prompted; can hallucinate citations | |
| Answers grounded in YOUR content, not general training data | No — pulls from whatever was in training | |
| Citation jumps to the exact moment (video timestamp, doc page) | No | |
| Speaks in your voice, on your domain, with your brand | Generic chatbot wrapper at best | |
| Remembers returning subscribers across sessions | Session-scoped only | |
| Searches your YouTube transcripts, podcasts, docs together | One PDF at a time, manually |
05In your voice
Q answers in the creator’s actual voice, drawing on their actual content. Same subscriber question, routed through two tenants. The vocabulary, the cadence, the references all change.
Tenant A · strength coach, 12 yrs of programs
Tenant B · interview podcast, 400+ episodes
Illustrative. Both tenants anonymized; voice differences are real consequences of per-tenant instructions and source content.
06Creator dashboard
Every question is intent data. Q surfaces the patterns: which topics resonate, which gaps to fill, which answers landed. Open your dashboard and you see this.
Questions your audience keeps asking that Q can’t answer with confidence. The shortlist for what to record next.
Most from returning subscribers — the deep-catalog askers.
Illustrative dashboard — example numbers.
07Why it compounds
Platforms come and go. The thing nobody can take from you — or copy — is the body of work you’ve already made. Q is how it starts working for you.
You already made the content. Most of it sits unwatched past week one, answering nobody. Q turns the archive into a working answer layer — every old episode back in circulation, every question routed to the moment you addressed it.
Answers cite across your whole catalog, so new episodes make old ones more findable — and the questions Q can’t answer become your content roadmap. The library gets more valuable the longer you’ve been at it. Fifteen years in is an advantage, not baggage.
Anyone can copy your format. Nobody can copy your corpus. An assistant built from your work, answering in your voice on your domain, is a reason to subscribe — and to stay — that doesn’t exist anywhere else.
08Platform
Live on your domain. Your colors, your voice. Subscribers feel like they’re talking to you, not to a generic chatbot.
Every answer points to the exact moment in a video, the page in a PDF, the paragraph in a doc. No hallucinations. No “trust me” answers.
YouTube transcripts, podcast audio, docs, PDFs. Ingest your back catalog once; subscribers search every minute of it.
Subscribers sign in with Discord or Google. Open the knowledge base for previews, or lock it down to members-only.
What did your audience ask this week? Where did Q struggle? You see it; you tune it; the answers get better.
Your data lives in your tenant. Domain-based isolation, scoped queries, separate ingestion. The plumbing under the chatbot is built for production.
Works with your library
09Memory & trust
Q remembers each subscriber across sessions — what they asked about, what they came back for. And every subscriber can see exactly what Q remembers about them, and delete any of it.
Domain-based isolation, scoped queries, separate ingestion pipelines. Your data lives in your tenant and never leaks into another creator’s answers.
A subscriber removes a memory and it’s gone. Hard delete, with audit history showing only redacted markers. GDPR-aligned by default.
Embeddings run locally on our infrastructure, not OpenAI. Your transcripts and docs stay in your tenant. Export available if you ever need to walk.
10FAQ
Early access
Q is in early access. If you’ve got a content library and an audience that asks questions, we should talk.
Get Early AccessFounding-tenant pricing locked in for early-access customers.