Document Live AI Host

For

Content marketers, course creators and report publishers

Solves

Written reports, decks and blog posts deserve a live audience but creators lack time and on-camera skill to go live consistently.

Delivers

Scheduled live broadcast with AI host, chat transcript and viewer engagement report

Built in

about 2 weeks of creation time, MVP in 2 days

Investment

$5,500 for the MVP, $17,500 for the full product

Run it

Inside your business, or as part of your offer to clients

For content marketers, course creators and report publishers, turn uploaded documents, links or Notion pages into scheduled live broadcasts with an AI host that reads, presents and answers questions.

1. Extract and summarise document content into a script.
2. Select an AI avatar and synthetic voice.
3. Schedule a live stream to Facebook Live, YouTube or RTMP.
4. Present slides and images alongside spoken script.
5. Answer live chat questions using a language model.
6. Label the stream as synthetic media and moderate responses.

What goes in, what comes out

The workflow

1. In
   Start with

   Documents, links, Notion pages, avatar preferences, stream schedule

2. 1

   Upload a document

3. 2

   Extract and review the script

4. 3

   Choose avatar and voice

5. 4

   Schedule the stream

6. 5

   Run a test broadcast

7. 6

   Go live on autopilot

8. 7

   Review chat logs after the event

9. Out
   Finish with

   Scheduled live broadcast with AI host, chat transcript and viewer engagement report

AI does the heavy lifting, people stay in charge

Use language models to extract content, generate a script and answer chat questions. Use text-to-speech and avatar generation for presentation. A human reviews the script and avatar before scheduling to ensure accuracy and tone. Moderation filters block inappropriate responses before they reach viewers.

What your team sees

Key screens: Document upload, script editor, avatar and voice picker, live stream scheduler. Use a simple upload drop zone for documents or links, a script editor showing extracted content with editable sections, an avatar and voice selection panel with preview, and a scheduler with platform and time settings. Show stream status and chat moderation queue during broadcast. In this product, the first view is document upload, followed by script editor, avatar picker and scheduler.

Accounts and administration

User accounts, stream schedules, script versions, avatar and voice settings, moderation rules, broadcast history, disclosure labels and audit trail of edits.

Integrations and data access

Start with Facebook Live, YouTube and RTMP endpoints; later add Notion, Google Drive, Slack for notifications and Zoom for hybrid events.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   2 days

   One buyer segment, one recurring use case. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   3 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   6 days

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will content marketers, course creators and report publishers use it to solve "written reports, decks and blog posts deserve a live audience but creators lack time and on-camera skill to go live consistently"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Run a paid pilot with five content marketers broadcasting weekly for a month.
4. Measure, then decide. Track two measurable outcomes: number of scheduled broadcasts per user per month and and average viewer engagement time compared to pre-recorded videos. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. First cut: one buyer (content marketer), one use case (blog post to Facebook Live), first two modules (script generation and basic avatar broadcast), manual review of script and chat responses before going live.

After the MVP. After paid pilot, automate chat moderation with better filters, add multi-platform streaming, custom avatars from user photos, and integration with Notion and Google Drive for live document updates.

What the build depends on. Needs reliable text-to-speech and avatar generation APIs, a language model with moderation filters, and streaming infrastructure that supports scheduled broadcasts.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test pricing at USD 49 per month for basic streams, USD 99 for chat interaction and custom avatars, USD 199 for multi-platform and priority support.

Message to test

Turn any document into a live AI broadcast that presents itself and answers questions.

Where to find buyers

Content marketing communities, course creator forums, social media groups for video marketers, and webinars on live streaming tools.

Lead magnet

Free demonstration of a blog post turned into a live AI broadcast with a sample avatar and chat interaction.

The first 30 days

1. Week 1: Build document upload and script generation.
2. Week 2: Integrate text-to-speech and basic avatar rendering.
3. Week 3: Add streaming to Facebook Live and scheduler.
4. Week 4: Test with five creators, collect feedback on script quality and viewer trust.

Paid pilot

Run a paid pilot with five content marketers broadcasting weekly for a month. Baseline is their current live streaming frequency and engagement; success is at least three scheduled broadcasts per user and positive viewer feedback on clarity and interaction.

Success metrics

Two measurable outcomes: number of scheduled broadcasts per user per month, and average viewer engagement time compared to pre-recorded videos.

Retention and expansion

Keeps earning through monthly subscriptions, with upsells for more stream hours, advanced chat features and custom avatars; renewals depend on consistent broadcast value.

Why clients would pick it

Grows harder to copy as the system learns from thousands of broadcasts, improving script quality, moderation accuracy and avatar realism, plus accumulated viewer engagement data.

Alternatives and positioning

Creators use pre-recorded videos, webinars with human hosts, or simple text-to-video tools; this differs by offering live interaction and autopilot scheduling.

Main delivery costs

Main delivery costs are cloud compute for avatar rendering, text-to-speech generation, language model API calls for chat, and video streaming bandwidth.

Require clear synthetic media disclosure on all streams. Moderate chat with filters and human review queue. Block inappropriate responses. Do not impersonate real people or present false information as fact. Limit access to authorised users and keep audit logs of all broadcasts.