Source-linked companion and content workbench

For

Writers and small content teams who want one owned AI companion for conversation, drafting and light game sessions

Solves

Companion chat, drafting, voice, memory and self-hosting live in separate rented tools, so context and data are split across subscriptions.

Delivers

Editor-approved companion replies and draft content linked to source references

Built in

about 4 weeks of creation time, MVP in 5 days

Investment

$13,500 for the MVP, $46,000 for the full product

Run it

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

Reduce tool switching and keep companion context and drafts in one owned workspace.

1. Provide an AI companion presence for conversation.
2. Generate articles, posts and other text content.
3. Adjust tone and style per project.
4. Support real-time voice chat.
5. Play supported games alongside the user.
6. Connect to approved communication and content platforms.
7. Analyze supplied data for trends and insights.
8. Support real-time multi-user collaboration.
9. Provide a simple task dashboard.
10. Offer content templates for common formats.
11. Suggest real-time clarity and flow edits.
12. Display a customizable 3D character.
13. Allow proactive companion interactions.
14. Retain long-term memory across sessions.
15. Keep a lightweight always-present design.
16. Allow character outfit and space customization.
17. Support self-hosting on user devices.
18. Keep source code open for community review.
19. Compare the reviewed result with the recorded baseline and value assumptions.
20. Capture corrections and named-owner approval before consequential use.
21. Export a versioned editor-approved companion replies and draft content linked to source references with source references and unresolved questions.

Everything these tools do, in one app

• AI companion presence Provides an AI character or assistant that users can interact with as a companion.Found in AIRI, SoulLink
• Content generation Generates written content such as articles, blog posts, or other text-based materials.Found in Aurore.ai, Twixie
• Customizable tone and style Allows users to adjust the tone and style of generated content.Found in Aurore.ai, Twixie
• Real-time voice chat Enables natural spoken conversation with the AI in real time.Found in AIRI
• Game playing Lets the AI play games such as Minecraft and Factorio alongside the user.Found in AIRI
• Platform integration Connects with popular communication or content platforms to enhance workflow.Found in AIRI, Aurore.ai, Twixie
• Data analysis Analyzes data to help identify trends and insights quickly.Found in Aurore.ai
• Real-time collaboration Supports multiple users working together on projects simultaneously.Found in Aurore.ai, Twixie
• User-friendly dashboard Provides a simple interface that simplifies task management.Found in Aurore.ai
• Content templates Offers pre-made templates for various content types like blog posts, social media updates, and emails.Found in Twixie
• Real-time editing suggestions Provides suggestions to improve clarity and flow while writing.Found in Twixie
• 3D character Displays a high-fidelity 3D character on the user's phone.Found in SoulLink
• Proactive interactions The AI occasionally initiates conversation or shares updates without a prompt.Found in SoulLink
• Long-term memory Remembers past mentions and preferences across sessions for continuity.Found in SoulLink
• Lightweight design Minimizes context switching and is always present without disrupting focus.Found in SoulLink
• Character customization Allows users to customize outfits and small interactive elements within the character's space.Found in SoulLink
• Self-hosting Enables users to host the AI on their own devices for full ownership and control.Found in AIRI
• Open source Allows community contributions and transparency.Found in AIRI

What goes in, what comes out

The workflow

1. In
   Start with

   Approved sources, style guides, past drafts and character settings

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect approved sources

4. 3

   Style guides

5. 4

   Past drafts and character settings

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Editor-approved companion replies and draft content linked to source references

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One approved source set and style guide; final publication and factual checks remain editorial. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Companion and character setup, Drafting and source-linked review, Admin and hosting console. Use a thumbnail gallery for projects and characters, a large central chat and drafting canvas, and a right-hand panel for sources, memory, tone and comments. Let users compare draft versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant passage. Make the task-specific outcome editor-approved companion replies and draft content linked to source references visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, asset versions, client comments, approval states, usage allowances, revision limits, download history and a rights record for supplied material. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.

Integrations and data access

Author-owned manuscripts, authorized interviews and permitted research sources. Cloud asset storage, design-file import/export and publishing destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

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

   5 days

   One buyer segment, one recurring use case; first modules: provide an AI companion presence for conversation; generate articles, posts and other text content. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   6 days

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

4. 4

   Full product

   10 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 writers and small content teams who want one owned AI companion for conversation, drafting and light game sessions use it to solve "companion chat, drafting, voice, memory and self-hosting live in separate rented tools, so context and data are split across subscriptions"?
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. Agree quality and outcome thresholds before the pilot using this measure: Accepted drafts per writing hour and corrections after review.
4. Measure, then decide. Track accepted drafts per writing hour and corrections after review; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Pilot scope: One approved source set and style guide; final publication and factual checks remain editorial. Implement one approved input format, a bounded representative case set and the first two task modules: provide an AI companion presence for conversation; generate articles, posts and other text content. Support the third module with operator review: adjust tone and style per project. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around editor-approved companion replies and draft content linked to source references. Retain the explicit scope boundary: One approved source set and style guide; final publication and factual checks remain editorial.

What the build depends on. Asset upload and preview, asynchronous generation jobs, editable version history, reviewer access and tested export formats. High-fidelity production requires specialist creative QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One approved source set and style guide; final publication and factual checks remain editorial.

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 a USD 300-1,500 fixed pilot for one defined asset package. Offer a monthly production allowance after repeat demand. Quote complex video, 3D or specialist design separately. These are test prices, not market benchmarks. Package the initial sale as one bounded editor-approved companion replies and draft content linked to source references. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.

Message to test

Reduce tool switching and keep companion context and drafts in one owned workspace. Demonstrate a concrete editor-approved companion replies and draft content linked to source references using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Writers and small content teams who want one owned AI companion for conversation, drafting and light game sessions professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample editor-approved companion replies and draft content linked to source references from a small authorized input set, with a transparent calculation of accepted drafts per writing hour and corrections after review and no promised savings.

The first 30 days

1. Week 1: interview five writers and small content teams who want one owned AI companion for conversation, drafting and light game sessions and inspect a recent example of companion chat, drafting, voice, memory and self-hosting live in separate rented tools, so context and data are split across subscriptions.
2. Week 2: prepare a consented or synthetic demonstration of the three task modules.
3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
4. Week 4: measure accepted drafts per writing hour and corrections after review, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.

Paid pilot

Agree quality and outcome thresholds before the pilot using this measure: Accepted drafts per writing hour and corrections after review. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.

Success metrics

Accepted drafts per writing hour and corrections after review; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs editor-approved companion replies and draft content linked to source references. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.

Why clients would pick it

A reusable library of approved styles, production constraints and review examples, together with reliable delivery for a narrow creative niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for writers and small content teams who want one owned AI companion for conversation, drafting and light game sessions. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

AIRI, Aurore.ai, Twixie and SoulLink. Compare this product with the buyer's present method on accepted drafts per writing hour and corrections after review. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Generation attempts, video or image processing, storage, reviewer hours, client revision rounds and licensed source assets. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of editor-approved companion replies and draft content linked to source references. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve author voice, source attribution, quotation accuracy and usage permissions. Authors approve substantive changes and publication scope. One approved source set and style guide; final publication and factual checks remain editorial. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.