The Opportunity

Your members already share knowledge informally — phone calls, emails, conference conversations. The expertise is real and valuable, but the exchange is ad hoc, unattributed, and unrewarded. When a member needs an answer that spans multiple sources, regulations, and jurisdictions, the bottleneck is not the knowledge — it is the time it takes to find it, assemble it, and verify it.

What if that same expertise were governed, attributed, and instantly accessible — with every source cited, every contributor recognized, and weeks compressed into seconds?

What This Is

A closed pilot with 3–5 industry leaders. Not a software purchase. Not a subscription. A collaborative effort to build a governed knowledge network where:

• Each participant contributes domain expertise under their own governance
• AI synthesizes answers from multiple sources, citing every one
• Contributors earn recognition when their knowledge helps others
• Premium content can be licensed through bilateral agreements — with usage tracked, attributed, and settled between participants
• Every participant controls what they share, with whom, and at what level of access

Think of the difference between calling your lawyer — scheduling the call, waiting for availability, hoping your question gets adequate time — and having governed, sourced answers from multiple experts available instantly, 24 hours a day. Every professional services firm faces this same challenge: how to make senior expertise accessible without bottlenecking on the senior people. The expertise exists. The time to access it changes everything.

What Participants Contribute and Receive

How It Works

The platform connects participants through governed agreements. Each participant maintains their own knowledge base under their own governance. Content flows between participants through bilateral agreements — with every piece of content attributed to its source.

When a member asks a question, the system retrieves relevant content from across the network, synthesizes an answer, and cites every source. Contributors whose content was used earn recognition. Premium content can be licensed under terms the provider sets — usage is metered, and participants settle directly.

Your Own AI Assistant

Each participant gets their own branded AI assistant — a dedicated instance on their own subdomain, with their own content, their own branding, and their own access levels. This is not a shared chatbot. It is your organization's governed knowledge, made conversational.

Public access (level 0): Your website visitors can interact with your public-facing AI assistant. It answers from your published content — product information, compliance guidance, FAQs — with every source cited. This is your expertise, available 24/7, governed and attributed.

Customer access (level 1): Your clients and select partners can be provisioned as users on your instance — an extranet for governed self-service. Customers query your content at their access level, with no ability to upload or modify. When a customer needs confirmation before acting, they click Get Verified and the request routes to your customer service team. Governed self-service, with human expertise a click away.

Employee access (level 2+): Your team members log in and access internal content at the appropriate level. Sensitive frameworks, draft policies, operational procedures — all queryable through the same interface, restricted by the access levels you set. Employees can upload and contribute content at their designated level.

C-Level access (level 7+): Decision-makers access the most sensitive strategic content — board-level analysis, competitive intelligence, unreleased strategy. This content is invisible to employees at lower levels. C-Level users get their own executive AI assistant experience: the same platform, the same interface, but a knowledge base reflecting their decision-making scope. Through peer agreements, C-Level content can be shared exclusively with C-Level contacts at peer organizations — a CEO's strategic analysis visible only to other CEOs in the network, not to all employees across the organizations.

Private documents (user-only): Every user — at any access level — can upload private documents that only they can access. Personal notes, draft analysis, research in progress, meeting preparation — all queryable through the assistant alongside the user's other accessible content. Private documents never enter the shared knowledge base and are never visible to other users, regardless of access level. Every member gets their own personal AI research assistant within the governed environment.

Network access (peer agreements): When your team queries content that spans peer agreements, the assistant draws from the network — upstream regulations, downstream operational knowledge, cross-participant expertise. Access levels on peer agreements control which content is visible to which roles — employee-level agreements share operational content, C-Level agreements share strategic content. The peer content enriches your assistant without exposing your internal content to others.

Internal Get Verified: Employees can request verification of any AI-synthesized answer before acting on it. The request routes to the appropriate internal subject-matter expert based on which content was cited. The expert verifies the synthesis — faster than creating an original response. Every verification creates a decision-making audit trail: who asked, what the AI synthesized, who verified, and when. Verification activity can be tied to internal incentive programs through Rosie's KPI dashboard.

Cross-network collaboration: Peer agreement access levels determine which employees can collaborate across organizations. When a question spans the network, employees from different participants can contribute to the same verification — each addressing the portion their organization's content informed. The audit trail spans organizations, governed by the same agreements that govern the content.

This removes the temptation and risk of employees using uncontrolled AI tools. When your own AI assistant provides governed, sourced, access-controlled answers from your own content and your trusted peers — with professional verification built into the workflow — there is no reason to paste internal documents into a public LLM.

You Control What You Share

Every document has an access level that you set. Internal knowledge stays internal. Only content you explicitly publish enters the network. You choose:

• What content — which documents, frameworks, or knowledge to contribute
• At what level — access levels from internal-only to fully public
• With whom — agreements are bilateral; you negotiate terms per participant
• How it's attributed — to your organization, to named contributors, or both
• Premium terms — set your own licensing terms for high-value content

Your competitive advantage is not your documentation — it is your people's judgment in applying that knowledge. The platform makes governed knowledge accessible. It does not replace the expertise behind it. It mitigates the risk of acting without it.

The Case Study

The pilot produces a Case Study documenting the results — including measurable time compression: how long answers took before the network versus after. The primary purpose is strategic: a credible Case Study with named industry leaders attracts other major players to the network — which directly benefits the original participants. More participants means richer answers, broader governance coverage, and a stronger network for everyone involved.

Participants choose whether to be named or anonymized in the Case Study. Even anonymized profiles carry weight when the participating firms are recognizable by description.

Why Coopetition Works Here

Competitors in the same industry face the same regulatory landscape, the same compliance requirements, and the same governance challenges. This shared reality is not a competitive differentiator — it is the cost of operating in the industry. Collaborating on governed knowledge infrastructure makes each participant more efficient without revealing what actually differentiates them: their strategy, their relationships, and their people.

The question is not whether to share knowledge across organizational boundaries. The question is whether to do it with governance, attribution, and recognition — compressing the time from question to confident answer — or without.

Growing the Network: The Supply Chain Advantage

The real power of the network emerges when it extends up and down the supply chain — upstream regulators, participants in the middle, downstream operators — all linked by governed agreements.

This is the content provenance chain:

From seconds to confidence: Get Verified

The AI-synthesized answer arrives in seconds. But before a member acts on it — before it informs a shipment, a classification, or a compliance decision — they may want professional verification.

Every Rosie response includes an AI disclaimer with a call to action: Get Verified. When a member clicks it, the response is routed to the contributors whose content was cited, asking them to verify the synthesis. This is faster and easier than creating an original response — the expert reviews and confirms rather than researching and writing from scratch.

journey
title As-Is — Time to confidence today (days to weeks)
section Traditional path
Ask: 3: Member
Find expert: 1: Member
Schedule call: 1: Member
Wait days: 1: Member
Receive opinion: 3: Expert
Follow up: 2: Member
Act: 3: Member

journey
title To-Be — With the Rosie network (hours)
section Rosie path
Ask: 5: Member
AI synthesizes: 5: Rosie
Get Verified: 5: Member
Expert confirms: 5: Expert
Act with confidence: 5: Member

The pilot is the starting point. The supply chain is the vision.

Pricing Strategy

Pricing for the pilot is designed to be transparent, fair, and shaped by the participants. Several models are available — the right choice depends on how the group wants to share costs and value. The goal is for everyone to see clearly what they pay, what they get, and how contributing more reduces their cost over time.

Per-seat model: Each participant pays a monthly fee per member seat on the platform. This is the simplest model — predictable costs, easy to budget. Each seat includes a monthly query allocation. Members who exceed their allocation pay a modest per-query overage, comparable to how mobile data plans work.

Usage-based model: Participants pay based on actual query volume rather than seat count. Lower risk for organizations still evaluating the platform. Higher cost per query, but no commitment to seats that may go unused during the pilot.

Contribution offset: In either model, members who contribute content that helps others earn Recognition of Contribution credits — additional queries at no cost. Active contributors effectively reduce their own costs by adding value to the network. This is not a discount. It is the economic engine of the ecosystem: the more you contribute, the more you can query.

Premium content licensing (IPR): Participants who contribute high-value, specialized content can set their own licensing terms. Usage is metered by the platform and reported monthly. Participants settle directly — the platform tracks attribution but does not handle payments. This creates a revenue stream for content providers, not just a cost.

Verification services: Verification can be performed by the original content contributors or by independent third parties — auditors, specialists, or any qualified expert on the network. Pricing for verification is set by the verifier — per verification, by complexity tier, or as part of a retainer. The platform routes verification requests based on which content was cited in the response, and the member can select contributor verification, third-party verification, or both. For complex questions spanning the supply chain, multiple verifiers can collaborate, each addressing the portion they are qualified to confirm. Internal verification can be tied to employee incentive programs through the platform's KPI dashboard — recognizing team members who contribute to governance quality.

Pilot pricing vs long-term pricing: The pilot is an opportunity to test the model before committing to long-term terms. Pilot pricing can be structured as a fixed commitment for the pilot duration, with the understanding that long-term pricing will be informed by actual usage patterns, content contribution levels, and the value participants experience.

The specifics — seat fees, query allocations, overage rates — are negotiated with participants. They can be set by the ecosystem lead, or the participants can collaborate on a pricing structure that reflects how they want to share costs and value. Either approach works. The platform supports both.

For context: a consultant engagement typically takes days to weeks from question to answer. A professional phone call addresses three questions in six minutes — if you can get on the calendar. The pilot puts governed, sourced answers from multiple experts at your members' fingertips in seconds — with professional verification available in hours, not weeks.

Next Steps

Collab.Ventures — Building governed knowledge networks for organizations that depend on each other.

Too much? See the Executive Summary →

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