The IP-to-Product Roadmap
Our proven framework for transforming your content library into a defensible, revenue-generating AI product.
Phase 1: Feasibility & POC
1-2 Weeks
Objective: To rapidly validate that your content can create a superior, high-quality AI experience.
Outcome: A working demo that proves the concept and gives you the confidence to invest in a full product.
Phase 2: Foundation & MVP Blueprint
1-2 Weeks
Objective: To architect the user experience and business logic for your new subscription product.
Outcome: A complete architectural blueprint for a market-ready application.
Phase 3: MVP Development
6-8 Weeks
Objective: To build the core, feature-complete application that users will pay for.
Outcome: A scalable, secure, and market-ready product.
Phase 4: Launch & Scale
1 Week +
Objective: To launch your new product and establish a long-term operational and growth plan.
Outcome: A new revenue stream and a successfully launched product. At this point, we define the future of our partnership.
After the Launch: Defining Our Partnership
Option A: Transition & Empower
Best for: Organizations with in-house technical teams who want to take full ownership of the product.
What it looks like: We conduct a comprehensive handover of the application, documentation, and operational knowledge. We empower your team to run, maintain, and evolve the product independently.
Option B: Operate & Evolve
Best for: Organizations that want to focus on their core business while we handle the technical and product operations.
What it looks like: We become your long-term strategic partner. We manage the application, analyze user feedback, and continuously evolve the product to meet market needs and drive growth.
Why Choose O'Donnell Systems?
The Strategic Partner vs. The Alternatives
| Assessment Criteria | Strategic AI Partner (My Approach) | SaaS Wrappers / DIY (Generic Tools) | Digital Agency (Generalist Firm) | In-House Hire (Intern or Developer) |
|---|---|---|---|---|
| Primary Goal | Revenue Generation. A deployable business asset (SaaS) built to monetize your IP immediately. | Utility. A quick "feature" to answer questions. Often becomes a cost center. | Transformation. A massive, all-encompassing digital project. | Development. Writing code. Often lacks the "Product" vision to turn code into revenue. |
| Data Strategy* | Clean & Curated. I script-clean and structure your data before the AI touches it to minimize hallucination risk. | Black Box. You upload raw files. If the data is messy, the AI fails. No nuanced control. | High Friction. They will do it, but often bill hourly for "Data Janitor" work, blowing up the budget. | Technical Only. Focuses on the database schema, rarely on the semantic quality of the content. |
| Speed to Market | 8-10 Weeks. Rapid deployment using a pre-validated, revenue-ready tech stack. | Days. Instant setup, but hits a "quality ceiling" you cannot break through. | 6-9 Months. Slowed by heavy process, multiple departments, and administrative overhead. | Slow Ramp. Hiring, onboarding, and "learning on the job" delays the launch significantly. |
| The "Who" | Veteran Builder. I combine a career of scaling complex subscription products with deep, hands-on expertise in launching this specific AI stack. You get Enterprise rigor with Startup speed. | You. You are the Product Manager. The tool provides no strategic guidance. | The Army. You pay for a PM, Account Mgr, Designer, and Devs. High burn rate. | The "Builder Gap." Most developers are trained to maintain existing code, not launch new products from Zero-to-One. Finding a single hire who spans AI, Payments, and Product Strategy is rare. |
| Extensibility & Code | Standard & Portable: Built on industry-standard stacks (Next.js/Python). Code is clean, documented, and transferable to any dev team. | Vendor Lock-In: You are a tenant. You cannot export the code, model weights, or logic. If they pivot, you lose your product. | Complex Dependency: Often built on proprietary agency frameworks or over-engineered architectures that require their specific team to maintain. | Maintenance Debt: You own it, but you are 100% responsible for every bug, patch, and server update forever. |
| Cost Structure | Fixed Project Fee. Predictable investment for a revenue-generating outcome. | Monthly Sub. Low entry cost, but scales poorly if you add users. Zero equity value. | Time & Materials. High risk of scope creep and "Change Order" fees. | High Fixed Cost. Salary + Benefits + Equity (150k–200k/yr) regardless of output. |
*Most AI projects fail because the data isn't ready. That's why we start with a Phase 1 Feasibility Audit. We ingest a sample of your content, clean it, and prove the AI works. If your data requires extensive 'janitorial' work (OCR, re-formatting), we identify that cost upfront during Phase 1—so you never get hit with surprise overages later.