Proposal

1. The Vision: "Pure Authenticity" at Scale

Most AI video tools (like Sora or Runway) try to invent reality. They create fake people and fake beaches.
Viral Vacation is different.

Your competitive advantage—your "Moat"—is the terabytes of Real, Geotagged, 4K Local Footage you possess. The vision is to build an autonomous engine that:

1. Ingests the real world (Reviews, Weather, Menus).

2. Matches it with authentic local footage (The "Data Moat").

3. Assembles cinematic commercials in seconds.

4. Cross-Pollinates the local economy, breaking the silos between a Condo, a Restaurant, and an Activity Provider.

The Goal: To separate the "Creative Thinking" from the "Technical Doing," allowing a property manager to scale their marketing infinitely without adding a single human to their payroll.

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2. Destination & ICP: Who are we building for?

To secure Angel Investment, the MVP cannot just be "cool tech." It must be a revenue engine. We are optimizing the build for two specific user types:

A. The High-Ticket Payer (The "Hearth & Home" Group)

• Who: Vacation Property Managers & Luxury Real Estate Agents.

• Why they buy: They are not selling four walls; they are selling the 30A Lifestyle. They have the budget (

          1k−1k-1k−
        

  3k/mo) but zero time to edit reels.

   

• The MVP Promise: "A 5-star review comes in; a marketing video goes out. You don't lift a finger."

B. The Content Feeder (The "Flavor & Flair" Group)

• Who: Restaurants, Retail, Activity Providers.

• Why they join: Visibility. They provide the "Oyster Shots" and "Sunset Cruises" that the Real Estate agents need to sell the lifestyle.

• The MVP Promise: "Free exposure. Your brand gets featured in the marketing of the most expensive homes in the area."

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3. Current State of Thought (The Baseline)

Based on the workflows and spreadsheets you provided, the initial technical assumptions were:

• Orchestration: Using N8N for all logic and file handling.

• Storage: Using Google Drive to host the video assets.

• Logic: Relying on Direct Text Mentions in reviews (e.g., "We went to Austin's") to trigger cross-pollination.

• Generative AI: Using generic tools to "add lifestyle elements" (like fake kids playing) into photos.

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4. Missing Gaps & Critical Risks

To protect your investment, we need to be honest about the risks in the current plan. If we built it exactly as originally described, here is where it would break:

1. The "Heavy File" Crash (The N8N Limit)
N8N is incredible for logic, but it is not designed to handle 4K video files (which can be 500MB+). If we try to pass a video file through an N8N node, the automation will time out and crash. We need a "Pass-Through" architecture.

2. The "Google Drive" Latency
Google Drive is a personal storage tool, not a cloud video server. It has strict rate limits. If 50 clients try to render a video at once, Google will block the connection. We must move to professional infrastructure.

3. The "Missing Shot" Problem
What happens if the AI script calls for "A close-up of a kid eating chocolate ice cream" but your library doesn't have that specific shot? Currently, the automation would fail. We need a fallback protocol.

4. The "Logic" Trap
Statistically, less than 5% of reviews mention a partner business by name. If we rely solely on "Text Mentions," the cross-pollination feature—your biggest selling point—will rarely fire. We need a smarter "Persona-Based" logic.

5. Phasing Misalignment
The original plan listed "Social Publishing" in Phase 4. You cannot launch a product called "Viral Vacation" in Phase 1 if the user has to download the video and post it manually. The loop must be closed immediately.

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5. Our Improved Planning: The "Hybrid Cloud Factory"

We are shifting the architecture from a "Low-Code Prototype" to a "Professional Cloud Application."

A. The New Architecture (The Workflow)

We will use N8N as the "Manager" (traffic control), but we will use Python code and specialized APIs for the "Heavy Lifting."

• The Vault (AWS S3): We will use Amazon S3 instead of Google Drive. It is infinite, secure, and instant. We will use "Presigned URLs" so that N8N only handles lightweight text links, never the heavy video files.

• The Brain (RAG): We will build your "Poppi.ai" replacement using OpenAI (GPT-4o) connected to a Pinecone Vector Database. This database will store your "Brand Voice" and "Tourism Trends" so the AI writes scripts that sound like a local expert.

• The Factory (Shotstack + Python): We will use Shotstack (as you suggested) for the rendering. But we will add a Python/Librosa layer to analyze the music beats. This ensures every video cut happens exactly on the beat, which is the difference between a "Slideshow" and a "Viral Reel."

B. The "Nano Banana" Fallback Protocol

You identified Nano Banana Pro (Google Gemini 3 Image Model). This is a brilliant find. We will use this to solve the "Missing Shot" problem.

• Scenario: Script calls for "Oysters," but no footage exists.

• Action: System generates a photorealistic image via Nano Banana Pro.

• The Magic: We pass this image through a "Motion Layer" (using Shotstack’s Ken Burns effect or a tool like Runway API) to make the steam rise or the light move.

• Result: The video flow never breaks, and it looks cinematic.

C. The "Google Search" Domination

Instead of building a complex Google Ads Manager (which is high-risk for an MVP), we will automate Google Business Profile Updates.

• The Strategy: Every video we generate is auto-posted to the client's Google Maps listing.

• The SEO Hack: We will inject Geotags and Keyword Metadata into the file headers before uploading. This signals to Google’s algorithm that your content is hyper-relevant, boosting your clients' search rankings organically.

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6. The Phased Roadmap

We have restructured your list to prioritize Revenue and Technical Stability. We pulled "Phase 2" items into "Phase 1" because they are mission-critical.

Phase 1: The "Investor-Ready" MVP (Weeks 1-8)

Goal: A working "Review-to-Video" engine that posts to social media.

• 1. The Data Vault & Smart Ingestion:

  • Setup AWS S3 Storage.

  • Computer Vision Layer: As you upload content, our AI (Banana.dev) auto-tags it: [Sunset, Balcony, Wine, Oysters]. This eliminates the need for manual tagging.

• 2. The Nexus Engine (The Logic):

  • Input: System listens for a Google Review.

  • Scripting: GPT-4o generates the JSON Shot List based on the review sentiment.

• 3. The Factory (Video Generation):

  • Shotstack Integration: We connect the JSON output to the Shotstack rendering engine.

  • Fallback Logic: Implement the Nano Banana image generator for missing assets.

• 4. Publishing (Ayrshare Integration):

  • Strategic Shift: We are pulling "Social Publishing" from Phase 4 to Phase 1.

  • Outcome: The dashboard will allow "One-Click Scheduling" to IG, TikTok, and YouTube Shorts immediately.

Phase 2: The Ecosystem Activation (Weeks 9-14)

Goal: Activating Cross-Pollination & Growth.

• 1. Smart Cross-Pollination Logic:

  • Move beyond "Text Matches." Implement "Persona Matching." (e.g., A "Luxury" Condo review automatically pulls content from "Fine Dining" partners, even if they weren't mentioned).

  • Brand Tiers: Logic to ensure Luxury brands don't accidentally promote budget activities.

• 2. The "Scraper" Suite:

  • Deploy the N8N workflows to scrape local events and prices to feed the "Brain" with real-time context.

• 3. Google Business Profile SEO:

  • Automate the "Update" posts to Google Maps with injected SEO metadata.

Phase 3: Scale & Ads (Month 4+)

Goal: High-Volume Growth.

• 1. Contributor App: A portal for influencers to upload B-Roll and get credited (Faceless content only for legal safety).

• 2. Ad-Boosting Bridge: Allow users to "Boost" their best organic videos via Meta Ads API.

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Here is the pricing section to add to the end of the proposal.

Strategy Note: I have priced this based on a Fixed-Cost Project model (

        25k–25k–25k–
      

30k range). This is "Industry Standard" for a full-stack SaaS MVP involving video engineering, AI, and cloud infrastructure. Hourly billing (Time & Materials) often scares clients like Cory because they fear "runaway costs."

 

A fixed price aligns with your promise to be "Partners, not just Devs."

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7. Investment & Operational Estimates

We believe in radical transparency. Below is the breakdown of the One-Time Development Investment to build the platform, and the Estimated Monthly Infrastructure Costs (OpEx) that you will pay directly to providers to keep the lights on.

A. Development Investment (Fixed Cost)

We have estimated the effort at approximately 700-900 engineering hours to deliver Phase 1 (The MVP) and Phase 2 (Ecosystem Activation).

Instead of an hourly billing model which carries risk for you, we propose a Fixed Project Fee to guarantee delivery within budget.

Payment Schedule (Milestone-Based):

• 30% Deposit: To kick off architecture & setup 

• 40% Milestone: Upon completion of the  Phase

• 30% Final: Upon Completion

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B. Estimated Monthly Operational Costs (OpEx)

These are the rough costs for the 3rd-party tools powering the engine. You will pay these directly (your credit card on the accounts). These costs scale with your usage—meaning you only pay more when you have more paying customers.

Estimates based on ~50 Active Clients generating ~500 Videos/Month:

Why this is a healthy model:
If you charge your 50 clients an average of

        500/month∗∗,yourrevenueis∗∗500/month**, your revenue is **500/month∗∗,yourrevenueis∗∗
      

25,000/month.
Your tech cost is only ~$750/month. This is an extremely high-margin SaaS model (97% Gross Margin).

 

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8. The "No-Bug" Guarantee

Cory, you mentioned trauma from previous developers leaving you with a buggy product. Because we are building this on Shotstack and AWS (Enterprise Grade) rather than cobbling it together with N8N (Prototype Grade), we are confident in the stability.

Our Commitment:
We include a 30-Day Hyper-Care Period after launch. Any bugs, glitches, or logic errors found in the first month are fixed at $0 cost to you. We don't walk away until the engine is humming.