Airtable & Make.com Expert Needed to Build AI-Powered Music Catalog MVP

About the Project I’m building the first MVP (Minimum Viable Product) of Synchos, an AI-powered music catalog and sync management platform for independent artists, producers, composers, and songwriters. The goal is to create a system that automatically organizes songs, stores all related assets, generates AI metadata, and prepares songs for sync licensing opportunities. This is NOT a website or SaaS project. This project is focused on building a clean, scalable Airtable foundation with one Make.com automation that I will personally use to organize my music catalog. This Airtable MVP will later serve as the blueprint for a custom SaaS platform. I already have Google AI Studio (Gemini API) credits and would like to use Gemini if possible. ⸻ Please Read Although Upwork shows this as a Contract-to-Hire opportunity due to an app limitation, this is NOT a full-time position. This is a small fixed-price MVP project with a budget of $100–150. I’m looking for someone who enjoys building clean, scalable systems—not someone who simply wants to complete a quick gig. If we work well together, I expect there will be additional paid milestones and future projects, but there is no expectation of full-time employment. ⸻ Project Goal Build Version 1 of the Synchos foundation. I value: * Clean database architecture * Good organization * Scalability * Documentation * Maintainability over having lots of unfinished features. ⸻ Scope of Work 1. Airtable Database Create a clean relational Airtable base using linked records. Tables * Songs * Collaborators * Writers * Publishers * Music Libraries * Music Supervisors * Agencies * Pitch History ⸻ 2. Songs Table Each Song record should support: Basic Information * Song Title * Artist * BPM * Key * Genre * Subgenre * Mood * Theme * Explicit / Clean * Availability * Notes Attachments * MP3 or WAV * Cover Art * Lyric Sheet * Split Sheet Links * DISCO Link AI Fields * Song Description * AI Song Summary * Keywords * Sync Categories * Metadata All AI-generated fields must remain manually editable. ⸻ 3. Airtable Interface Create a clean interface that feels like an application instead of a spreadsheet. Dashboard Display: * Total Songs * Ready to Pitch * Never Pitched * Missing Assets * Recent Songs * Follow-Ups Due My Catalog Search and filter songs. Song Details Every field should be editable. ⸻ 4. Views & Filters Create useful views including: * Ready to Pitch * Never Pitched * Missing Lyrics * Missing Split Sheet * Missing Cover Art * Missing Metadata * Available * Exclusive * Non-Exclusive * Sports * Trailer * Hip-Hop * Pop * Explicit * Clean ⸻ 5. Simple CRM Create linked tables for: Music Libraries * Library Name * Website * Contact * Email * Notes Music Supervisors * Name * Company * Email * Notes Agencies * Name * Contact * Email * Notes Pitch History Each pitch should link to a Song. Track: * Song * Contact * Date Sent * Status * Notes ⸻ 6. One Make.com Automation Build one automation using: Airtable → Make.com → Google AI Studio (Gemini API) → Airtable When I upload a song package (whatever information is available): * MP3/WAV * Lyric Sheet * Split Sheet * Cover Art * DISCO Link The automation should: * Extract embedded audio metadata when available (such as Song Title and Artist from ID3 tags) * Send the available information to Gemini * Generate: * Song Description * Genre * Mood * Theme * Keywords * Sync Categories * AI Song Summary * Automatically populate the Airtable record If full audio analysis is not practical within this budget, please use the available text and metadata while preserving the uploaded audio for future enhancements. ⸻ 7. Collaborator Memory When a split sheet is uploaded, the system should attempt to extract collaborator information whenever possible. Examples: * Name * Email * PRO (Performing Rights Organization such as BMI, ASCAP, SESAC) * Publisher This information should be stored in reusable Collaborator records so I do not have to enter it again for future songs. Song-specific ownership percentages should remain unique to each song. ⸻ 8. Manual Editing Everything generated by AI must remain editable. Nothing should be locked. ⸻ 9. Documentation Please provide: * Airtable Base * Make.com Scenario * Setup Instructions * Instructions for updating the Gemini API key ⸻ Important This project is intentionally small. I understand my budget is limited. I would rather have a clean, scalable, well-organized foundation than lots of unfinished features. I am looking for someone who understands database design and automation and can help me build Version 1 correctly. ⸻ Future Phases Future paid phases may include: * AI Split Sheet Generator * Spotify Reference Analyzer * YouTube Reference Analyzer * AI Brief Matching * AI Song Recommendations * Semantic Lyric Search * Advanced CRM * Additional Make.com Automations * Custom SaaS Development My goal is to continue working with the same developer if this MVP is successful. ⸻ Please Answer These Questions 1. Have you built Airtable + Make.com systems before? 2. Have you integrated Google AI Studio (Gemini API) or another LLM API into Make.com? 3. Please share one or two similar projects. 4. If you had my budget ($100–150), what would you prioritize building first? 5. What would you simplify to ensure this MVP is successful? 6. Can this Airtable structure easily migrate into a future SaaS platform? 7. Is there anything you would recommend changing to make this MVP stronger while staying within budget? Please begin your proposal with the word “Synchos” so I know you’ve read the full project description.