SponsorBase

AI Sponsorship Management Platform

Empowering creators to navigate sponsorship deals with AI confidence

Content creators are signing sponsorship contracts they don't understand, leaving them vulnerable to unfair terms and lost revenue.

Timeline

6 Weeks

(Research → Launch)

Role

Solo Founder

Product Designer

Engineer

90+

Signups (Organic)

87%

Satisfaction Score

22s

Avg Analysis Time

The Challenge

While platforms like FYPM solved pay transparency, no tool helps creators analyze if a specific contract is actually fair. Creators suffer from "contract anxiety" and often sign bad deals because they lack legal context.

Research & Discovery

Instead of jumping straight to building, I spent 4 weeks validating the opportunity. I analyzed 50+ Reddit threads and audited 8 competing platforms, finding zero AI contract tools for individual creators.

Qualitative Research. I used Dovetail to synthesize insights from interviews with 8 creators, revealing a key insight: "I don't know what I don't know." They can't spot unfair terms because they don't know what to look for. They needed instant mobile analysis since 70% of deal work happens on phones.

Design Philosophy

Simple, Lovable, Complete (SLC). Instead of shipping a minimum viable product, I focused on shipping a complete solution to one focused problem.

Simple

One product

($24.99/mo)

Lovable

Premium design

Streaming AI

Complete

Full workflow

Scam detection & Review

UX Strategy

Mobile Only. Designed for 375px-428px viewports.

Conversation Cards over Forms. Users tap "Check for Scams" or "Review Contract"—it feels like texting a knowledgeable friend, not filling out a legal document.

Natural Language Output. Replaced "The perpetuity clause in Section 4.2..." with "Red flag: This brand can use your content forever."

AI Architecture

I implemented three different AI models, selecting each based on speed, cost, and reasoning requirements. Total AI costs are just $3/month for 1,000 users.

Perplexity

Rate Calculator

Real-time search

Gemini 2.0 Flash

Email Templates

2x faster, 66x cheaper

GPT-4

Contract Assistant

Complex reasoning

Testing & Iteration

Beta Testing. Tested with 10 users for 1 week to validate the core value proposition.

Qualitative Insights. Direct feedback from beta testers revealed that while the analysis was accurate, the legal jargon was still intimidating. This led to "Iteration 1," where I replaced legal terms with natural language severity levels (🟢🟡🔴) to make the impact of each clause immediately obvious.

Quantitative Insights. I implemented Microsoft Clarity to track user behavior through session recordings and heatmaps. This quantitative data identified friction points in the contract upload flow that were invisible during interviews, allowing for precise, data-driven UI refinements.

Iteration 1

Added severity levels

(🟢🟡🔴)

Iteration 2

Added negotiation

templates

Iteration 3

Added benchmark

data context

Technical Strategy

Smart Caching. Implemented a caching layer that reduced redundant API calls by 60%, significantly lowering costs.

Streaming Responses. Used streaming for AI responses to ensure the app felt fast and responsive on mobile networks, even when processing complex analysis.

Graceful Degradation. Robust error handling ensures that if one AI model fails, the user is guided helpfully rather than seeing a crash.

The Result

"I almost signed a deal that would've blocked me from 3 other brands for 6 months. This tool caught it in 20 seconds."

Impact

3 users negotiated

better terms

By focusing on a mobile-first, conversation-driven experience backed by a multi-model AI architecture, SponsorBase successfully bridged the gap between complex legal protection and the on-the-go workflow of modern creators.

Tech Stack

React / Next.js

Tailwind CSS

Supabase / Vercel

Dovetail (Qualitative)

MS Clarity (Quantitative)

Design

Figma (37 artboards)

4.6/5 Usability Score

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