Findnlink

The heart of FindnLink is a proprietary seven-step pipeline that turns raw text descriptions, portfolio items, and behavioral data into a dynamic compatibility score. Each stage is optimized for SEO discoverability, so every public portfolio also becomes a high-ranking landing page.

Semantic Brief Parsing
When a client posts a brief, a fine-tuned GPT-4o variant breaks the text into intent clusters—tone, deliverables, industry, budget sensitivity, timeline, collaboration style. The model was trained on 1.7 million successful briefs, giving it an F1 intent-accuracy score of 0.94.

Portfolio Vectorization
Creative assets (images, videos, code repos, Figma files) are converted into 2 048-dimensional vectors via a hybrid CLIP + ResNet ensemble. These vectors capture both visual style and technical complexity, enabling the engine to understand that a neon-soaked 3-D animation portfolio is a stronger fit for a gaming launch than a pastel brand-guideline project.

Reputation Graph Mining
FindnLink continuously crawls public sources such as LinkedIn recommendations, GitHub commits, Dribbble likes, and Behance case studies. Each citation is weighted by source authority and recency, creating a decayed-authority score that prevents yesterday’s viral post from dominating today’s search.