AI-Powered Meme Search Engine
ML Challenge / Multimodal AI
Case study

AI/ML / Multimodal Search

Prototype

Dhaka, Bangladesh

AI/ML / Multimodal Search · Detailed breakdown

Project overview

Why this build
mattered.

Semantic image search system using CLIP model for text-to-image matching across meme datasets.

Snapshot

ML Challenge / Multimodal AI / Prototype / Python, Sentence-Transformers, CLIP

PythonSentence-TransformersCLIPPyTorchMultimodal AI
CLIP ViT-L-14
model
Semantic Similarity Matching
accuracy
Multi-format Support
formats

System views

Screens and
surfaces

What shipped inside

Key features
and modules

The same motion language from the main homepage carries through here, but the content turns toward the architecture, workflow, and operational details that made this project useful.

Highlight

Integrated Sentence-Transformers CLIP ViT-L-14 model

Highlight

Multi-format image support (PNG, JPG, WebP)

Highlight

Semantic similarity scoring with cosine similarity

Delivery summary

Build notes

Project essentials

AI-Powered Meme Search Engine

ML Challenge / Multimodal AI · Prototype · AI/ML / Multimodal Search

Integrated Sentence-Transformers CLIP ViT-L-14 model1
Multi-format image support (PNG, JPG, WebP)2
Semantic similarity scoring with cosine similarity3

Let's build something worth building.