When Off-The-Shelf Fails: Signs You Need Custom Models
Off-the-shelf vision APIs are great — until they aren't. When accuracy plateaus, domain drift creeps in, or edge cases pile up, even the best plug-and-play model can become a bottleneck. In this post, we unpack the red flags that signal it's time to go custom and share a phased roadmap to help you transition smoothly — without blowing deadlines or budgets. Whether you're struggling with OCR misreads, misclassified logos, or brittle workarounds, learn how bespoke models can future-proof your computer vision stack.
Transfer Learning Hacks for Rapid Image Models
Transfer learning has revolutionized the way we build image models — especially when time, data or compute power is limited. In this beginner-friendly guide, you'll learn how to fine-tune pre-trained giants like VGG, EfficientNet and CLIP to achieve fast, accurate results on small datasets. From smart layer freezing to real-world use cases in retail, agriculture and content moderation, we’ll show you how to build powerful vision systems without starting from scratch. Perfect for startups, solo devs or any team looking to do more with less.