Solutions & Platforms
Scalable systems engineered for resilience, validation, and ownership.
Hop develops intelligent systems at scale – reliably, reproducibly and responsibly.
We engineer robust machine learning systems built to deploy seamlessly in the cloud, on-premises, or at the edge. When off-the-shelf infrastructure falls short, we construct custom compute environments to push the boundaries of AI research. As a platform-agnostic team with deep expertise across AWS, GCP, and Azure, we obsess over scale, latency, concurrency, and resilience so your models run flawlessly in the real world.
Featured Case Study
Building Trust with LLMs: Balancing Product with Potential
As large language models started seeing widespread commercial use, Harvard Business Publishing recognized that LLMs stood poised to transform the publishing industry. HBP didn’t yet know what was possible from a product perspective, they weren’t sure how to get started, and they didn’t know what they needed to know to implement successfully – they were facing true uncertainty. With a trusted, high-value brand, HBP stands to lose a lot from associating an ineffective – or worse, toxic – chatbot with their name. Not only did they have to chart a course through rapidly changing waters, they had to do it in a way that avoided any potential for a negative brand experience. They needed trusted partners to navigate this space.