How Searchable ships customer-requested features in 30 minutes on Vercel

Searchable, which helps brands track and improve how they appear across AI search engines such as ChatGPT, Perplexity, and Claude, reports a 5x increase in development velocity while running on Vercel. The company has processed more than 100 billion tokens and says it can ship customer-requested features in as little as 30 minutes.

A large part of that speed comes from Vercel’s AI Gateway. Searchable avoids implementing model SDKs itself and does not handle API key rotation, so model access and credential management sit behind the gateway rather than in application code. That removes a class of integration and ops work that usually slows AI product teams.

For engineers and builders, the numbers point to a concrete workflow: less time on provider wiring means more time on product surface. Shipping a customer request in 30 minutes is only plausible if model plumbing is already standardized and not renegotiated per feature. The 5x velocity claim is the operational signal behind that claim, not a vague productivity slogan.

Searchable sits in a crowded AI-search visibility space, where brands care how they show up in answers from ChatGPT, Perplexity, Claude, and similar engines. Competing on analytics and recommendations for that surface only works if the product can absorb customer feedback quickly. Infrastructure that collapses model integration cost is a direct lever against slower competitors still maintaining per-provider SDKs and keys.

What to watch next is whether that 30-minute path holds as feature requests grow more complex, and whether token volume past the 100-billion mark stays manageable without reintroducing custom model-layer work. Teams building similar multi-model products should treat AI Gateway-style abstraction as a measured alternative to owning every SDK and rotation path in-house.