The context layer you never have to build
Twigg is a stateful API for calling LLMs. Instead of rebuilding and resending your whole conversation on every request, you create a chat once and send only the next event. Twigg holds the state: it fits context to the target model's schema, compacts or truncates when it runs long, and routes the call. Control tool schemas, system prompts and context windows from the dashboard, and track usage and billing. Build anything from personal agents to enterprise apps. You never manage context again.
Twigg is a stateful API designed for interacting with large language models (LLMs) by maintaining conversation context, allowing developers to send only the next event in a chat. It offers tools for managing schemas, prompts, and usage tracking, facilitating the development of applications from personal agents to enterprise solutions.
Scored deterministically. Only candidates that fire a story trigger are sent to a model, so this one has no written angle.
Gaps in our data, not findings about the product. Their weight is redistributed across the 5 we did measure.
A source that found nothing is a measurement. A source that has not run is a gap. Neither means the launch lacks the thing.