Small, fast models for the decisions inside your request path
PITCHED AT THE LONDON NIGHT ON 18 AUGUST 2026
Classifying a message or gating an agent action is too nuanced for hard-coded rules and too slow and costly to send to a live language model on every request. Sparkient trains task-specific models that answer in milliseconds and can run at the edge.
There is a category of decision that sits awkwardly between engineering approaches. Rules become brittle, a live language model adds latency, cost and a runtime dependency you cannot remove, and training a bespoke model needs labelled data and someone to maintain it.
Sparkient makes that middle option cheap: small task-specific models, generated and served, fast enough to sit inside a production request path and portable enough to run offline at the edge.
These founders pitched at the same startup events. The room is usually the reason people find each other.