Abstract
The present disclosure relates to a system for anticipatory execution in chatbot systems that addresses latency caused by idle compute time while users type queries. The system includes a speculative query firing framework configured to initiate shadow runs and proactive tool calls during user typing. Multi-modal triggers monitor user behavior and session context to fire speculative requests, including temporal triggers for detecting stable partial strings, semantic triggers using a completion model to predict query completion, and intent triggers for recognizing clear intent patterns. A parallel shadow queue routes shadow requests to a lowpriority execution queue for performing shadow runs and eager hydration of heavy signals. A similarity engine evaluates a delta between a speculative query and a final submitted query, injecting shadow-fetched context when similarity exceeds a threshold. The system reclaims idle compute time during human typing to reduce perceived latency.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Jain, Rohit, "Speculative Query Firing for Anticipatory Execution in Chatbot Systems", Technical Disclosure Commons, (August 06, 2026)
https://www.tdcommons.org/dpubs_series/11281