Summary
Overview
An enterprise AI middleware layer collapses semantically equivalent agent tasks into one shared execution so organizations can cut duplicate compute, API calls, and backend load without modifying individual agent code.
Abstract
Technical Abstract
Canonical task fingerprints are produced through SQL normalization and transformer-based semantic encoding. A non-resetting admission window gathers clustered sister tasks before execution, while exact hash matching and approximate vector search identify duplicates and near-duplicates. Matching requests are subscribed to a single Shared Execution Unit, and the final result is fanned out to all originating agents through registered callbacks, with distributed locking and deduplication metrics supporting multi-node deployments.
Search Context
SEO Keywords
semantic deduplication patent, enterprise agent patent, multi-agent middleware patent, shared execution patent, autonomous AI agent patent
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