Research Papers

Explore our technical publications, active research files, and architectural drafts.

A. Vance, L. Thorne, S. Patel[paper.neural_multi_agent]
Active Research

Neural Architecture for Multi-Agent Systems

Proposing a state-routing graph model for multi-agent systems, prioritizing deterministic path selection and failover states during concurrent runs.

S. Chen, R. Gomez[paper.knowledge_graph_scale]
Published

Scalable Knowledge Graph Construction

Detailing chunk extraction frameworks using custom parser schemas to build reliable, searchable entity graphs from enterprise PDF logs.

L. Thorne, J. Miller[paper.doc_understanding_layout]
Published

Efficient Document Understanding Models

Methods for training token-efficient layout encoders, lowering layout analysis times by 40% while preserving optical character details.

P. Nair, K. Zhao[paper.telemetry_anomaly_realtime]
Active Research

Real-time Anomaly Detection Framework

Evaluating telemetry logs using lightweight encoder networks to flag system connection anomalies in under 5 milliseconds.

A. Vance, S. Chen[paper.federated_learning_onprem]
Experimental

Federated Learning for Enterprise AI

Mocking model updates across isolated data nodes, keeping proprietary data within on-premise partitions while syncing weights.

R. Gomez, L. Thorne[paper.conv_orchestration_state]
Published

Conversational AI Orchestration

Outlining state-machines that coordinate conversation turns, routing complicated user intents to correct specialist agents.