Technical Publications

DF Memory — Three-Tier Persistent AI Memory

Proven and demonstrated DF Memory engineering by Agentic AI Systems, featuring persistent RAG, TOC.md knowledge navigation, ontology, evidence-based knowledge promotion and DF Smart Memory AI-agent-coordinated retrieval.

A centralised memory architecture enables authorised distributed AI nodes to retrieve and reuse organisational knowledge independently of individual language models.

Author: Reddy (Eddie) Jamisola
Organisation: Agentic AI Systems
Document Number: 202610-AASPUB-0002

Read / Download Publication 0002 (PDF)

Dynamic GPU Compute Mode Switching, Model Switching and Multi-Inference

Proven single-GPU and multi-GPU AI execution, concurrent multi-model inference and dynamic compute resource allocation, developed by Agentic AI Systems.

The publication presents demonstrated configurations including single-GPU multi-inference, multiple models on one GPU, multi-GPU model execution and flexible allocation of five GPUs between shared-model and independent-model workloads.

Author: Reddy (Eddie) Jamisola
Organisation: Agentic AI Systems
Document Number: 202610-AASPUB-0003

Read / Download Publication 0003 (PDF)

Consumer GPU Power-Curve Optimisation and Active Thermal Management

Experimental observations of 70–75% GPU power limits with approximately 1–5% performance degradation across selected NVIDIA and AMD consumer GPUs.

The research examines NVIDIA GeForce RTX 3080 and RTX 3090, and AMD Radeon RX 6800 graphics cards, including silicon-lottery variability, 100% fan operation during compute workloads and a 30-second post-compute cooling period.

Results may vary between GPU models and individual chips, even within the same model family.

Author: Reddy (Eddie) Jamisola
Organisation: Agentic AI Systems
Document Number: 202610-AASPUB-0004

Read / Download Publication 0004 (PDF)

DF Nexus: Unified Agentic AI Workflows Across Edge, Home Lab, Distributed GPU and Cloud Infrastructure

DF Nexus is the foundational distributed agentic AI architecture developed by Agentic AI Systems, connecting smartphones, laptops, CPU-based edge devices, home laboratory GPU infrastructure, distributed AI nodes and cloud computing into one coordinated execution environment.

The architecture supports CPU-only, CPU+iGPU and CPU+dGPU processing, small 1B and 4B language models, speech-to-text, text-to-speech, single-GPU compute-mode switching, model switching, multi-inference and dynamic multi-GPU resource allocation.

WireGuard and Tailscale provide private encrypted connectivity between authorised AI nodes, while cloud VPS services coordinate workflows, persistent memory and resource selection. Elastic GPU compute and authorised frontier-model APIs extend available processing capacity.

Author: Reddy (Eddie) Jamisola
Organisation: Agentic AI Systems
Document ID: 202610-AASPUB-0005

DF Codex V1.1 — Engineering Persistent AI Knowledge Through Vector-Based Semantic Retrieval

DF Codex is an incremental AI-assisted source-code analysis system developed by Agentic AI Systems, incorporating intelligent Smart Archive, repository snapshots, historical checkpoints and recovery mechanisms.

This publication explores integration with DF Memory Ontology Edition and vector-based semantic retrieval using local ONNX inference and 384-dimensional embeddings. It distinguishes operationally accepted V1 capabilities from V1.1 development and validation.

Author: Reddy (Eddie) Jamisola
Organisation: Agentic AI Systems
Document ID: 202610-AASPUB-0006

AIGENESIS — Five-GPU AI Inference Architecture, Dynamic Model Switching and Multi-Inference

A comprehensive engineering publication examining the AIGENESIS five-GPU AI compute platform, including motherboard, CPU, system memory, GPU hardware, PCIe topology, model deployment and inference configurations.

The paper documents nine GPU and model execution modes, concurrent inference benchmarks, multi-agent workload orchestration, model switching, CPU/RAM offloading, performance observations, system limitations and experimental validation results.

Author: Reddy (Eddie) Jamisola
Organisation: Agentic AI Systems
Document ID: 202610-AASPUB-0007