07R&D & INNOVATION

ARKLINTECH LAB

The future-facing engineering layer. We explore emerging protocols, autonomous agents, and hardware-accelerated edge inference with honest, clear state labels.

LAB-01PrototypesIN DEVELOPMENT

Self-Healing Financial Ledger Agent

Autonomous AI agent monitoring double-entry bookkeeping ledgers for automated anomaly mitigation.

Investigating autonomous background agents capable of auditing multi-gateway banking webhooks, identifying non-matching transaction traces, and drafting correction records for human review.

TECHNICAL THESIS:

Can localized LLMs with constrained SQL toolchains reduce financial reconciliation audit time by 90% while maintaining 100% deterministic safety?

AUTONOMOUS AGENTSFINANCIAL LEDGERSANOMALY MITIGATION
Benchmarking deterministic SQL mutation guards against synthetic accounting discrepancy benchmarks.
LAB-02ExperimentsPROTOTYPE

Zero-Cloud Offline State Mesh

Peer-to-peer CRDT state synchronization across local POS terminals without centralized LAN routers.

Prototyping Conflict-Free Replicated Data Types (CRDTs) over BLE and localized WebRTC mesh networks for zero-infrastructure restaurant and warehouse operations.

TECHNICAL THESIS:

Evaluating merge latency and partition recovery when 10+ operational handhelds exchange state without internet or local WiFi router dependency.

CRDTLOCAL-FIRSTOFFLINE MESHWEBRTC
Prototype testing with Electron client nodes simulating intermittent packet drop scenarios.
LAB-03ConceptsCONCEPT

Dynamic SOP Reasoning Engine

Translating natural language standard operating procedures into executable workflow state machines.

Conceptual architecture for taking company policy PDFs and automatically generating typed BPMN state machines with validation test suites.

TECHNICAL THESIS:

Validating whether AST compilation techniques combined with LLM semantic parsers can eliminate manual workflow setup for complex operations.

SOP TO CODESTATE MACHINESAST COMPILER
Theoretical schema mapping and AST grammar definitions.
LAB-04Emerging PlatformsEXPLORING

Sub-10ms Edge Inference Appliance

Hardware micro-appliance running quantized vision and decision models at the operational edge.

Exploring low-power NPU hardware acceleration for real-time kitchen item inspection and physical inventory tracking without cloud streaming bandwidth.

TECHNICAL THESIS:

Assessing inference yield and thermal stability of 3B parameter quantized models on localized edge appliances.

EDGE HARDWARENPU INFERENCECOMPUTER VISION
Evaluating silicon developer kits and ONNX Runtime NPU execution providers.