The Engine Room: Edge-Compute Architecture

Current Pipeline & Architecture Our internal pipelines are currently built on localized AMD Strix Halo architecture. We strictly utilize Llama 3.3:70B for logical reasoning, Kokoro TTS for voice synthesis, and Krea 2 for visual generation. Because our bespoke LanceDB RAG/SAGE stack is inherently model and hardware agnostic, we are fully capable of deploying whatever configuration best fits our client's existing edge-compute capabilities.

The Foundry Pivot (12B Fine-Tuning) To optimize edge deployment for our clients, Darkline Media leverages high-end cloud compute nodes for short, intense bursts. We utilize these nodes to educate customized 12B models via highly curated JSONL datasets. This hyper-education burns away generic prose and forces the model into specific operational cadences before we deploy them onto localized hardware.

The Hardware Horizon While our bespoke LanceDB stack deploys seamlessly on current enterprise architectures, our operational horizon is heavily focused on next-generation NVIDIA edge hardware. Migrating our enterprise clients to 128GB unified-memory architectures—specifically the upcoming NVIDIA RTX Spark enterprise notebooks and scalable GB300 compute nodes—will allow DLM to run massive 70B–120B parameter models natively. This completely eliminates cloud friction and maximizes unhackable, localized edge-compute capabilities for our most secure sectors.