Question 1

What exactly does 'Hardware-Software Co-Design' mean for our AI models?

Accepted Answer

It means we do not treat AI as a standalone software wrapper. We design custom neural network graphs specifically optimized to map directly onto domain-specific silicon, system-on-chip (SoC) architectures, and advanced robotics pipelines. This maximizes compute efficiency, dramatically reduces power footprint, and provides highly deterministic execution.

Question 2

How do your sub-100MB Small Language Models (SLMs) run offline on the edge?

Accepted Answer

We utilize advanced custom compiler toolchains, model weight pruning, and low-bit quantization. This compresses large-scale networks to fit natively within resource-constrained edge memories (sub-100MB footprint) without losing factual precision, enabling zero-latency local inference without any internet connection.

Question 3

Can we license Renitiate's patented spatial computing or digital human frameworks?

Accepted Answer

Yes. Renitiate licenses its published core modular frameworks designed for real-time spatial digital twin integration, real-time microsecond response loops, and digital human dialogue. These frameworks are built to run natively on edge systems, bypassing expensive cloud APIs.

Question 4

How do you handle private enterprise data security and compliance?

Accepted Answer

Because our engineering focus centers on edge intelligence and domain-isolated SLMs, your operational datasets never leave your private local infrastructure. We specialize in 100% air-gapped, on-premise execution, ensuring full compliance and IP custody.

Question 5

What is your delivery pipeline for custom systems engineering?

Accepted Answer

We follow a rigorous, peer-reviewed engineering lifecycle: Algorithmic Feasibility & Silicon Mapping, Co-Design Blueprints, Custom Graph Kernel Compilation, Hardware-in-the-Loop Validation on target SoCs, and Edge Telemetry tuning.

Question 6

How do we get started with Renitiate's R&D engineering lab?

Accepted Answer

Simply fill out our contact form selecting your targeted deep-tech focus track (Custom AI Product Engineering, Hardware/SoC Co-design, or Framework Optimisation). Our engineering team will review your hardware requirements and schedule a technical consultation.

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