Solutions · Edge AI
Local inference and small language models
On-device and perimeter-bound inference with a named trust boundary. There is no default vendor API for regulated inputs.
When local SLMs fit
We use on-device or perimeter-bound models when the input cannot leave the customer environment, when a third-party API would create a custody problem, or when latency and offline operation matter more than a hosted frontier model. If a hosted API is the honest fit, we say so.
Quantization and grammar, stated honestly
Quantization, constrained decoding, and deterministic grammars are engineering choices with trade-offs. We will name the model class, the hardware envelope, and what the system will not do. We do not promise certified clinical or weapons-grade accuracy from a marketing page.
Engagement model
Work is scoped in writing: architecture, evaluation, and implementation. We do not list a capability we cannot show. Government R&D that uses these techniques is contracted as services, not as a product SKU.
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