And you cannot prove it isn't.
Local-first AI infrastructure. Sovereignty is Strategy.
Serving law firms, medical practices, and finance/compliance entities across Washington & Oregon. Remote engagements available nationally.
Most organizations adopting AI are renting someone else's infrastructure. The model runs on a third-party server. The data travels over their network. The inference path is outside your control boundary. The terms of service can change. The API can be deprecated. The data retention policy can shift after a merger.
For organizations handling attorney-client privileged material, protected health information, deal data, or fiduciary-bound financial records, that architecture is a liability that doesn't show up on the budget line.
We build the alternative: AI infrastructure where the model, the data, and the inference path all stay inside your premises.
Local-first AI stacks designed for organizations that cannot send sensitive data to third-party inference endpoints. Model selection, hardware sizing, inference runtime (Ollama / vLLM), RAG pipeline, access controls, audit logging, air-gap tier design, and team training — all inside your control boundary.
GPU and inference stack tuning so the infrastructure doesn't run hot and expensive. We profile actual load, find VRAM saturation points, calibrate inference parameters, and sequence long-context generations to avoid heat buildup. Documented before/after thermal metrics.
A local writing assistant that produces first drafts in your organization's voice, grounded in your own documents, with the output dropped into your existing workflow. The analysis itself never leaves your infrastructure. For firms that need writing capability without feeding a third-party algorithm.
Discovery fees credited in full toward any implementation engagement booked within 90 days. Bundling two or more service lines waives discovery fees for the second and third line.
SYN-AUDIT-001 — Thermal Logic Optimization Audit on production hardware (NVIDIA RTX A2000, 8GB):
A sovereign inference stack running hot because nobody tuned the logic to the iron. The fix: adjust n_gpu_layers from 35 to 32, switch to "Cold Logic" parameters (Temp 0.7, Top-P 0.9). No new hardware. No vendor contract. Same stack, running at the level it was built for.
1. 20-minute architecture review. We walk through your current setup — inference pipeline, data flows, hardware inventory. No pitch deck. Just the diagram of what local-first would look like for your organization.
2. Discovery phase. 5–10 business days (depending on service line). We map your data flows, audit your hardware, assess your compliance posture, and produce a written assessment with a go/no-go recommendation and a scoped build estimate.
3. Implementation (if you proceed). Built, configured, tested, documented, and handed off with team training. You own the hardware and the system. We specify and validate — you purchase. No markup.
The first step is a 20-minute conversation. We'll walk through what you have today and what a local-first architecture would look like. No pitch deck. No commitment. Just the diagram.