About ISWIZ AI
Built for the Operators, Not the Observers
ISWIZ AI was founded in San Antonio, TX by practitioners who spent years watching enterprise AI projects fail — not from lack of technology, but from lack of structure. We build the ontological foundation that makes AI reliable, then deploy agents that act on it.
Our Mission
Make AI Trustworthy for Regulated Industries
Most AI vendors sell you a model. We sell you a system — one that understands your business before it touches your data. Our mission is to make AI automation as reliable and auditable as the professionals who use it: attorneys, surgeons, accountants, engineers. That means ontology-first design, air-gapped infrastructure when required, and agents that cite their reasoning.
How We Work
Four Principles We Don't Compromise On
Ontology Before Agents
We never deploy an agent into a business we haven't modeled. Every engagement begins with a structured mapping of your objects, relationships, and processes. The ontology is the contract between your business and the AI.
Compliance Is Structural
HIPAA, CJIS, and SOC 2 compliance cannot be bolted on after deployment. We design it into the data model, the inference pipeline, and the audit log from day one — not as a checklist, but as an architectural constraint.
Local When It Matters
For workloads where data cannot leave the building, we run everything on-premise on NVIDIA DGX Spark Grace Blackwell. No cloud dependency, no data egress, no third-party model access to your client files.
Tiered Reasoning, Fully Logged
We route each task to the right model for the job: on-premise inference for sensitive, latency-critical work, frontier cloud models for complex reasoning. Every tool call an agent makes is logged and reviewable — who, what, when, and what it returned. No black boxes, no hidden reasoning steps.
Infrastructure
NVIDIA DGX Spark Grace Blackwell
Our research and production infrastructure runs on the NVIDIA DGX Spark Grace Blackwell platform — a desktop supercomputer delivering up to 1,000 TOPS of AI performance in an air-gapped, on-premise form factor. We use it for local LLM inference for sensitive workloads, with tiered routing to frontier cloud models for tasks that need deeper reasoning. For clients in regulated industries, this means enterprise-grade AI with zero data egress.
Platform
NVIDIA DGX Spark Grace Blackwell
Performance
Up to 1,000 TOPS
Deployment
Air-gapped, on-premise
Compliance
HIPAA · CJIS · SOC 2
Inference
Local + tiered cloud routing
Audit
Full tool-call provenance log
