Results at a glance
Chat p95 latency
18 ms
Throughput
500 tok/s
TCO savings
72%
Availability
99.9%
Infrastructure
K8s vs Bare-metal
Inference
Triton/ORT vs vLLM
Vector Store
FAISS vs Milvus
GitOps
ArgoCD/Flux
Decisions & Trade-offs
Every sovereign AI deployment requires critical architectural decisions. Here are the key trade-offs we navigate:
Cloud vs On-Premise
Trade convenience for control. On-prem means full data sovereignty but requires infrastructure investment.
Model Size vs Latency
Larger models offer better accuracy but impact response time. Right-sizing is critical for production SLAs.
Batch vs Streaming
Batch processing maximizes throughput; streaming minimizes time-to-first-token. Choose based on user experience requirements.
GPU Utilization vs Cost
Higher GPU utilization reduces TCO but may increase queue times during peak load.
Key KPIs
Production-grade AI infrastructure requires monitoring these critical performance indicators:
Latency
p50: <10 ms/token
p95: <20 ms/token
p99: <35 ms/token
Throughput
Requests/sec: 200+
Tokens/sec: 500+
Concurrent: 50+
Reliability
Uptime: 99.9%
MTTR: <5 min
MTBF: >720 hrs
Efficiency
GPU Util: 80%+
Memory Util: 75%+
TCO vs Cloud: -72%
Real-World Deployments
Production sovereign AI implementations across industries.
Finance
Knowledge assistant for compliance-heavy banking operations