01
Direct Access
You talk directly to engineers who inspect the system, name the tradeoffs, and do the work.
What We Solve
Make AI features economically durable.
Response time, serving efficiency, and infrastructure discipline decide whether the feature survives scale. We work where the waste hides: low GPU utilization, oversized models, weak routing, poor batching, and missing caches.
That usually shows up as slow p95 and p99 that damage product experience, rising GPU spend with weak utilization and poor serving choices, autoscaling drift that increases cost without stability, and opaque serving stacks with weak profiling and cost visibility.
What You Get
- Serving architecture review for latency, throughput, and cost behavior
- Optimization plan across routing, batching, caching, and hardware placement
- Profiling visibility for tokens, requests, queues, and utilization
- Rollout strategy for safer scaling and performance regression control
- Cost model tied to product traffic and business constraints
Coverage and Delivery
Serving Stack
- Model serving architecture and engine selection
- Batching, caching, concurrency, and queue behavior
- Quantization and runtime optimization paths
- Model routing, fallback logic, and request shaping
Performance and Cost
- GPU and CPU placement strategy
- Latency breakdown and profiling methodology
- Utilization analysis and scaling policy review
- Budget-aware recommendations for production traffic
Typical Outputs
- Serving and routing architecture map
- Latency and cost bottleneck analysis
- Optimization roadmap with sequencing
- Monitoring and regression guard recommendations
Business Fit
- AI products approaching production scale
- Teams with rising inference spend and unstable response times
- Platforms where margins depend on serving efficiency
- Organizations that need AI capability without runaway infrastructure cost
Why Teams Choose SToFU Systems
Senior-led delivery. Clear scope. Direct technical communication.
02
Bounded First Step
Most engagements start with a review, audit, prototype, or focused build instead of a giant retained scope.
03
Evidence First
Leave with clearer scope, sharper priorities, and a next move the business can defend under scrutiny.
Delivery
Senior-led
Direct technical communication
Coverage
AI, systems, security
One team across the stack
Markets
Europe, US, Singapore
Clients across key engineering hubs
Personal data
Privacy-disciplined
GDPR, UK GDPR, CCPA/CPRA, PIPEDA, DPA/SCC-aware