AI Systems Built forthe Real World
We design, build, and deploy AI systems that don't just demo well — they run fast, reliably, and at scale.
Specialized in High-Performance AI Deployment
Our expertise sits at the intersection of:
- GPU-accelerated inference
- Model optimization (quantization, pruning, TensorRT-LLM–style graph simplification)
- End-to-end deployment pipelines for production environments
- Integrating GenAI into existing enterprise and legacy stacks
- Safety-critical, latency-sensitive applications
- Large-scale on-prem and multi-cloud GPU infrastructure
If you need AI that works under real constraints — speed, memory, cost, reliability — that's our lane.
What We Deliver
Systems that meet strict latency requirements
Cost-optimized GPU deployments
Accurate, robust models tailored to your environment
Clean integration with your existing workflows
Production-grade reliability and observability
Why You & AI
AI that works under real constraints
No buzzwords. No "magic AI button." Just rigorous engineering focused on speed, memory, cost, and reliability.
Low-Latency Systems
Sub-100ms inference goals with optimized prefill/decode separation and token throughput engineering.
Cost-Optimized GPU Usage
Right-sizing GPU deployments through intelligent batching, scheduling, and resource management.
Accurate & Robust Models
Models tailored to your specific environment with comprehensive evaluation harnesses and regression testing.
Clean Workflow Integration
Seamless integration with existing enterprise systems, ERPs, CRMs, and internal tools.
Production Reliability
Robust fallbacks, comprehensive monitoring, and observability for zero-downtime operations.
Our Approach
From assessment to production
A systematic approach to building AI systems that meet strict performance requirements while integrating cleanly with your existing infrastructure.
Phase 1
Assessment & Architecture
- Use-case evaluation and feasibility analysis
- Model + GPU resource planning
- Architecture design for scalable deployments
Phase 2
Optimization & Build
- Model quantization (INT8, FP8, FP16)
- Graph cleanup and operator fusion
- Custom kernels and performance tuning
Phase 3
Deploy & Monitor
- Containerization + GPU scheduling
- CI/CD pipelines for model updates
- Logging, metrics, and model-health monitoring