Resources
Proof points
A few public projects and case studies. More are under NDA.
These are public projects we can talk about. Commercial work is under NDA, but references and architecture reviews are available after an intro call.
VCA Inference Cache
Problem: High-throughput LLM serving workloads waste compute on repeated prompt prefix processing.
Approach: Built a key-value cache layer optimized for inference workloads, with eviction policies tuned for transformer attention patterns.
Outcome: Reduced redundant computation for repeated prompt structures; cache hit rates scale with conversation length and batch size.
Apollo Mission Simulator
Problem: Historical space-mission simulations are either toy models or closed-source.
Approach: Combined a 3D Apollo command module with the real yaAGC guidance computer and Keplerian orbital mechanics in the browser.
Outcome: A runnable, inspectable simulation that proves we can bind real embedded systems, physics, and 3D rendering in a single web app.
Merlin LLM Router
Problem: Model selection is usually static, so latency and cost suffer on heterogeneous request traffic.
Approach: Built a multi-provider router that picks the cheapest capable model per request using sub-millisecond reinforcement-learning scoring.
Outcome: Lower per-request cost without sacrificing quality; routing decisions improve as request patterns change.
DGX Spark Memory Planner
Problem: Developers waste hours tuning memory and quantization settings for NVIDIA DGX Spark workloads.
Approach: Created a unified memory-budgeting and quantization advisor that models batch size, sequence length, and precision trade-offs.
Outcome: Faster, less error-prone model sizing; fewer out-of-memory failures during experimentation.
Ready to ship?
Want to go deeper? Tell me what you are building and I will reply within one business day.
hello@vibecodingagency.com