What we’ve actually shipped
Frameworks, architectures, and operational playbooks — tested against real production traffic.
Agentic Routing for Enterprise
Your traffic isn't one shape. Most requests are classification or extraction that a cheap model handles at a fraction of the price. Route on that difference and spend drops by 60–80% with no movement in your quality metric. Here's the architecture, including the two failure modes we hit first.
SPIFFE/SPIRE in AI Workload Identity
An inference server might live ninety seconds before it's replaced. You can't hand it a certificate. SPIFFE/SPIRE gives it a cryptographic identity it can prove in that window, and it works with vLLM and LiteLLM without touching your application code.
Observability for Agentic Pipelines
One user request can fan out into three tool calls, two model calls and a synthesis step. When it goes wrong you need to see the whole shape at once, not four dashboards. This is the span structure that makes that possible.
Research Q&A
Ask a question about our work. Answers are grounded in what we’ve actually shipped, with sources.
Try asking about
Ask a question about our research to get a grounded answer with citations.
Routing
Fallback chains, model selection, circuit breakers
SPIFFE
Workload identity for ephemeral AI containers
Observability
Span trees, latency budgets, Langfuse
Security
LLM red-teaming, prompt injection, eval harnesses