open source · ai infrastructure
Infrastructure for the
age of intelligent systems
The wave of capable foundation models has created a new problem: the infrastructure to actually use them well doesn't exist yet. Not at the level that matters — evaluation, observability, and the runtime systems that let models operate reliably in production. That's what we're building.
Open source, at every layer of the stack
Aevyra is building the missing layer between foundation models and production — the infrastructure that makes them actually work.
Everything is open-source. No wrappers, no shortcuts.
See the projects →From the Blog
Recent Projects
Origin
Failure attribution. When an agent fails, Origin reads the trace and tells you which span caused it — with severity, confidence, and a fix type pointing to the exact layer that needs repair.
Witness
Agent tracing. Records every step of an agent pipeline — inputs, outputs, timing, and how steps relate to each other — in a single structured object. Zero runtime dependencies.
Reflex
Agentic prompt optimization. Reflex takes your dataset and prompt, runs evals, diagnoses why scores are falling short, and rewrites the prompt — iterating until it converges.
Verdict
LLM benchmarking. Run your prompts across any model, score responses with pluggable metrics, and get a side-by-side comparison. The foundation for model selection and knowing whether your fine-tuning is working.
Forge
Autonomous vLLM deployment optimizer. Give it a model, a GPU, and a workload trace — it tunes your serving config overnight and delivers a deployment recipe that beats hand-tuned defaults.