01
Make the system explicit.
Models and prompts are components of larger systems. Their relationships should be represented, inspectable, and testable.
Eldritch, Inc.
We build software that makes AI systems better.
Eldritch builds infrastructure for constructing, evaluating, and optimizing AI systems.
Our first product
Azathoth
AI workflows should be able to learn how to become better AI workflows.
Azathoth is an open-source framework for constructing, evaluating, and optimizing multi-model AI systems across quality, reliability, latency, and cost.
01
Construct
Compose models, prompts, tools, context, and multi-step workflows as explicit software systems.
02
Evaluate
Measure behavior against explicit goals using repeatable experiments and evidence.
03
Optimize
Search for better tradeoffs between capability, quality, reliability, latency, and cost.
What we believe
AI systems should be engineered, not guessed at.
Modern AI applications combine models, prompts, tools, retrieval, memory, context, and multi-step workflows.
The number of possible configurations quickly exceeds what an engineer can reasonably explore by hand.
We build systems that measure what works—and use that evidence to improve what comes next.
Our approach
Treat AI behavior as an engineering problem.
02
Measure before optimizing.
Improvement requires evidence. Evaluation should be built into the architecture rather than added after deployment.
03
Optimize the whole system.
The best model is not always the best system. Quality, reliability, latency, cost, and capability belong in the same engineering conversation.
Eldritch, Inc.