01 —
LLM Applications & AI Agents
Raise the accuracy of LLM-powered applications by tuning prompts, context pipelines, tool use, architectures, model selection, and more.
02 —
RAG Pipelines
Evolve retrieval strategies, chunking parameters, and ranking logic against real query patterns. In our benchmarks, the biggest wins came from changing the pipeline, not the prompt.
03 —
Rules Engines
Compared to traditional AI systems, rules engines are predictable, explainable, and auditable, but hard to improve. We use large datasets and AI to iteratively train your rules engine, expanding coverage while evals catch regressions.
04 —
Document or Website Processing
Multi-step text processing pipelines often include extraction, scoring, editing, classification, reasoning, and more. Define an objective metric and CodeEvolver can continuously improve it against your data.
05 —
Continuous Re-Optimization
Every model release changes what the optimal system looks like, and new customers bring new requirements and failure cases. Automatically re-run the engine whenever models, requirements, or data drifts, and keep your edge without a major engineering effort.