Benchmarking Framework
Standardized evaluation across multi-turn conversations of varying depth, domain complexity, and instruction density. Measuring continuity, coherence, and factual consistency.
MethodologyResearch
Every design decision is backed by systematic benchmarking across real-world long-conversation scenarios.
Standardized evaluation across multi-turn conversations of varying depth, domain complexity, and instruction density. Measuring continuity, coherence, and factual consistency.
MethodologyAutomated scoring pipelines combining LLM-as-judge evaluation with deterministic metrics for retrieval precision, token efficiency, and response quality.
EvaluationMeasuring how effectively context is preserved across 50+, 100+, and 200+ turn conversations. Testing instruction adherence decay rates with and without orchestration.
TestingStudying the precision-recall tradeoffs in conversational memory retrieval. Identifying optimal strategies for fragment selection and context window composition.
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