RESEARCH
More from
every computation.
Model agnostic by design. The Transductor makes model calls more efficient behind the API your application already uses.
OUR WORK
Spend computation
where it helps.
LLM applications repeat instructions, revisit information and ask related questions. Treating each call as entirely new repeats work.
Our research studies what can be reused, how to reduce the work needed for an answer, and how to check that answer. The application keeps its normal prompts, messages and response handling.
We evaluate efficiency alongside answer quality, across models and workloads. The benchmark comparison includes the complete cost of producing an answer.
TECHNICAL REPORTS
Research foundations.
Technical reports on evidence, organizational memory and governed action. These earlier studies provide background to the Transductor’s work on model efficiency.