Practical model evaluation
Developing repeatable ways to compare quality, reliability and cost for real customer workflows.
Research
As a bootstrapped startup, we explore focused questions in model quality, controllability, efficiency and safety, then apply what works to practical products.
Current work
Developing repeatable ways to compare quality, reliability and cost for real customer workflows.
Testing lightweight approaches that keep chatbot and agent replies consistent with a customer's tone, policies and brand voice.
Establishing responsible review and moderation practices for the products and client solutions we build.
Research focus
How do we let businesses steer agent tone, behavior and guardrails without losing reliability?
Smaller, faster, cheaper inference — without giving up answer quality.
Building AI systems that respect data privacy, trademarks and consent.
Better metrics for what humans actually consider a 'good' agent response.
We work with academic labs, independent researchers and partner companies.
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