Public research
Review specific product directions, the users they may serve, and the evidence and uncertainty behind each assessment.
A lightweight QA layer that evaluates AI-drafted support replies, sends questionable replies for human review, and summarizes recurring quality failures.
Target user
Support leads, support engineers, and technical founders at small B2B SaaS companies using AI-assisted written support.
A regression service that reruns representative support cases whenever prompts, knowledge, policies, tools, or configurations change and reports reply-quality regressions before release.
Target user
Support engineers, AI engineers, and technical founders who maintain production AI support workflows without a dedicated evaluation team.
A lightweight attribution layer that assigns model requests, supported tool-provider requests, and persistent runtime costs to each agency client and project, then presents cost-to-serve and delivery-margin views.
Target user
Small AI agency owners and technical delivery leads operating AI applications or agents for multiple clients.