Workflows
The work TAISR is built for.
TAISR is structured around the canonical jobs of technical AI safety research. Each is a first-class workflow, not a special case of a generic chat surface.
Primary workflows
Literature synthesis
Draw together the evidence on a research question, with provenance and methodological caveats preserved. Generic frontier models tend to flatten contradictions into a single confident summary; TAISR keeps the disagreement visible because the disagreement is often the finding.
Benchmark and evaluation comparison
Compare safety-relevant benchmarks and evaluations across models and methods. Each benchmark has known caveats — what it measures, what it doesn't, what it can be gamed by. TAISR surfaces those caveats alongside the numbers, so a comparison reads as evidence rather than a leaderboard.
Safety-case and reporting review
Review safety arguments and technical reports for completeness, evidence support, and the gaps a careful reviewer should flag. Built for the work of saying what a document does and does not establish.
Challenge and rebuttal review
Examine objections to a claim, surface live methodological disagreement, and find counter-evidence the original argument did not address. Treats challenges as research artifacts, not as a debate to be won.
Private pilot
Access is invitation-only.
Onboarding is in small batches, prioritizing high-context users.