Technical AI Safety Research
A specialist system for technical AI safety research.
In math, chemistry, biomedicine, clinical research, software engineering, and weather forecasting, specialist systems have outperformed generic approaches by encoding domain structure. TAISR applies that pattern to technical AI safety: a curated corpus, evidence discipline, and workflows shaped around the field's real research tasks.
Why specialize
AlphaProof, SWE-Agent, AlphaFold, GraphCast, Lexis+, and RECTIFIER point to the same lesson: specialization works when the system encodes the domain substrate, verifier loops, task-specific interfaces, and evidence structure. TAISR applies those levers to technical AI safety research.
The domain substrate, not a thin slice of generic search
ChemCrow's leverage starts from 18 expert-designed chemistry tools; AlphaFold's from biological priors built into the architecture. TAISR starts from a continuously curated technical AI safety corpus with explicit scope and provenance.
Every claim wears its support state
Specialist legal AI like Lexis+ beats vanilla GPT-4 — and still misgrounds citations roughly 17% of the time. TAISR's outputs tag every claim supported / weakly supported / contradictory / open, so the residual gap is visible rather than hidden in fluent prose.
Each canonical job has its own scaffold, not a blank chat box
SWE-Agent went from 1.3% to 12% on SWE-bench by replacing a bare prompt with a purpose-built agent scaffold. TAISR is built the same way around its canonical jobs — synthesis, comparison, review, challenge, and research-gap analysis.
Workflows
Five recurring jobs get first-class scaffolds: literature synthesis, benchmark and evaluation comparison, safety-case review, challenge and rebuttal review, and research-gap and hypothesis support. TAISR's edge is not generic paper search; it is preserving evidence, support state, and contradiction through the work. See how each is built →
Private pilot
Access is invitation-only while we onboard the first cohort of collaborators.
For independent and grant-funded technical AI safety researchers, frontier-lab safety and evaluations teams, AI governance and standards groups, and institutions funding or supervising technical AI safety work.
We respond personally to every request. No marketing list, no automated drip.