Feature 03 of 10+ is liveFrontier evals, red-teaming, post-training data and RL environments for the teams building the most capable AI. Our research. Our AI universe.
Six interconnected research engines. One advanced intelligence environment.
Enter Frontier Systems Lab →A private research environment for AI evaluation, agent reliability and verifiable intelligence. Six engines, one network.
Built for frontier developers and the teams who build on their models. Every tool here works on one question: can you rely on this model, for this job, today? What is still being proven stays unnamed until it works.
Paste your AI's system prompt and the one thing it must never do. Probe fires 26 attacks across 11 techniques and shows you exactly which ones made it leak, judged by a hidden canary token and not by opinion.
Test your AI now →For serious research, for the future. Out of a vast archive, the papers that matter to your work and what each one found.
Which ideas are breaking out of their own history, sealed each month and graded in public.
Named on the day it works. Not before.
Cross-domain synthesis, systems thinking, problem reframing. Top of scale in frontier-model assessment.
Daily, adversarial use across frontier models
Ways we make models better: evals, red-teaming, data, environments
Benchmarks tell you how a model scores. We tell you how it behaves — where it breaks, why, and what data fixes it.
Before we change anything, we measure it. Attention, outputs, failure clusters, judge agreement — so every fix is aimed, not guessed.
Custom benchmarks built from your real use cases — not leaderboard trivia. Capability elicitation, LLM-as-judge calibrated against expert humans, contamination checks, and a harness you keep.
Adversarial testing by people who live inside these models. Jailbreak discovery, prompt-injection audits for agents, refusal calibration and reward-hacking hunts — every finding reproducible.
Expert-written SFT demonstrations, preference pairs for RLHF and DPO, and reasoning traces — designed against the failures we found, and measured on the evals that matter.
Verifiable tasks with graders that can't be gamed — tool-use, browser and workflow sandboxes where agents roll out, fail, and get better. Built for long-horizon reliability.
The failure modes we hunt, shown as illustrative examples — the kind of thing a 72-hour teardown surfaces, each with its fix.
We attack your model or agent for 72 hours straight. You get a ranked failure report, reproducible prompts and a fix for each.
A custom eval suite for your product, a harness you keep, and baselines across the frontier models you're choosing between.
Your embedded red-team and data partner, release after release — preference data, reasoning traces and RL environments on demand.
The lab makes frontier models better. The studio makes frontier products understood. We redesign and rebuild your homepage, with the research to prove every change.