Evaluate your product on 8.3 billion agents
before you ship.

Yes. Every agent is drawn from 1,162 persona dimensions — demographics, life experience, personality (Big Five + MBTI), values, habits, skills, attitudes, 50 languages, accessibility needs, and live interaction state. Multiplied together that's billions of distinct, internally-coherent personas, so your evaluation covers the long tail and edge cases — not just the median user. You can also weight or constrain the space to mirror your real customer mix.

We calibrate against published human studies and held-out human baselines — matrAIx reproduces real human trajectories to 95%+ on the flows we've benchmarked. Where you have ground-truth data, we anchor the simulation to it; where you don't, we report confidence intervals and flag low-confidence segments rather than overclaim. You can also run a small human-in-the-loop validation (see Q07) to spot-check accuracy on your specific case.

Every trajectory is scored on several axes: fidelity (match to human baselines — 95%+ on benchmarked flows), coverage & diversity across the persona space, task success / completion rate, internal coherence (does the persona behave consistently with its dimensions), calibration (predicted vs. observed outcomes), and reward / preference scores for training use. We also report data-hygiene signals like deduplication and outlier flags, so you can see the quality of every batch before you rely on it.

Yes — and it makes the results sharper. Share your segments (personas, cohorts, geographies, account tiers, or anonymized analytics) and we map them onto the persona dimension space so the agent population matches your real user base. You then get reports sliced by your segments, not just generic ones.

matrAIx agents are synthetic — no real personal data is needed to run a simulation, so there's no PII exposure by design. If you share customer segments, we accept aggregated / anonymized inputs under NDA. Trajectory data is encrypted in transit and at rest, access-controlled, isolated per customer, and deletable on request. Your data is never used to train shared models without your explicit opt-in.

We run smoke tests that evaluate the matrAIx agents online against known-good cases, and you get full session replays of every trajectory — so you can step through, inspect, and audit each agent's decisions. You can define your own acceptance checks and we surface any that fail.

Yes. We offer a human-in-the-loop validation service: a small, representative sample of simulated trajectories is reviewed and scored by humans to confirm the simulation matches reality before you trust the full run. It's the fastest way to build confidence on a new flow.

Yes — the data is built for post-training. Every run is captured and scored into training-ready data: the best trajectories export as SFT examples, and scored pairs export as preference data for RL / RLHF and reward modeling. The same simulations that evaluate your product also improve your model or agent each iteration.

Yes. We agree on a quality bar up front, and if a run doesn't meet it we'll re-run it or refund you — we stand behind the results.

matrAIx provides forward-deployed engineers and go-to-market (GTM) engineers — highly skilled and experienced — who work hands-on with your team to integrate matrAIx directly into your product iteration process, from first run to production.