A model that
behaves the way you want.
Constitutional AI rules, critic models, safety classifiers and red-team feedback — woven into training so your model is helpful, honest, and harmless by construction.
Built for production, not just demos.
- Constitutional AI rule authoring + few-shot example sets
- Critic model dataset generation (self-critique training)
- Safety classifier training data (8+ harm categories)
- Refusal + safe-completion demonstrations
- Red-team probe set development
- Jailbreak resilience eval suite
- Persona / style adherence calibration
- Constitutional revision based on production drift
How a typical engagement runs.
Constitution
Co-design rules + counter-examples; map to your company's AUP and applicable regulations.
Generate
Produce critic and refusal data with controlled augmentation across the constitution.
Train
Inject into SFT and reward-model training; monitor for over-refusal and under-refusal.
Red-team
Run 1k+ probes per category; iterate on holes until target jailbreak rate is met.
Monitor
Production drift dashboards + monthly probe-set refresh.
What you get in your bucket.
Questions, answered.
How is this different from off-the-shelf safety filters?
Filters sit outside the model and trade off latency + UX. Alignment bakes the policy into the model so it refuses gracefully and uses your tone — no awkward bolt-on.
Can you cover regulated content (finance, medical)?
Yes. We add jurisdiction-specific rules (e.g. FCA + SEC guidance, HIPAA, ICH GCP) and review with your legal team before training.
How do you measure over-refusal?
We curate a benign-probe set and report false-refusal rate alongside attack-success rate. The goal is always Pareto improvement, not just refusing more.
Do you support multilingual alignment?
Yes — alignment data and red-team probes are translated and culturally adapted in 60+ languages with native reviewers.
Ready to build
AI you can trust?
Talk to a solutions architect — get a pilot scoped in 48 hours.