Use cases
Where post-training pays off first, and what each industry's constraints mean for data, evaluation and deployment.
Industries and workflows
Post-training for customer support agents
How to fine-tune an LLM support agent that follows refund and escalation policy: data from resolved tickets, policy-aware rewards, evals by intent, and the metrics that matter in production.
Read →Use casePost-training for banks and insurers
Fine-tuning LLMs under model risk management: how SR 11-7 expectations map onto post-training, what validators ask for, and use cases from claims extraction to KYC review.
Read →Use casePost-training for healthcare and life sciences
How to fine-tune LLMs on clinical text: HIPAA Safe Harbor and Expert Determination de-identification, medical coding and documentation use cases, and evaluating clinical models.
Read →Bring a model and a metric.
Tell us what the model should get better at. A post-training engineer replies within one business day with a plan, a compute estimate and an eval design.