Four ways we work with you.
Build the system, put a voice agent on the phones, train the model, or prove that what you have is safe to ship. Most engagements start with one of these and grow into the others.
Production AI agents and workflows for regulated teams.
Agents, document automation and retrieval, built into your systems with a human in the loop.
- Document understanding
- Chat and in-app assistants
- Retrieval over your knowledge
Voice agents that handle the calls your team shouldn't have to.
Voice assistants that handle calls to an approved protocol, work inside your systems and hand off to people with full context.
- Inbound call handling
- Scheduling and intake
- Protocol-driven conversations
Fine-tune models on your data, with the evidence to prove it helped.
Curated datasets and fine-tuned models on your data, with before-and-after evidence.
- Dataset design and curation
- Annotation and human review
- Supervised and preference tuning
Know what your model gets wrong before your customers and regulators do.
Eval suites, red-teaming and regression tests that show what a model gets wrong before customers do.
- Task-specific eval suites
- Calibrated LLM-as-judge pipelines
- Red-teaming and safety testing
Start from the problem, not the service.
“We have a workflow that needs AI inside it, and it has to pass a compliance review.”
Custom AI solutions →“Our phones are busier than our team, and every call has to follow the same rules.”
AI voice agents →“Our prompts have hit a ceiling, or the model has to run inside our own environment.”
AI model training →“We are about to ship an LLM feature and need evidence it behaves, not a demo.”
AI model evaluation →Tell us what you're trying to ship.
Thirty minutes with the founder. We'll tell you honestly whether we're the right team, and what it would cost.