Use Vellum to develop a chatbot for insurance that can answer policy questions, assist with claims, provide quotes, and document client interactions.
Vellum helps you along the AI adoption curve. Go from prototype, to deployed prompt, to optimized model in three steps.
Quickly iterate to find the best prompt, model provider, model, and parameters for your use-case – all while using data specific to your company.
Use Vellum's LLM-provider-agnostic API to interface with deployed prompts/models in production. Compatible with popular open-source libraries like LlamaIndex.
Vellum automatically captures all the data needed to know how your models are performing in production so that you can improve them over time.
With Vellum you have total ownership of your RAG process, prompts, models and tools you use.
Vellum provides a shared workspace where Engineers, PMs and Domain experts can collaborate on building LLM features.
Every model input, output, and end-user feedback is captured and made visible at both the row-level and in aggregate.
"Vellum has completely transformed our company's LLM development process. We've seen atleast a 5x improvement in productivity while building AI powered features"Eric Lee, Partner & CTO of Left Field Labs
No more juggling browser tabs and tracking results in spreadsheets.
Test changes to your prompts and models before they go into production against a bank of test cases + recently made requests.
Dynamically include company-specific context in your prompts without managing your own semantic search infra.
Track what's worked and what hasn't. Upgrade to new prompts/models or revert when needed – no code changes required.
See exactly what you're sending to models and what they're giving back. View metrics like quality, latency, and cost over time.
Use the best provider and model for the job, swap when needed. Avoid tightly coupling your business to just one LLM provider.