Build Summarization LLM Features for Production

Use Vellum to test, evaluate and productionize your summarization prompts that condense large text into clear summaries for a variety of tasks.

Screenshot of Vellum's playground

Develop Production-Grade

Summarization Features


Use proprietary data as context in your LLM calls.

Prompt Playground

Side-by-side prompt and model comparisons.


Integrate business logic, data, APIs & dynamic prompts.


Find the best prompt/model mix across various scenarios.


Track, debug and monitor production requests.

Frequently Asked Questions.

How do you evaluate a LLM summarization?

To evaluate your LLM summarizations you can use LLM-based evaluation and build custom evaluators that will check for things like coherence, factual accuracy, and comprehensiveness.

How can I summarize a whole document using LLMs?

You can either use an LLM with large context size like Claude 2.1 or GPT-4 Turbo, or create a multi-step AI workflow (RAG) that references a vector database containing your document.

What is the best LLM for summarization?

Typically, every LLM model excels at summarizing content. Experimenting with various prompts and model settings is necessary to find the optimal response.