Send any amount of data, or point Luemyn straight at your warehouse or lakehouse. Pick frontier, open or your own fine-tuned models, or let intelligent routing choose the right one for each prompt. Results go back to your tables, with zero data retention.
Batch LLM work should be the cheapest, simplest way to put models to work on your data. Today it isn't.
Batch APIs are the cheapest way to run frontier models, but the plumbing is yours: limits, retries, failed rows, and moving data in and out of your warehouse. SQL AI functions are easy, but you pay for it. On Snowflake, Claude Sonnet 4.6 costs 2.4× its batch API price, before warehouse compute.1
Luemyn: straight from your warehouse and back, built on batch-API pricing.
At billions of rows, the model you choose is the whole bill. Running a frontier model on every row overpays for the easy ones. Switching to a cheaper model is risky when you can't see whether quality holds, and fine-tuning your own is a project of its own.
Luemyn: frontier models, open models we host, and your own fine-tuned models in one pipeline.
Many teams can't send data to a service that keeps it, or that processes it outside their region.
Luemyn: we keep nothing, and EU data stays in the EU.
Bring a table and a definition of a good answer.
We're building in this order, and design partners get each step first.
We're working with a small number of teams running large batch LLM workloads. Tell us what you're processing and where your data lives.
hello@luemyn.ai1. Snowflake AI_COMPLETE, claude-sonnet-4-6: 1.80 / 9.00 AI Credits per million input / output tokens at $2.00 per AI Credit ($3.60 / $18.00), Snowflake Service Consumption Table 6(a). Anthropic Message Batches API: $1.50 / $7.50 per million tokens, with results within 24 hours. Snowflake warehouse compute is billed separately. List prices, November 2026.
2. Luemyn stores no prompts or outputs once a job completes and results are delivered. When a job runs on a third-party frontier model, that provider's data terms also apply.