Most data requires domain knowledge that can be hard to source and curate, and publicly available benchmarks are contaminated or too general to be useful to actual product builders.

Sepal AI is the data development platform that enables people to build useful datasets.

We bring data generation tooling, synthetic data augmentation, rigorous quality control, and a network of over 20k PhD and industry experts into one platform so you can manage the production of high quality datasets.
The data development platform for LLM users and builders.
Title: Sepal AI: Building LLMs for Large Enterprises. | Y Combinator

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### Building LLMs for Large Enterprises.

Sepal AI builds Large Language Models for Enterprises through data development, finetuning, and inference. Our team comes from Turing, Vercel, McKinsey, and Bain. At Turing, we built the LLM training business and products to support over $120M revenue growth in 6 months for companies like Open AI, Google, and Anthropic. We learned that large, non-tech enterprises that we worked with, like PepsiCo, Bridgestone, and Volvo, don't have the data they need to train models to produce real value. Which means they’re not going to unlock the value from AI without a partner. We are targeting the 2400 largest non-software companies to build, continuously fine tune, and deploy their custom models.



Sepal AI

Founded:2024

Team Size:3

Location:San Francisco

### Active Founders

### Robi Lin, Founder

Co-Founder @ Sepal AI Built the enterprise workflow products and fulfillment strategy at Turing.com. Scaled Turing’s LLM trainer business line from 50 to 800+ onboarded developers in 5 months for foundational LLM and enterprise customers. Previously was at Bain & Co.



### Kat Hu, Founder

Cofounder @ Sepal AI Built Turing’s Foundational LLM trainer business GTM. Ran orgs of 500+ AI trainers & built corresponding operations for scale. Previously was at McKinsey.



### Fedor Paretsky, Founder

I'm the co-founder and CTO at Sepal AI. Previously, I built platforms and infrastructure to bill users at Vercel while it went through hyper growth ($20M -\> $100M ARR). Before that, I worked on FP&A software at Mosaic and on platforms and infra at Newfront Insurance.



### Company Launches

[### 🌱 Sepal AI - Confidently deploy your AI models](

**Tl;dr:** Sepal provides frontier data and tooling for advancing responsible AI development.
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[Sepal AI]( is on a mission to advance human knowledge and capabilities with the responsible development of artificial intelligence.

**🧐 Responsibly advance human knowledge with AI? What does that mean?**
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We believe in a world where AI advances scientific research and empowers economic growth.

To achieve that future, AI product & model builders need:

1.  **Golden Datasets and Frontier Benchmarking:** To iteratively measure model performance on specific use cases.
2.  **Training Data:** To improve model capabilities using fine-tuning and RLHF.
3.  **Safety / Red-teaming:** To measure and forecast the safety of LLMs before putting them out in the wild.

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⚠️ **Okay, well why does it matter?**
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Frontier data for AI development is vital for safe deployment & scaling. However, developing this data is difficult.

Most frontier data requires domain knowledge that can be hard to source and curate (e.g., finance, medical, physics, biology, etc.). Publicly available benchmarks (e.g., MMLU, GPQA, MATH, etc.) are contaminated and too general to be useful to actual product & model builders.

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**🌱 How do we do this?**
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We’ve built Sepal AI - the data development platform that enables you to curate useful datasets.

**The Platform:** We bring data generation tooling, human experts, synthetic data augmentation, and rigorous quality control into one platform so you can manage the production of high-quality datasets.



**Our Expert Network:** We’ve built a network of 20k+ experts across STEM and professional services (think academic PhDs, business analysts, medical professionals, marketing and finance consultants) to support campaign design & data development.

Sample engagements we’ve run:

*   **🧬 Cell and Molecular Biology Benchmark:** An original benchmark to evaluate complex reasoning across models. Produced by a team of PhD biologists from top institutions in the US.
*   **💼 Finance Q&A + SQL Eval:** A Golden Dataset to test the ability of an AI agent to query a database and produce human-expert-level answers to complex finance questions.
*   **📏 Uplift Trials & Human Baselining:** End to end support for conducting secure in-person evaluations on model performance.
*   _…. \[insert your custom use case next?\]_

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**🙏 Asks:**
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1.  If you are building an AI application and need to measure or improve your model, or
2.  If you are a researcher at an AI lab building or evaluating models for new capabilities / risk areas, or
3.  If you’re passionate about the development of AI, AI safety, or evals in general…

Let’s [chat](

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**👪 Our team:**
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Meet [Kat]( (on the left), [Robi]( (in the middle), [Fedor]( (on the right)!

Robi and Kat previously built the technical LLM training business for Turing. Kat on the go-to-market & operations side. Robi on the product & fulfillment side. Fedor is a long-time close friend - he was an early engineer at Vercel & Newfront where he built out foundational infrastructure.

Say hi: [founders@sepalai.com](mailto:founders@sepalai.com).
