Get AI to do what you actually want it to do.

Entry Point is the modern fine-tuning platform for proprietary and open-source large language models, including GPT, Llama-2, and Mistral.

Train models from leading LLM providers:

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The future is fine‑tuned.

When you reach the limits of prompt engineering, it’s time to fine-tune your own model. Fine-tuning is showing a model how to behave, not telling. It works together with prompt engineering and retrieval-augmented generation (RAG) to extract the maximum potential from large language models.

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Higher Quality

Fine-tuning can help you to get better quality from your prompts. Think of it like an upgrade to few-shot learning that bakes the examples into the model itself.

Faster Generation

For simpler tasks, you can train a lighter model to perform at or above the level of a higher quality model, greatly reducing latency and cost.

More Predictable Outputs

Does your model go off the rails? Fine-tuning can help. Train your model not to respond in certain ways to users, for safety, to protect your brand, and to getting the formatting right.

Scales With Your Team

Cover edge cases and steer model behavior by adding examples to your dataset, instead of running into conflicts from trying to make changes to a single epic prompt.

Fine-tuning at its finest.

In the past, fine-tuning was hard. You needed a lot of data, infrastructure, and insider knowledge. But the game has changed. Now, with modern large language models, you can start to shape output and behavior with a few dozen training examples — and Entry Point makes the whole process more seamless than ever.

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Train Across Providers

Don’t get locked into a single API or model. Entry Point helps you keep up with the fast-paced world of AI by opening up multiple LLM providers through a unified interface.

Work Together

Invite your team and keep track of your training data and fine-tuning jobs in one place. Count tokens, estimate costs, evaluate performance, and compare hyperparameters to see what works best.

Write Templates

The prompt and structure of your fine-tuning data has a big impact on outcomes. Our templating engine lets you iterate rapidly to see what structure, labels, and prompts yield the best results with your dataset.

Import & Export

Getting data in and out of Entry Point is a breeze. You can export your entire dataset as a JSONL anytime in the syntax and structure of your choice.

Share Models

Deploy a frontend to your fine-tuned model with a single click and share it for testing. All the completions are saved so you can catch problems and augment your dataset.

Avoid Common Pitfalls

Fine-tuning has a reputation for being finicky — we’re on a mission to fix that. We deal with all the nuances for different models, from syntax to token limits, so that you can get the results you want the first time.

No Code Required

We implemented all the APIs from top LLM providers and built a user-interface to make them more accessible, with full access to underlying hyperparameters and key settings.

Use Cases for Fine‑tuning

There are countless ways to leverage fine-tuned LLMs in software and business.

Content

Produce high-quality reports, blog articles, social media posts, emails, and more.

Tagging & Classification

Segment your data and tag content for search, meta data, or features.

Data Extraction

Extract key values from unstructured data in a consistent format.

Prioritization

Prioritize support issues, bug reports, lead form submissions and more.

Recommendations

Suggest products that a user might want based on items in their shopping cart or order history.

Fraud Detection

Train a model to determine if activity is suspicious or high-risk.

Moderation

Detect and flag inappropriate content in inboxes, apps, and chats.

Data Enrichment

Populate new fields for your data, like industry or custom segments for business contacts.

Scoring & Ranking

In a RAG workflow, you can use a fine-tuned LLM to rank your set of results by relevance.

Loved by customers

"I saw your product and the price tag and did not flinch. It was like finding water in the desert. We could not build our product without fine tuning. It is an absolute necessity to get the types of responses we need."

-SCOTTY, FOUNDER OF MINDSCRIBE

"I'm extremely pleased with Entry Point. Previously, preparing the JSONL and coding myself threatened my marriage, as my wife can attest. This tool is essential for anyone who needs to fine-tune models as part of their work. The team is highly responsive, assisting me over the weekend and addressing and enhancing my feedback. As it currently stands, it's the best innovation since sliced bread."

-TONI MATAS, FOUNDER AT SUPERALIA

"I have tried many fine-tuning platforms, but Entry Point was by far the easiest to use!"

-ANDRES PONCE, E-COMMERCE MARKETING MANAGER EMEA AT MEDTRONIC

"I think there are so many people with access to ChatGPT but don’t quite understand the power of it. I feel like I got a superpower."

-NATHAN GYANESHWAR, FOUNDER OF PURCHASEPLUS

"I love using Entry Point to manage my datasets, add to them manually, create synthetic examples, and then compare performance. It makes it so much easier to test all these things."

-JOHN GRANGE, CO-FOUNDER AND CTO AT OPSCOMPASS

"They have such a great product I was excited to go to office on Sunday to try it out!"

-ERKI KOLDITS, FOUNDER OF ZLICK

"Entry Point has been such an amazing application to work with that's made such a difference. If you're training models with OpenAI, you should definitely give it a try."

-JORDAN SILVERA, CEO AT SMART INTROS

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New to fine‑tuning?

Fine-tuning is the process of adapting a foundation model to a specific task, allowing you to change the behavior of the model by "show, not tell."

To learn the basics and train your first custom models, consider joining our free LLM Fine-tuning Masterclass.

Masterclass details

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