FinetuneDB is the easiest way to train and deploy your own fine-tuned models from one unified platform. Train AI models with your data in minutes, not weeks, and get better performance at a lower cost.
FinetuneDB allows us to quickly iterate and create model versions that best serve our needs. Give it a try if you're a startup that could benefit from fine-tuning your LLMs, or even if you're curious about how fine-tuning might improve your model's performance.
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Maker
👋 Hey Product Hunt!
We're excited to introduce FinetuneDB (https://finetunedb.com), the easiest way to train and deploy fine-tuned models! 🎉 With FinetuneDB, teams can easily create & manage high-quality datasets and streamline the full workflow—from fine-tuning to model deployment and evaluation with domain experts. Want the details? Check out our docs here: https://docs.finetunedb.com.
Why we built it:
Fine-tuning is powerful, but creating high-quality datasets is a major bottleneck that stops teams from getting the most out of base LLMs. Without a streamlined way to build, organize, and refine datasets, teams often struggle to adapt their models to new products, formats, or requirements. FinetuneDB removes this barrier by making it simple to build, organize, and refine datasets and then use them to train proprietary and open-source models that meet specific needs, all in one place.
What makes FinetuneDB special?
🚀 End-to-End Workflow – From dataset creation and fine-tuning to serving and evaluating outputs.
📊 No-Code Dataset Manager – Version-controlled and collaborative, allowing you to upload JSONL, use production data, or work with domain experts to build custom, high-quality datasets.
🤖 Evaluation Workflows – Enable non-technical team members to review and refine model outputs. (LLM-as-judge also available)
What can you achieve with fine-tuning?
Fine-tuning unlocks new capabilities and can improve LLMs for a wide range of tasks. Here are just a few examples:
🎯 Domain specific model improvement – Fine-tuning enables your model to deliver more reliable outputs, dramatically reduce hallucinations, and achieve much higher accuracy on your specific tasks. By incorporating your own data, you can build models that truly understand your domain, making them far more accurate than generic, prompt-based alternatives.
📰 Content creation for news & blogs – Fine-tune a model to write in your unique brand voice, reducing the need for editing and reformatting. This is especially useful for high-volume publishers wanting consistent style across content.
🛍️ E-commerce product descriptions – Generate descriptions in your brand’s style as products change, without needing to re-engineer prompts. By fine-tuning, you create examples for each scenario, refining outputs to be accurate and consistent. Your custom model, trained on your domain-specific data, will follow your exact format and tone.
Most users work with OpenAI models, but we’ve got you covered if you want to train open-source LLMs. Our pay-as-you-go pricing for serverless inference with models like Llama and Mistral includes up to €100 in free credits to get started!
We’re currently in public beta, and we’d love to hear your feedback! Whether you're experienced with fine-tuning or exploring custom LLMs for the first time, FinetuneDB is here to make the process easier, faster, and more accessible for everyone.
Thanks for checking us out ✨
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Congrats!!! love the product and how it helps us increase our LLM productivity and efficiancy
😸 Congrats on launching! I'm curious: What competitive edge do people get from using FineTuneDB over other vanilla 🍦 model training services?
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Maker
Thanks André, our no-code dataset manager makes it super easy to create high-quality datasets in collaboration with your team / domain experts. This enables you to get started with fine-tuning quickly.
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Big congrats Felix! Looking forward to follow your journey and support you from my role at AWS.
Which 3 key use cases are you looking to excel at first?
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Maker
Thanks @asbjorn_jorgensen ! Domain specific model improvement is the biggest one, which is really use case agnostic, but also e-commerce product descriptions and content creation for companies to create custom models in that space are very sought after.
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Ahh this is a great way to fine-tune what we have dealt with! Just out of curiosity.. who do you think is this best used by? What use cases have been most successful with your solution?
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Maker
@frederik_nagel good to hear, anyone who’s looking improve an LLM for a specific task, can be anything from improving output accuracy to aligning tone of voice for content creation such as newspapers. Here‘s an overview of a couple more: https://finetunedb.com/use-cases/
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Oh this looks good! @felix94123! Had one question, do you see yourself also helping create synthetic data so it could be one whole product? Create + fine tune in one place?
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Maker
@dhruv_tekchandani yes synthetic data generation is already possible (manually) but will be expanded into an automated workflow. Then you can easily expand your datasets with additional synthetic data for better performance. If you have a use case you want to discuss always happy to chat, just reach out: founders@finetunedb.com 🙏
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Interesting. Is it possible to get detailed statistics about the dataset created in the Manager to mitigate data bias? Same thing during deployment and concept drift.
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Maker
Happy to hear @jakob_salomonsson, there are some statistics available and more to come soon!
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Excited for Finetune DB, currently a user and it’s helped tremendously with cost savings, and especially being efficient in understanding our data.
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