We just launched our brand new AI Data Generation feature which allows you to use ayn LLM to generate synthetic data and insert that directly into a Postgres or Mysql database.
Simply connect your database, configure any LLM that you want to use (we support any model that is hosted on an endpoint, it can be local as well!), then provide a prompt and generate data.
We first sample 10 records to give you an idea of what the data looks like and you can iterate on the prompt and data until you're ready.
Neosync handles all of the infrastructure, prompt-chaining, formatting and orchestration of the data from the LLM to your database.
Here are some use-cases:
- If you're building a new app you can use Neosync to seed your database
- If you're working on a new service that has it's own database or schema, you can use Neosync to seed it with data.
- If you want additional data for fine-tuning or RAG, you can use Neosync to generate that data
What's next?
We can generate up to 1000 records right now and are working on supporting up to 10k in the next few weeks. Currently it works for a single table but we're working on making it work for an entire database including all of your constraints.
Here's a 5-min demo video:
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[ 4.6 ms ] story [ 13.6 ms ] threadWe just launched our brand new AI Data Generation feature which allows you to use ayn LLM to generate synthetic data and insert that directly into a Postgres or Mysql database.
Simply connect your database, configure any LLM that you want to use (we support any model that is hosted on an endpoint, it can be local as well!), then provide a prompt and generate data.
We first sample 10 records to give you an idea of what the data looks like and you can iterate on the prompt and data until you're ready.
Neosync handles all of the infrastructure, prompt-chaining, formatting and orchestration of the data from the LLM to your database.
Here are some use-cases: - If you're building a new app you can use Neosync to seed your database - If you're working on a new service that has it's own database or schema, you can use Neosync to seed it with data. - If you want additional data for fine-tuning or RAG, you can use Neosync to generate that data
What's next?
We can generate up to 1000 records right now and are working on supporting up to 10k in the next few weeks. Currently it works for a single table but we're working on making it work for an entire database including all of your constraints. Here's a 5-min demo video:
https://www.loom.com/share/79af81c12b7543fd9d3174c22842ccf2?...
You can run it locally using Docker Compose or Helm or try our hosted platform for free at neosync.dev
Thanks!