Fine-Tuning Data
Custom, high-quality, privacy-compliant datasets at massive scale that you can afford
Free data testing tool
Save hours of time figuring out what data you're missing with Nurdle's free data-testing app.
Find out about its label bias, clustering, skew, and more…
Run locally or in Google Collab without sharing your data.
Use Custom Nurdle Datasets for
Predictive Classifiers
Generative LLMs (Chat & Non-Chat)
Train models to detect customer satisfaction, sentiment, regulatory risk, personal information or pretty much any behavior that can be communicated when one person writes something to another.
Fine-tune LLMs – whether for AI chatbots or for non-chat NLU AI applications – for better accuracy, domain expertise, brand persona, subject matter detail, policy compliance and role-based information retrieval.
Nurdle Data Fills the Missing Gaps
Kick-start your classifiers with custom cold-start datasets based on your specifications
Amp up performance of existing models by massively scaling your data with Nurdle data that mimics what you've already got
Supplement your model's performance with custom data to improve performance on a specific ability
Cold-Start Problem
Fine-tune your LLM
Improve specific capabilities
to see how closely they matched 7500 rows of real human-generated and manually-labeled data. There was a clear winner.
Near-human-level accuracy at synthetic price and speed
We tested the top synthetic data providers ...
F1 Score
Human Data
92% Accuracy of Human Data - At 5% of the Cost
Nurdle Data
Gretel
Mostly AI
Compared to Human
Data Scientist Prep Time
Cost / 100k Rows
78.5%
100%
160 hr
$10000
72.1%
92%
40 hr
$500
65%
82%
80 hr
$33
50% (random noise)
63%
80 hr
$1
Cheaper is Better. The future of AI is small, specialized LLMs that are cheap to run
ChatGPT is great for prototyping an AI project, but the compute costs to run it is 100 - 500 times more expensive than smaller LLMs that have been fine-tuned for specific use-cases.

This example by AnyScale shows performance differences for a specific task (summarizing emails) before and after task-specific fine-tuning.

Nurdle creates custom, high-performing training datasets for specific use-cases – so you can afford to deploy your AI project.
Why Nurdle?
How Nurdle can help
Kick start the 'Cold Start Problem'
Get your project off the ground with the custom dataset you need to start model building and model iteration.

Nurdle generates 2nd generation synthetic "lookalike" datasets based on small samples of real data – or your specifications. So even if you require difficult-to-find, privacy-regulated or low-prevalence datasets, Nurdle can produce clean, labeled datasets at the volume you need to get your project going.
Data Gap Analysis
Find out what data you're missing for better performance.

If you're not sure what data you need for improvement, Nurdle can analyze your data for you to tell you:

  • What data vector clusters are present in your data;
  • What data is missing for more robust cluster performance;
  • Data skew, bias and clustering;
  • How much and what type of data you still need.
Specific-Attribute Fine-Tuning Data
Whether the weak link in your generative LLM performance is a specific language, specific subject-matter or specific type of chat interaction, Nurdle can leverage our proprietary NurdleGPT data vault of millions of human-to-human unstructured text interactions to build synthetic "lookalike" tuning datasets to increase performance for individual use-cases.
Model Improvement Fine-Tuning Data
Sometimes you've got a working model or generative LLM but it's just not accurate enough for production.

Whether you know exactly what kind of data you need augmented or you need a Data Gap Analysis to determine what's missing, Nurdle can produce massive amounts of high-quality, Pii-compliant, cleaned and labeled synthetic "lookalike" data to boost your model accuracy – quickly, easily and inexpensively.
Not sure? Here's Some Sample Use Cases
Contact us to talk about your project. We'll show you how we can help.
Classifiers
Generative LLM
Whether used in a chatbot or social media or even applied to call transcripts or emails, detecting customer sentiment and intent can help you quickly route the most important conversations to the right people in your organization.

Nurdle's chat datasets can quickly improve your sentiment and user intent detection classifiers, so your chatbot can accurately recognize what your customers are thinking.
Classifiers
Whether used in a chatbot or social media or even applied to call transcripts or emails, detecting customer sentiment and intent can help you quickly route the most important conversations to the right people in your organization.

Nurdle's chat datasets can quickly improve your sentiment and user intent detection classifiers, so your chatbot can accurately recognize what your customers are thinking.
Generative LLM
Most companies use ChatGPT or another very large LLM to prototype their AI product. But when they run it in production, it costs a lot of money because they're paying for compute costs on billions of parameters that are irrelevant to their use-case.

When you're ready to scale your AI chatbot or other generative LLM, Nurdle can provide the custom datasets you'll need to train a small, low-cost LLM for the specific uses and capabilities you need.
How we do it
We produce high volume lookalike data (labeled or not); use your data to test it
Nurdlized Datasets
We produce high volume lookalike data (labeled or not); use your data to test it
Nurdlized Datasets
4
We detect ideal data clusters and what data is missing for your use-case
Data Gap Analysis
We detect ideal data clusters and what data is missing for your use-case
Data Gap Analysis
3
We compare yours with our pre-labelled LLM data vault
Nurdle Data Overlay
We compare yours with our pre-labelled LLM data vault
Nurdle Data Overlay
2
Yours or ours - as few as 50 rows
Real Data Sample
Yours or ours - as few as 50 rows
Real Data Sample
1
We produce high volume lookalike data (labeled or not); use your data to test it
Nurdlized Datasets
We detect ideal data clusters and what data is missing for your use-case
Data Gap Analysis
We compare yours with our pre-labelled LLM data vault
Nurdle Data Overlay
Yours or ours - as few as 50 rows
Real Data Sample
0
4
3
2
1
Need help with something else?
Let Nurdle do the boring part of data science so you can do something more important.
Data Sourcing, Cleaning, Prep & Labeling
It is super frustrating when you've built a great model or generative AI app, but there's no way to test it for accuracy or hallucinations. Time to Nurdle-ize it.
Evaluation Data: RAG/QA-formatted test data
Test your data for free:
Save hours of time figuring out what data you're missing with our free Nurdle data test tool.
Label bias, clustering, skew, and more..
Run locally or in Google Collab without sharing your data.
Justin Davis
Co-Founder and CEO
"Nurdle has been used for 6 years by Spectrum Labs to parse billions of online human interactions.

We've used Nurdle data to moderate content for Riot Games, Grindr, The Meet Group, Together Labs, and other gaming, dating, and social media platforms."
Apply for Nurdle’s Pilot Program
Available for a select group of companies.
Data Gap Analysis Report
Preparation of Unstructured Datasets
Augmenting Existing Data into Fine-Tuning Datasets
Identify what kind and how much data is missing from your dataset to increase the accuracy of your LLM.
PII scrubbing for GDPR and HIPPA compliance, cleaning, and labeling.
Use cases include (but are not limited to) conversational LLMs, Q&A LLMs, and training your LLM in multiple languages.
Follow us on social