Guides

Building high-quality NLP and LLM models can be complex, so we've created these guides to deliver maximum business impact and streamline team efficiency.

Best Practices for Prompt Engineering

Learn more about best practices for Prompt Engineering when using Claude, Mistral, and Llama.
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Productizing Large Language Models: A Comprehensive Guide

Datasaur previously helped democratize access to NLP, and now it will support companies in being at the forefront of Large Language Model (LLM) adoption and product development consultation.
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Guide to Liability in AI

Read about the ways that our laws and liability systems are evolving with—and as a result of—AI's rapid evolution.
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Guide to the Democratization of AI, ML, and NLP

AI is revolutionizing society and bringing up new ethical issues. Read about how democratization is coming into play for AI, ML, and NLP.
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Guide to Data Labeling Best Practices

Read about our best practices for increasing the efficiency of your team and your data labeling.
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As seen on

"We compared Datasaur to 55 other tools, and in that exhaustive comparison -- we found Datasaur to have the most complete suite of tooling."

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"Datasaur enabled us to automate our entire QA pipeline, we know what has been labeled (and the quality of each label) every 5 minutes without touching anything. It's all automated."

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"Integrating the platform with our AWS environment has been seamless, providing us with scalable data labeling capabilities."

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"We found the entire platform incredibly intuitive and easy to navigate. Onboarding was smooth and we were able to quickly adopt their automation tooling which was very important for us when considering a labeling platform."

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"We [Consensus] had a very complex and specific set of annotation needs. Datasaur was able to address those needs efficiently and effectively all while maintaining the personal touch you would expect from a start-up."

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"Our experience was pretty great. I enjoyed my time on Datasaur."

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"Instead of manually creating each project, we’re able to automate the project creation. Instead of manually scrolling through hundreds of medical labels, we can rely on search functions. This has saved admins and team members a lot of time in their project workflows."

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