Sold by: Datasaur
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LLM Labs enables businesses to solve key business problems through AI & automation of OTS, custom, and private LLMs.
4.4
Overview
Use OTS LLMs or create your own proprietary model to automate AI solutioning to solve key business problems: improve margins and profits and accelerate delivery timelines by reducing costs, people time, and resources.
LLM Labs offers over 250 language models for robo-labeling (automated data annotation) based on OTS or custom ontologies and data sets. Models can be leveraged simultaneously for comparison, evaluation, and benchmarking of inference quality, speed, and cost as well as model recommendations. Furthermore, LLMs can be deployed in Datasaur's Data Studio for custom model development and automation.
You can explore and evaluate all of these with peace of mind, as Datasaur is SOC 2 Type 2, HIPAA, and GDPR compliant. Your data stays your data.
Highlights
- Leverage 250+ LLMs for robo-labeling (automated data annotation), model building and evaluation.
- Build custom AI solutions with the best-in-market LLMs and annotation tools for automation to reduce people time and costs by over 70%
- Full service workforce management and review tooling that allows teams to track and monitor progress.
Details
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Delivery method
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Free trial
Try this product free according to the free trial terms set by the vendor.
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
Pay as you go | You will be charged based on your usage of LLM Labs when performing any of the following activities: Running prompts and applications in Playgrounds, updating embeddings in Vector Stores, and generating completions for Evaluation projects. The cost depends on the model you use for these activities. An optional subscription plan is available for users who need to use their own LLM credentials from several providers, such as Azure, OpenAI, Bedrock, and Vertex. Contact us at support@datasaur.ai to learn more. | $0.00 |
Dimension | Description | Cost/unit |
|---|---|---|
Usage fees | Each model has a different cost. | $0.01 |
Vendor refund policy
This is a pay as you go plan. You will only be charged for the amount you use. For any refund requests please contact support@datasaur.ai
Custom pricing options
Request a private offer to receive a custom quote.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
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Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
For further inquiries or assistance with our products, please contact us at support@datasaur.ai .
To learn more and explore our products, visit our documentation at
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Customer reviews
Christina w.
Fast, Flexible Translations—But Some Words Still Trip It Up
Reviewed on Jul 30, 2026
Review provided by G2
What do you like best about the product?
I can type anything in English and it will translate it to any language that I need it to.
What do you dislike about the product?
Sometimes it is unable to translate certain words
What problems is the product solving and how is that benefiting you?
I get a lot of customers and clients that speak spanish and I use this to communicate with them
Mar M.
Impressive Model Evaluation for Comparing Outputs and Performance
Reviewed on Jul 30, 2026
Review provided by G2
What do you like best about the product?
The model evaluation capabilities to compare model outputs and assess performance are impressive
What do you dislike about the product?
There can be occasional lag when working with large datasets
What problems is the product solving and how is that benefiting you?
Data annotation, labeling, data set management and model evaluation
Jagan M.
Versatile NLP Platform with Seamless Exports and Customizable Workspaces
Reviewed on Jul 30, 2026
Review provided by G2
What do you like best about the product?
I love the sheer versatility of the platform. Whether you are working on traditional NER, complex document parsing, or LLM fine-tuning, Datasaur adapts to the project rather than forcing you to adapt to it. The ability to customize the workspace for specific dataset demands is fantastic, and the clean export formats integrate seamlessly into our existing backend workflows without requiring a ton of custom parsing scripts.
What do you dislike about the product?
While Datasaur handles standard NLP datasets very smoothly, it can experience noticeable lag when working with massive datasets or extremely long documents. Opening multi-megabyte files or scrolling through dense text with heavy annotation overlays sometimes causes slight UI delay. Additionally, while the interface is clean overall, setting up complex nested entity schemas has a bit of a learning curve for new annotators.The export pipeline, while functional, occasionally requires custom post-processing scripts to convert annotated data into non-standard ML model formats. There are also minor UI quirks when highlighting closely overlapping spans of text in complex NER tasks, where selecting the exact character offset can take a couple of tries. Streamlining raw export options and refining the text selection precision would make the experience seamless.
What problems is the product solving and how is that benefiting you?
The biggest problem Datasaur solves for us is the immense bottleneck of manual data labeling. In NLP projects, preparing the training data can easily consume more than half the project timeline. By centralizing the process and incorporating automated pre-labeling, Datasaur dramatically reduces the time our team spends on tedious annotation. This benefits me directly because it frees up our engineering hours, allowing us to focus on model training and deployment rather than wrangling messy spreadsheets or building custom in-house labeling tools. Ultimately, it accelerates our time-to-market for new AI features.
Writing and Editing
Clean, Polished Interface with Versatile Text and Audio Features
Reviewed on Jul 30, 2026
Review provided by G2
What do you like best about the product?
I really like the smooth interface—it looks clean and polished. I also appreciate the text and audio capabilities, which make it easy to use in different ways.
What do you dislike about the product?
I’ve noticed a bit of lag when processing large datasets.
What problems is the product solving and how is that benefiting you?
It helps me bulk-label data and annotate text files, which makes my workflow much easier, this creates efficient workflows.
Anish A.
Easy-to-Use Annotation Tools with a Smooth, Consistent Review Workflow
Reviewed on Jul 30, 2026
Review provided by G2
What do you like best about the product?
The annotation tools are easy to use, even for large projects. I like how multiple team members can work together without creating confusion. The review workflow is also straightforward and helps maintain consistency across datasets.
What do you dislike about the product?
Some advanced features took a bit of time to understand, and the interface can occasionally feel busy when working on complex projects. Better onboarding for new users would make the initial learning experience smoother.
What problems is the product solving and how is that benefiting you?
It helps us organize and annotate datasets much faster than using manual spreadsheets or custom tools. Collaboration is easier, review cycles are shorter, and the overall quality of labeled data has improved.