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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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
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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
Rishav K.
Engineering-First AI with Real Impact—Fast-Paced Priorities, Strong Security Focus
Reviewed on Aug 05, 2026
Review provided by G2
What do you like best about the product?
What I like most about Datasaur is its focus on solving real-world problems with AI rather than using AI as a buzzword. The company's work in data labeling and LLM evaluation is critical for building reliable AI systems, and I find that space exciting. I also appreciate the engineering-first culture and the opportunity to work on security in a fast-growing AI company where protecting customer data and building secure infrastructure are core priorities. Given my background in cloud and application security, I believe I can make a meaningful impact while continuing to grow in the AI security space.
What do you dislike about the product?
From what I've seen, I don't have any major dislikes about Datasaur. If I had to mention one challenge, it's that as a fast-growing AI company, priorities and requirements can change quickly. However, I actually see that as an opportunity to learn, adapt, and contribute in a dynamic environment rather than as a negative.
What problems is the product solving and how is that benefiting you?
Datasaur is solving one of the biggest challenges in AI: creating high-quality labeled data and evaluating LLM outputs efficiently. Better training and evaluation data leads to more accurate, reliable, and trustworthy AI models. That benefits me because I work in cybersecurity, where AI is increasingly used for threat detection, alert triage, and security automation. Reliable AI systems depend on quality data, so Datasaur's platform helps improve the accuracy and trustworthiness of the tools security teams rely on every day.
Ayush U.
Intuitive Annotation Management and Smooth Team Collaboration
Reviewed on Aug 05, 2026
Review provided by G2
What do you like best about the product?
What I like most about Datasaur is how simple it is to manage large annotations projects. The labeling tools are intuitive, and multiple team members can work on the same dataset without creating conflicts. The built-in review process also keeps annotations consistent and makes quality control much easier.
What do you dislike about the product?
Some advanced capabilities require time to learn, and the interface can feel a bit crowded on larger projects. A more guided onboarding experience would help new users become productive more quickly.
What problems is the product solving and how is that benefiting you?
Datasaur has streamlined our data annotation workflow by replacing manual processes with a centralized platform. Teams can collaborate efficiently, complete reviews faster, and maintain higher labeling accuracy across datasets. This has reduced turnaround time and improved the overall quality of our training data.
Computer Software
Secure, Straightforward AI for Sensitive Business Data
Reviewed on Aug 04, 2026
Review provided by G2
What do you like best about the product?
What I like most about Datasaur is the secure environment it provides for using AI with sensitive business information. It gives our team the advantages of an AI assistant while still ensuring our company data stays protected. The platform is straightforward to use, and it allows us to work with internal documents confidently, without worrying about privacy issues or unauthorized data sharing.
What do you dislike about the product?
The subscription cost can be a barrier for smaller teams. I also wish it offered more flexibility when integrating with third-party tools, since connecting external services often requires extra permissions and additional configuration.
What problems is the product solving and how is that benefiting you?
Datasaur lets our team use AI for everyday tasks without risking exposure of confidential company information. Rather than relying on public AI tools, we can work within a secure environment that aligns with our organization’s privacy requirements. As a result, our productivity has improved, security concerns have decreased, and it’s become much easier to use AI confidently as part of our daily workflow.
Internet
Intuitive, Collaborative Data Annotation with Strong Quality Control
Reviewed on Aug 03, 2026
Review provided by G2
What do you like best about the product?
Datasaur offers an intuitive, collaborative platform for data annotation and labeling, which makes it straightforward to prepare high-quality datasets for AI and machine learning projects. The interface is easy to navigate, supports multiple data types, and includes strong quality-control features. It also helps teams work together efficiently while keeping annotations consistent across contributors.
What do you dislike about the product?
For large-scale annotation projects, setting up complex workflows and quality-assurance rules can take a while. I also think the reporting and analytics dashboard could offer more granular visibility into annotator performance. Expanding native integrations to include additional ML platforms would further streamline the overall workflow.
What problems is the product solving and how is that benefiting you?
Datasaur streamlines the data annotation process by bringing labeling, quality assurance, and team collaboration together in a single platform. By centralizing these steps, it reduces manual effort, helps improve annotation accuracy, speeds up dataset preparation, and allows AI teams to train high-quality machine learning models more efficiently.
Nicole M.
Privacy-First AI That Runs Securely Behind Your Firewall
Reviewed on Aug 03, 2026
Review provided by G2
What do you like best about the product?
I like its privacy first approach. Runs models behind the customers firewall or within thier controlled infastructure. It helps organizations for example in the health care system.
What do you dislike about the product?
This program is more complex to deploy, and has a slightly higher cost.
What problems is the product solving and how is that benefiting you?
It helps to design custom models and deployment options. It helps improve workflows within an organization which can also improve relevance and usefulness.