Sold by: Airbrush Technology
Deployed on AWS
AWS Free Tier
Deploy a production-ready private AI and RAG environment with LLM integration, vector search, document retrieval, and AI application APIs.
Overview
Airbrush Tech Private AI & RAG Server provides organizations with a deployable foundation for building secure, data-aware AI applications. The solution brings together retrieval-augmented generation, vector search, LLM integration, and scalable AI application services in a ready-to-deploy server environment.
Designed for teams that need greater control over their AI infrastructure, the server can be used to build internal knowledge assistants, document intelligence applications, enterprise search, automated decision-support workflows, and other generative AI solutions using private organizational data.
The platform is designed around modern AI engineering practices, including RAG architectures, vector databases, Python-based AI workloads, model integration, API-driven services, and cloud-native deployment patterns. It can serve as a foundation for organizations moving from AI experimentation to repeatable production deployments.
Highlights
- Private RAG Infrastructure: Build AI applications that retrieve relevant information from organizational documents and knowledge bases before generating responses.
- LLM & Vector Database Integration: Connect supported language models and vector-search infrastructure to create intelligent search, knowledge retrieval, and document-processing workflows.
- AI Application Server: Deploy a centralized AI foundation for development teams building production applications, APIs, automation workflows, and internal AI services.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04 LTS
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
Dimension | Cost/hour |
|---|---|
t2.micro Recommended | $0.06 |
c3.large | $0.03 |
m1.medium | $0.06 |
Dimensions summary
You pay by the hour for the compute instance that runs this private AI and RAG server. Three instance sizes are offered: c3.large, t2.micro, and m1.medium. Each represents a different amount of processing power and memory. You choose the size that fits your workload and are billed only for the hours you run it. There are no long-term commitments. Pricing scales with the instance size you select and the total hours it operates.
Top-of-mind questions for buyers
Each option runs the private AI and RAG server on a different AWS EC2 instance size. The c3.large, t2.micro, and m1.medium sizes offer different amounts of CPU and memory. You pick the size matching your workload, and each running instance meters as one unit per hour.
Software charges apply only while the instance runs. Fully stopped instances do not accrue hourly software fees. Underlying AWS storage costs may still apply for stored data, but the software license meters running hours only. Stopping the instance halts hourly software billing.
You are billed per hour for whichever instance size runs at that time. To change size, you stop one instance and launch another. Billing follows the size actually running each hour, so switching sizes changes your hourly rate going forward. There is no long-term commitment.
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Vendor refund policy
Refunds are currently not available. Requests will be reviewed on a case by case basis. Eligible refunds are processed in accordance with AWS policies.
Legal
Vendor terms and conditions
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Content disclaimer
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
First release of Airbrush Tech Private AI & RAG Server
Additional details
Usage instructions
To begin using this image, connect via SSH. Until you connect SSH into the instance and validate your credentials, you will not be able to access the Software. To connect to the operating system, use SSH and the username buntu. For instructions on using SSH to connect to your instance, see the AWS EC2 documentation: http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AccessingInstancesLinux.html2 Please note, this image may take upto 10 minutes to instantiate.
Support
Vendor support
For comprehensive assistance and guidance, our dedicated support team is available at https://airbrushtechnology.org/contact-us.html We are committed to providing prompt and effective solutions to address all your queries and ensure a smooth experience with our services. Our team is committed to providing responsive assistance to address technical queries, engagement planning, and ongoing project support.
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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