Overview
Private AI Document Search by Code Creator is a self hosted document intelligence and semantic search server designed for customers who want private document retrieval running inside their own AWS account.
This AMI helps organizations upload PDFs, Word documents, text files, Markdown files, policies, manuals, reports, technical documentation, contracts, support notes, and internal knowledge files into a private searchable knowledge base. The system converts documents with Docling, extracts searchable text, indexes the content into Qdrant vector search, and lets users search or retrieve relevant passages through a simple browser interface.
The product is designed for teams that want AI document search capabilities without immediately sending sensitive documents into a third party SaaS platform. It is useful for internal knowledge bases, technical documentation, support documentation, compliance records, operations playbooks, research files, business records, customer service references, and AI agent retrieval experiments.
By default, the server runs in private retrieval mode. No external LLM key is required to upload, index, search, and retrieve source backed passages. Without a configured model provider, the product returns the most relevant private document passages with source names and similarity scores instead of generating polished AI summaries. Optional generated answers can be enabled later by connecting an external or local model provider.
The application includes a public IP based web interface, first boot password generation, Basic Auth protection, an indexed document library, Docling UI access, Qdrant vector storage, Docker Compose services, helper commands, status checks, backup tooling, and MCP ready retrieval positioning for future AI agent workflows.
Uploaded documents remain visible in the indexed document library after upload. Customers do not need to reupload documents every time they search or ask questions. The browser file picker may clear after upload, but indexed documents remain stored and searchable until the customer removes or rebuilds the instance.
After first boot, Docling may take approximately 3 to 5 minutes to fully initialize. The web page may appear before document conversion is ready. If document conversion is not ready immediately, customers should wait a few minutes and refresh the page.
Only ports 22 and 80 need to be opened for the initial Marketplace deployment. Docling, Qdrant, and the private backend application are bound to localhost or internal Docker networking.
This AMI is built for customers who want a practical private AI document search starter server with a simple monthly software charge and normal AWS infrastructure charges. This is a repackaged open source software product wherein additional charges are applied for the deployment of the application and AMI support and compliance.
Highlights
- Self hosted private document search running inside the customer AWS account. Upload PDFs, Word files, text files, Markdown files, policies, manuals, reports, and internal documents without relying on a third party SaaS document platform.
- Built with Docling document intelligence and Qdrant vector search. Convert documents, index extracted text, search private knowledge, retrieve relevant passages, and keep uploaded files visible in an indexed document library.
- MCP ready retrieval foundation for future AI agent workflows. Use private retrieval mode with no external LLM key required, then optionally connect an external or local model provider for generated answers later.
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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
Private AI Document Search by Code Creator gives organizations a fast way to launch their own private document retrieval server on AWS. Instead of uploading sensitive PDFs, Word files, policies, manuals, and business records into a third-party SaaS tool, customers can run document conversion, vector indexing, and semantic search inside their own cloud account. It is practical on day one, useful without an external LLM key, and positioned for the next wave of AI-agent retrieval workflows.
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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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