Sold by: Lynxroute
Deployed on AWS
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This is a repackaged open source software product wherein additional charges apply for hardening, security configuration, and setup support.
AnythingLLM is a self-hosted ChatGPT-style workspace for chatting with your documents using any LLM provider, with built-in RAG, AI agents and vector search in a single hardened container. This Lynxroute build is hardened and ready out of the box: admin user with unique password at first boot, server bound to loopback behind Nginx TLS, embedded LanceDB and native embedder pre-configured, on a CIS Level 1 hardened Ubuntu 24.04 LTS base.
MIT license - fully auditable, no vendor lock-in.
Overview
This is a repackaged open source software product wherein additional charges apply for hardening, security configuration, and setup support.
WHAT IS ANYTHINGLLM
AnythingLLM is an open-source, self-hosted ChatGPT-style application that turns any document collection into a private, queryable workspace. The server is a Node.js application that ingests PDFs, DOCX, HTML, plain text, audio transcripts, and code, chunks and embeds the content into a vector database, and serves a multi-user web UI for chat and AI agents. It supports any LLM provider through a single switch in the admin UI - OpenAI, Anthropic Claude, AWS Bedrock, Azure OpenAI, Google Gemini, Cohere, Mistral, Groq, OpenRouter, Ollama, LM Studio, vLLM, LiteLLM, and many more. AI agents can browse the web, run SQL, call tools, and execute multi-step workflows. Operators get team workspaces with per-workspace document scope, role-based access, public chat embeds, REST API for programmatic access, an OpenAI-compatible developer API, and a built-in admin UI. Persists users, workspaces, chats, documents, and vectors in embedded SQLite and LanceDB - no external database required. MIT license, no vendor lock-in.
WHAT THIS AMI ADDS
Security hardening:
- Admin user with unique password (EC2 Instance ID) generated at first boot - never baked into the AMI
- JWT signing key, encryption signing key, and salt (>=32 chars each) generated at first boot
- AnythingLLM container bound to 127.0.0.1:3001 only - reachable only through the Nginx reverse proxy with TLS
- Multi-user mode enabled at first boot - the bootstrap auth window closes immediately after admin creation
- No provider API keys baked in - operator configures OpenAI, Anthropic, Bedrock, Ollama, etc. in the admin UI after login
- Anonymous telemetry disabled by default
- Nginx reverse proxy with TLS, HTTP-to-HTTPS redirect, WebSocket support for streaming chat, security headers
- UFW firewall pre-configured - only TCP 22, 80, 443 are exposed
- fail2ban, AppArmor
- CVE scan - every image is scanned for vulnerabilities before release
Out of the box, with no external services:
- Embedded LanceDB vector database - file-based, no separate container or network call
- Native embedder (Xenova/all-MiniLM-L6-v2) running inside the container - no external embedding API key required for RAG
- SQLite storage for users, workspaces, chats - no external database to provision
OS hardening (CIS Level 1):
- CIS Ubuntu 24.04 LTS Level 1 benchmark applied via ansible-lockdown
- auditd, SSH hardening, kernel hardening, IMDSv2 enforced
Compliance artifacts:
- SBOM - CycloneDX 1.6 at /etc/lynxroute/sbom.json
- CIS Conformance Report at /etc/lynxroute/cis-report.html
- CIS Tailored Profile at /usr/share/doc/lynxroute/CIS_TAILORED_PROFILE.md
Highlights
- Security baked in: admin user with unique password at first boot, JWT and encryption keys per instance, container bound to 127.0.0.1 behind Nginx TLS.
- RAG works out of the box - no external embedding service or vector DB to provision: ships with the native embedder (Xenova/all-MiniLM-L6-v2) inside the container and embedded LanceDB on a persistent host volume. Just upload documents and chat. Add provider API keys later in the admin UI.
- CIS Level 1 hardened Ubuntu 24.04 LTS: auditd, fail2ban, AppArmor, SSH key-only, IMDSv2 enforced. CVE-scanned before every release. SBOM (CycloneDX) and CIS Conformance Report included. MIT license - fully auditable, no vendor lock-in.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04
Deployed on AWS
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Pricing
Free trial
Try this product free for 5 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
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.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
t3.medium Recommended | $0.05 |
m6i.large | $0.05 |
m6i.xlarge | $0.05 |
t3.large | $0.05 |
t3.small | $0.03 |
Dimensions summary
You pay by the hour based on the EC2 instance size you run. Five options let you match compute power to your workload. The t3.small, t3.medium, and t3.large are burstable instances for lighter or variable use. The m6i.large and m6i.xlarge are general-purpose instances for steadier or heavier demand. Larger sizes carry a higher hourly rate. You pay only while an instance runs, with no upfront commitment. AWS bills the software hourly, on top of standard EC2 infrastructure charges.
Top-of-mind questions for buyers
Each option maps to an EC2 instance type. The t3.small, t3.medium, and t3.large are burstable, suited to lighter or variable document workloads. The m6i.large and m6i.xlarge are general-purpose, suited to steadier retrieval and chat loads. Pick the size that matches your expected concurrent users and document volume.
The software charge meters only while the instance runs. Fully stopped instances accrue no hourly software fee. You pay per running hour with no upfront commitment. Note that stopped instances may still incur standard AWS storage charges for attached volumes, which are separate from the software charge.
The image ships on a hardened Ubuntu 24.04 base with CIS Level 1 hardening, CVE scanning, and bundled compliance reports. Unique credentials generate at first boot. Support carries a 24-hour response target. The charge does not cover custom development, third-party integrations, or your wider cloud environment.
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Vendor refund policy
We do not offer refunds for this product. AWS infrastructure charges (EC2, EBS, data transfer) are billed separately by AWS and are not refundable by us.
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Content disclaimer
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
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
AnythingLLM 1.18.0
- AnythingLLM updated 1.17.0 -> 1.18.0, a bugfix release with no database migrations. MIT unchanged
- About 50 fixes across attachments, scheduled jobs, data connectors and AstraDB embeddings
- Security: login no longer reveals whether a username exists, and the embed allowlist is matched by origin
- Rebuilt on the latest CIS Level 1 hardened Ubuntu 24.04 LTS base, picking up every operating-system security update published since the previous build
Additional details
Usage instructions
- Launch instance (t3.medium recommended; t3.small works for light loads)
- Open Security Group - allow TCP 443 from your IP
- SSH: ssh -i key.pem ubuntu@<PUBLIC_IP>
- Read credentials: sudo cat /root/anythingllm-credentials.txt
- Open https://<PUBLIC_IP>/ in your browser - accept the self-signed certificate warning
- Log in with admin credentials from the credentials file
- Navigate to Settings -> AI Providers and configure your preferred LLM (OpenAI, Anthropic, AWS Bedrock, Ollama, etc.)
- Create a workspace, upload documents, and start chatting
Admin password equals the EC2 Instance ID. Credentials are saved to /root/anythingllm-credentials.txt at first boot. RAG works out of the box with the built-in native embedder and LanceDB - no external embedding service required. Replace the self-signed TLS certificate with a CA-signed certificate for production use.
Resources
Vendor resources
Support
Vendor support
Visit us online: https://lynxroute.com
For AnythingLLM documentation: https://docs.anythingllm.com For AnythingLLM upstream issues: https://github.com/Mintplex-Labs/anything-llm/issues For AWS infrastructure issues:
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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