Sold by: Software Sushi
Deployed on AWS
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Flowise is a drag-and-drop builder for LLM chatbots, RAG pipelines and AI agents. Design flows visually, test them and call them over an API. This Ubuntu 24.04 AMI runs Flowise 3.1.4 behind loopback-only HTTPS, creates a per-instance owner account and stores data in SQLite. Bring your own model credentials.
Overview
Flowise 3.1.4 lets developers and product teams assemble LLM applications visually by connecting nodes for models, prompts, document loaders, vector stores and tools, then test them in the browser. This AMI puts that builder in your own AWS account, so flows, credentials and data stay on infrastructure you control.
What you get: Flowise on a loopback-only HTTPS endpoint (port 8443) with a per-instance TLS certificate, a private owner account whose password is generated at first boot into /etc/flowise/admin.password (readable only with sudo), local SQLite persistence under /var/lib/flowise, and a pinned Node 22 runtime. No model-provider credentials are included. Add your own in the Flowise UI, for example Amazon Bedrock through the ChatBedrock node. The image does not include Docker, Chromium/Playwright, Redis queue workers or Postgres.
Getting started takes a few minutes: launch t3.medium (32 GiB encrypted gp3 or larger, IMDSv2), attach an instance profile with AmazonSSMManagedInstanceCore, allow outbound HTTPS and keep the security group free of inbound rules. Connect with Session Manager, run bash /opt/sushi/docs/demo.sh as ubuntu, read the password with sudo, then forward port 8443 with AWS-StartPortForwardingSession and open port 8443 on localhost over HTTPS in your browser (trust the instance certificate).
Software fee: USD 0.02 per running t3.medium instance-hour with the first five days free for one concurrent instance; the same full software runs throughout and there is no product-imposed time, user or usage limit. Additional concurrent instances incur software fees. EC2, EBS, data transfer and any model-provider charges are billed separately. No annual offer is configured.
This is a repackaged open source software product wherein additional charges apply for independent AWS packaging, validation, maintenance and setup documentation (https://docs.flowiseai.com ). FlowiseAI authors the open-source core under Apache-2.0. Upstream enterprise portions carry FlowiseAI commercial terms and are not granted by this offer. No FlowiseAI endorsement is claimed. Back up /var/lib/flowise together with /etc/flowise before replacing an instance.
Highlights
- Build LLM chatbots, RAG pipelines and agent flows visually, then call them through the Flowise API.
- Loopback-only HTTPS UI with a per-instance certificate and an owner password generated on first boot, reached through Session Manager port forwarding.
- Runs in your AWS account with local SQLite storage. Connect the model providers you already use, including Amazon Bedrock.
Details
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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 | $0.02 |
Vendor refund policy
We offer a full refund of software charges for the first 48 hours billing starts if the product does not perform as described. To request a refund, email info@softwaresushi.com with your EC2 instance ID and a description of the issue. AWS infrastructure costs (EC2, EBS, data transfer) are billed by AWS and are not eligible for refund by us.
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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
Flowise 3.1.4 on Ubuntu 24.04 with a pinned Node 22 compatibility runtime, reviewed dependency overrides, a source-derived esbuild native runtime, SQLite persistence, per-instance TLS and owner account, and a loopback HTTPS flow builder. Connect through Session Manager. Bring your own provider credentials; no provider keys, browser downloads or enterprise entitlement are included.
Additional details
Usage instructions
- Launch t3.medium (32 GiB or larger encrypted gp3, IMDSv2) with AmazonSSMManagedInstanceCore and outbound HTTPS. No inbound rules are needed.
- Connect with aws ssm start-session --target <instance-id>, then run: sudo -iu ubuntu bash /opt/sushi/docs/demo.sh (it waits for first boot; expect SUSHI_CUSTOMER_DEMO_PASSED).
- Read the owner password privately: sudo cat /etc/flowise/admin.password
- From your workstation: aws ssm start-session --target <instance-id> --document-name AWS-StartPortForwardingSession --parameters '{"portNumber":["8443"],"localPortNumber":["8443"]}', open port 8443 on localhost over HTTPS in your browser and trust the instance certificate (/etc/flowise/tls/cert.pem). Sign in as admin@localhost.local .
- Add your model-provider credentials in Flowise and build your first flow. Back up /var/lib/flowise and /etc/flowise together.
Resources
Vendor resources
Support
Vendor support
Software Sushi provides AMI packaging and setup guidance. Contact info@softwaresushi.com for installation questions. Support coverage requires a separate agreement. This offer does not include FlowiseAI 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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