FlowX ScamGuard
Small models from a banking software company that read the text of an SMS, email or chat message and explain which scam tactic it uses. A human makes the decision on a disputed operation; automatic blocking without review is not acceptable.
- Developer
- FlowX.AI, USA and Romania
- First release
- Jul 2026
- Latest release
- Sep 2026
- Sizes
- 0.6B – 1.7B
- License
- Commercial use allowedApache 2.0
- Russian
- Not supported
- Ready-made builds
- GGUF, MLX (Apple)
- Running
- On your own serverAlso runs without a GPU
- Industries
- Finance, Security, Customer support
What it does
- Flagging incoming messages that show signs of deception
- Explaining which phrase triggered the flag
- Filtering emails and messages before they reach an operator
Where it is used
Hardware requirements
Versions
- Обновление карточек и сборок
- scam-guard-qwen06b и scam-guard-qwen17b
How to run it
I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems. Quantization compresses a model so it takes less video memory and runs on more modest hardware. Answers change slightly, so quality is checked on your own examples.
Frequently asked questions
Can FlowX ScamGuard be used in a commercial project?
Yes. License: Apache 2.0. It allows commercial use, but it is still worth having a lawyer review the license before launch.
What hardware does FlowX ScamGuard need?
At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Some versions also run on an ordinary CPU, without a GPU. You can calculate the exact VRAM for your model size and context in the hardware calculator.
Does FlowX ScamGuard support Russian?
No. The developer documentation lists the supported languages and Russian is not among them.
Where can I download FlowX ScamGuard and what does it cost?
The FlowX ScamGuard weights are open and free to download. You only pay for the hardware it runs on and for the setup. Source links are at the bottom of this page.
How I deploy it for clients
- SelectionI pick the model size for your task and hardware and test it on your examples.
- DeploymentI deploy it on your server or in a closed network and provide an API.
- Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
- IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.
Similar models
A classifier from an IEEE S&P study: it separates ordinary requests to a language model from requests that order text and a page meant to deceive people. A human makes the decision on a disputed operation; automatic blocking without review is not acceptable.
DetailsCybersecurityPhishing Email Detection DistilBERTcybersectony · not disclosedCommercial use allowedA very light classifier for emails and links showing signs of phishing. It errs in both directions, so borderline emails are still reviewed by a person.
DetailsText analysisFlowX OpenNERFlowX.AI · USA and RomaniaCommercial use allowedA family of small models that pull amounts, deal parties, jurisdictions, accounts and sanctions-screening mentions out of banking and insurance texts. A human makes the decision on a disputed operation; automatic blocking without review is not acceptable.
DetailsSource: huggingface.co/flowxai/scam-guard-qwen17b. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.


