These are research artifacts and open-source tools published by FlowX.AI, not shipped platform features. For platform capabilities, see AI in FlowX.
border: open-source LLM guardrails
border is an open-source Python library (Apache-2.0) that checks LLM inputs and outputs and signs an evidence record for each check. Evidence records hold hashes, the resolved policy hash, and the model revision that produced each finding, never the userβs text. It runs on CPU with the network interface down, and every classifier is scored in 26 languages.border.flowx.ai
Project site and documentation
GitHub
Source, Apache-2.0
Benchmarks
Published latency and accuracy numbers
Open models on Hugging Face
The flowxai organization on Hugging Face publishes 50 Apache-2.0 models focused on on-device AI for regulated industries: PII detection (piiguard, cee-pii), scam and fraud classification (scam-guard), content moderation, and regulated-advice detection, alongside two public benchmarks (cee-pii-bench, scamguardbench).
huggingface.co/flowxai
All models and benchmark datasets
Paper series
Seven technical papers on enterprise AI agents, published at flowx.ai/research:flowx.ai/research
The paper series, with arXiv links where available