The Security Lab for
Small Language Models
We test the models you have built and deployed. Adversarial testing, red teaming, and security assessments for production AI systems.
[ 01 ]
THESIS
SichGate exists to advance the science of AI red teaming for the systems that matter most.
We find vulnerabilities, publish findings, and build open methodology. The field is moving faster than its safety knowledge. Responsible innovation means understanding what you've built before it reaches the people it's meant to serve.
[ 02 ]
THE EDGE GAP
Industry research focuses on cloud LLMs. SichGate secures models at the edge.
In medical devices, financial terminals, and private infrastructure.
Black-box and white-box adversarial evaluation for quantized, fine-tuned, edge-deployed language models.
[ 03 ]
THE ENGINE
Find.
Build.
Scale.
Continuous Research //
Findings published to the security community.
Proprietary Tooling //
Research codified into a suite of adversarial attacks built to exploit SLM-specific weaknesses.
Productized Assessments //
High-fidelity AI red teaming for regulated industries. Research-backed tools yielding a definitive map of model risk.
[ 04 ]
THE MARKET
The SLM market is projected to grow from $5.3B in 2024 to $26.7B by 2032.
CAGR
22.4%
Cost pressure is a primary driver — a 7B parameter SLM runs 10–30× cheaper than a 175B LLM.
Rising demand for edge-deployable AI and the on-premise data requirements of regulated industries like finance and healthcare are accelerating adoption — and the attack surface that comes with it.
CONTACT
You deployed a fine-tuned model. Contact us to understand its risk surface.