Our story (so far)
AI has advanced faster than anyone expected. Models became more capable, tools more powerful, and production rollouts more aggressive, often within weeks.
But along the way, security was treated as an afterthought. Most teams focused on outputs, performance, and features, assuming the model itself would behave safely if trained well enough.
In reality, training alone isn’t enough. Even well-aligned models can be manipulated through carefully crafted prompts that override instructions, leak sensitive data, or trigger unintended behaviors at runtime.
We saw teams struggle to fix this the hard way: retraining models, adding brittle prompt rules, or reacting only after something was leaked in production. The cost and complexity kept growing, but the risk never really went away.
LockLLM was created to address this gap. We protect LLM-powered apps, internal copilots, and agent workflows by detecting risky inputs before execution, so teams gain a practical layer of control without slowing down development.
Our goal is simple: make AI systems safer without making them harder to build. As models continue to evolve, security shouldn’t lag behind, it should be part of the foundation.
