Galini

Galini is a guardrails-as-a-service platform that makes it easy for enterprises to create, test, deploy, and refine content guardrails for their AI applications. As organizations deploy AI agents and LLM-powered features into production, they face an increasingly critical challenge: ensuring AI outputs comply with company policies, industry regulations, and safety standards without slowing down development or degrading user experience. Galini addresses this by providing a managed guardrails layer that sits between AI applications and end users.

The platform filters both harmful inputs (prompt injections, policy-violating requests, attempts to extract sensitive data) and harmful outputs (responses that violate compliance requirements, contain inappropriate content, or leak confidential information). Unlike hardcoded content filters that produce excessive false positives, Galini's guardrails are configurable based on each company's specific policies and the regulatory requirements of their industry — a healthcare AI has different guardrail needs than a marketing AI or a financial advisory tool.

The create-test-deploy-refine workflow is central to Galini's approach. Teams can define guardrail policies, test them against representative traffic, deploy with confidence, and continuously refine based on real-world performance data. This iterative approach acknowledges that guardrail requirements evolve as AI applications mature and as regulatory landscapes shift. The platform provides analytics on guardrail activations, false positive rates, and policy coverage gaps.

For enterprises deploying AI in regulated industries (healthcare, finance, legal) or high-stakes consumer-facing applications, Galini provides the compliance infrastructure that makes responsible AI deployment practical. Rather than building custom content safety systems — which require specialized ML expertise and ongoing maintenance — teams can implement production-grade guardrails through a managed service, reducing both the engineering burden and the compliance risk of AI deployment.