AI Security SDK for Custom Applications
A Python, TypeScript and .NET SDK embeds the same prompt and response controls into employee-facing and customer-facing applications — fitting operating models whose AI strategy includes building, not only buying, and whose engineering posture cannot reinvent prompt protection on every project.
Free Advisory
Fibi sources Liminal AI AI Security SDK for Custom Applications at no cost to you. Our advisory is funded by the carrier.
Side-by-Side Comparison
We compare Liminal AI against 300+ carriers so you know you're getting the best solution for your needs.
Post-Sale Support
Dedicated advisor for the life of your contract — Fibi escalates issues on your behalf so you're never dealing with carrier support alone.
More from Liminal AI
Related Services
Secure AI Enablement Platform
Single-pane access to leading generative AI models behind a governed control plane that inspects every prompt and response — fitting operating models whose workforce is already using AI and whose security posture cannot continue treating each consumer AI tool as an unmanaged egress channel.
Sensitive Data Protection on Prompts & Responses
A policy engine applies redact, mask, warn and pass-through actions on PII, PHI, financial identifiers and internal terminology before prompts reach a model — with rehydration of masked terms in the response — fitting operating models whose regulated data cannot be sent verbatim into third-party LLM endpoints, and whose privacy posture demands a deterministic control plane rather than user-side discipline.
Shadow AI Discovery & Governance
Sanctioned, observable AI usage across web, desktop and embedded applications replaces ad-hoc consumer AI tools — fitting operating models whose security posture has discovered employees pasting sensitive content into unmanaged AI surfaces, and whose governance posture cannot rely on blocking AI as a sustainable strategy.
Custom Multi-Model Assistants
Build, share and govern custom assistants configured with natural-language instructions, document context and an explicit or auto-selected model — fitting operating models whose use cases demand task-specific assistants, and whose IP and customer-data posture cannot accept consumer assistant tooling that lacks tenant isolation and policy enforcement.