One governance layer across every LLM and AI agent integration — Bedrock, Azure OpenAI, Gemini, and custom — with a live inventory, consistent guardrails, prompt injection detection, and a full audit trail.
Warden is in active design with early-access partners. What you see here is the real assessment methodology and roadmap — we build the production platform around the first partners who commit.
Every team shipping AI features is quietly expanding your attack surface.
Teams stand up Bedrock, Azure OpenAI, and Gemini integrations independently. Most security teams cannot list every LLM call happening in production today.
A 2026 enterprise survey found 88% of organizations had a confirmed or suspected AI agent security incident in the prior year — most had no detection in place when it happened.
Customer data flows into prompts and completions with no consistent redaction layer, especially in fast-shipped internal tools built outside a formal AI platform.
Agents that can call tools, move money, or delete records often ship without a mandatory human-in-the-loop gate for high-risk actions.
Warden scans your cloud accounts, API gateways, and CI/CD pipelines to build a live inventory of every Bedrock, Azure OpenAI, Gemini, and custom LLM integration in production.
Wraps every discovered integration with consistent content filtering, denied-topic controls, and PII redaction — built on the same Bedrock Guardrails and Azure AI Content Safety primitives our consulting team already implements for clients.
Monitors prompts and completions for injection patterns, jailbreak attempts, and anomalous tool-calling behavior, scored and alerted the moment they occur.
A tamper-evident audit trail of every agent interaction — the evidence base you need for a compliance review or an incident postmortem.
Configurable human-in-the-loop checkpoints for actions above a risk threshold — financial transactions, data deletion, external communications.
A single control tower across every cloud and model provider — no more checking three separate consoles to know what your AI estate is doing.
Need an actual inventory and control plane for agentic AI before the board asks what happens if one of these agents goes wrong.
Shipping multiple LLM-powered features across Bedrock, Azure OpenAI, and Gemini and need consistent guardrails without rebuilding them per project.
In regulated industries (healthcare, financial services) who need an audit trail for every AI-assisted decision, not just a policy document.
Four questions. The same scoring logic our team uses in real client assessments.
How many distinct LLM or AI agent integrations does your organization run in production?
Our AI engineering team implements Bedrock Guardrails, Azure AI Content Safety, and Gemini safety filters as part of every foundation model engagement — Warden productizes that same expertise into a standing control plane.
Unlike single-vendor security tools, we already work across AWS, Azure, and Google Cloud for our consulting clients — Warden is built cloud-agnostic from the start.
This isn't our first production SaaS product — FinOps Co-Pilot is live today doing exactly this kind of cross-cloud governance work, for cost instead of security.
Become an early access partner — get direct input into the roadmap and priority implementation.