From LLM gateway to MCP governance, with purpose-built data protection throughout, the control plane your organization needs is taking shape.

The AI revolution gets headlines for its astonishing technology and sky-high valuations of big companies. The real history is going to be made, however, one person at a time, inside their workplace, engaging productively and creatively. How that succeeds or fails isn’t getting the attention it deserves.

AI adoption will depend on how much we trust it

AI will only become adopted by business through the creation of a pervasive human-machine interface of trust. Leaders need to know they have the right tools for their people, from LLMs onward. They need to manage spend and find the most effective behaviors for their missions. Security needs to know that there is a system of access and permissions to draw on corporate data, and they need to know that people and agents aren’t going to sketchy MCP servers or unwittingly taking risks with bad external data. People working with AI need to know they’re safe, and doing quality work that furthers their careers.

As AI moves from a more efficient way to do robotic process automation in the workplace to sophisticated agentic systems carrying out tasks inside and outside the organization, these multiple needs for trust are only getting more urgent.

LLM and MCP governance with purpose-built data protection

This is why Bardoor has extended the trust layer for agentic governance. Our approach includes:

  • Barndoor LLM Gateway, where people can choose and route models, monitor costs and usage, and create and enforce access and prompt policies. AI apps will stay fast, resilient, and on-budget for every provider. AI moves from a sandbox or test phase into meaningful adoption in production. 
  • Barndoor MCP Governance, offering customers the ability to control and manage how agents access company data and applications, while providing identity-aware access policies per your IdP, server, tool authorization rates, and call-volume limits. 

To both our LLM Gateway and MCP Governance products we offer purpose-built data protection capabilities, ensuring that sensitive data such as PII, isn’t accidentally leaked into or from a prompt, or maliciously added to AI instructions (and then discerned) via a rogue MCP tool call. 

We offer customers guidelines, but also the ability to fine-tune their policies to suit their business needs. We’ve made our data protection context-aware by default, so for example the label “confidential” sends up red flags and prevents data sharing. This is also customizable, since authentic trust is only possible if you and your teams have a say in how you operate.

We’ve included ways to prevent prompt injections and other malicious behaviors, so you can be confident you are working in trusted spaces.

Building understanding and transparency with customers

There is more work to be done. Building trust in the age of AI  is ultimately done by people and machines working together in new ways. The AI must be healthy and reliable, and the people need to be confident both about their tools and that they are staying within company policies and practices. Without some level of understanding and transparency, they cannot trust what they are doing. 

That’s why we’ve worked closely with customers in IT, Operations, and Management, building out a comprehensive system that addresses different needs while providing tools that are intuitive and effective. Since trust is established with ground-up risk management, we began with protection against corporate disasters, and then moved to optimizing opportunities. Corporate disasters also draw front-page headlines, and we’re here to keep you away from those.

The Barndoor agentic governance control plane is built to give teams the confidence to deploy AI at scale, without losing visibility or control. Reach out to see what Barndoor can do for your team.