Model-Agnostic AI Architecture

By decoupling your data layer from specific model providers, MCP servers ensure your infrastructure remains resilient regardless of which AI tools you adopt next. MCP increases resilience against technological obsolescence, ensuring that your investment continues to provide value well into the future.

MCP Servers Flow

How Buildable Achieves Savings and Resiliency with MCP

Universal Data Connectors

We implement the Model Context Protocol to create a standard bridge between your AI assistants and your internal data sources. This eliminates the need to write custom integration code every time you want to test a new AI tool or model.

Local & Private Deployment

We configure MCP servers to run within your own private infrastructure or on local machines. This ensures that your proprietary documents and databases are accessible to the AI for context but never exposed to the public cloud or used for model training.

Granular Permission Scopes

You define exactly what the AI can see and touch with strict read/write controls. We help you set up specific boundaries so an assistant can access a single project folder without having the keys to the entire company directory.

Real-Time Audit Logging

We build in comprehensive logging that tracks every file accessed and every query made by the AI. This gives your security team total visibility into how AI agents are interacting with your internal systems at all times.

How we build things matters

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Let's build something together Our approach

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Learn more about our approach, the tools we use, and the agile process below.

Our Process & Approach

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