Allganize has launched a secure MCP-based Agent Builder within its Alli platform, enabling enterprises to create powerful AI agents optimized for on-premise and SaaS environments. Unlike other solutions, Allganize ensures secure, isolated MCP component execution to meet strict data security and compliance standards. The Agent Builder works with Agentic RAG, requiring no code, and supports use cases like enterprise search, data analytics, and submittal reviews. Allganize currently supports over 300 clients across finance, energy, manufacturing, and government sectors.
Allganize, a Proven AI Leader Since 2017, Unveils Agent Builder Built on Model Context Protocol (MCP) – Optimized for Security and On-Premise Environments
April 21, 2025 – Houston, TX – Allganize (www.allganize.ai), a leading provider of enterprise LLM solutions, announced the official launch of its new Agent Builder based on Model Context Protocol (MCP), now available within its flagship platform, Alli. This new feature allows companies to build highly capable AI agents optimized for security, scalability, and compatibility with both SaaS and on-premise environments.
Allganize has been delivering enterprise-grade AI solutions since 2017 and was among the first to implement generative AI technologies in real-world applications as early as 2022. While many players are entering the space with MCP-based agent offerings, most fail to meet strict enterprise security requirements.
MCP (Model Context Protocol) is a powerful architecture that allows LLMs to dynamically interact with various tools, services, and data sources. However, most MCP components are externally developed and executed by the AI, often holding broad access privileges. This raises significant concerns for enterprise customers, particularly regarding access control, stability, and data leakage.
To address these issues, Allganize has developed a secure, fully isolated instance environment in which MCP components are executed, ensuring zero interference with core web systems, databases, or internal networks. This approach enables enterprise clients to safely deploy robust AI agents even in highly regulated and security-sensitive environments. For on-premise deployments, Allganize also offers its proprietary Alpha-V2 and Alpha-R1 models, designed to optimize performance without compromising compliance.
The Agent Builder works in tandem with Alli’s Agentic Retrieval-Augmented Generation (Agentic RAG) capability. This integration allows users to build agents without coding that can retrieve, analyze, and reason across complex document sets and internal data.
1. Enterprise Search Agent: Combines internal document search with external SaaS platforms, providing unified answers and insights across documents, databases, and tools.
2. Data Analytics Agent: Connects with complex databases and BI systems to automatically generate tailored reports.
3. Submittal Review Agent: Analyzes and reviews submittals against AEC industry standards and project specifications tominimize review time and project risk.
Allganize currently serves over 300 enterprise clients across the U.S., Japan, and South Korea in industries such as finance, energy, manufacturing, and the public sector. The Alli platform offers a comprehensive AI solution, including everything from industry-specific on-premise LLMs to agent builders and a full marketplace of enterprise-ready AI apps.
1. What is the Model Context Protocol (MCP)?
MCP stands for Model Context Protocol. It’s an advanced architecture developed to give AI agents deeper context awareness, secure data access, and the ability to perform complex tasks with higher accuracy—especially in enterprise environments.
2. Why is MCP important for enterprise AI?
MCP allows companies to deploy AI agents that understand not just queries, but the business context behind them. This makes AI outputs more accurate, secure, and aligned with enterprise goals—without exposing sensitive data to third-party models.
3. How is Allganize's Agent Builder different from other tools?
Allganize’s Agent Builder is based on MCP and designed for on-premise or hybrid deployment, meaning companies can build and run AI agents with complete control over data security and compliance. It’s also no-code, so anyone can build custom agents without engineering help.
4. Can Allganize agents work with my existing systems?
Yes. The agents integrate with existing enterprise tools and data sources through secure APIs, enabling them to automate tasks like search, data analysis, document comparison, and more.
5. What use cases can be built with the MCP-based Agent Builder?
The platform supports a wide range of use cases, including:
Founded in 2017, Allganize is a leading enterprise AI company offering an end-to-end LLM platform that includes proprietary models, an agent builder, and a marketplace of production-ready AI apps.
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