How Data² reView Pioneers Enterprise Agentic Tooling Beyond MCP

While the Model Context Protocol (MCP) has established a standardized way for AI agents to interact with external tools and services, at Data² we've recognized early that enterprises require a more comprehensive framework to address the complex challenges of security, governance, and integration at scale. Our reView platform has been built from the ground up with this understanding, implementing an architecture that not only aligns with emerging best practices but extends them through our proprietary artificial reasoning technology.

Beyond Basic Integration: The Data² Approach

Where standard MCP implementations focus primarily on tool connectivity, reView's architecture centers on a secure, discoverable, and evolvable ecosystem for AI assistants within enterprise environments. Similar to the blueprint's layered architecture with an Enterprise MCP Gateway, our platform provides centralized access control while adding crucial capabilities through our graph-based data model.

The core differentiator in our approach is how we've implemented the Enterprise Knowledge Graph & Registry component. Rather than simply storing tool definitions, reView maintains a comprehensive, multi-dimensional classification system that organizes not just tools, but all enterprise information by department, domain-specific taxonomies, entity relationships, and capabilities. This addresses the critical challenge of discoverability across organizational silos that many MCP implementations struggle with.

Security By Design

Security concerns remain one of the biggest barriers to enterprise AI adoption. Our platform integrates seamlessly with enterprise identity providers, supporting multiple authentication methods including OAuth 2.0, SAML, and API keys, while implementing role-based and attribute-based access control for fine-grained permissions. With zero-trust security at its core, reView is ready for the most demanding enterprise and government deployments, as demonstrated by projects like ICON, SITEC-M, and MAVERICK.

Sophisticated Tool Orchestration Through Artificial Reasoning

Where the blueprint proposes a Tool Orchestration Layer with Chain-of-Tools selection mechanisms, reView takes this concept further through our artificial reasoning technology. Our platform doesn't just manage tool sequences, it understands the relationships between tools, data, and organizational context to make intelligent decisions about:

• When to use specific tools based on deep contextual understanding
• How to optimize multistep workflows across different data types
• Error recovery pathways with complete traceability
• Cross-domain reasoning that mirrors human expertise

This approach addresses the limitation that MCP lacks a built in workflow concept, creating a system that can handle complex business processes with the sophistication of human reasoning but at machine scale.

Continuous Evolution Through Connected Intelligence

The true power of our approach emerges in how reView enables continuous improvement through its connected intelligence framework. By maintaining explicit relationships between entities, our system:

• Collects comprehensive metrics on tool usage patterns
• Tracks success rates by tool, context, and domain
• Identifies optimization opportunities across organizational boundaries
• Suggests refinements based on emerging usage patterns
• Enables auto-composition of frequently chained tools

This creates a feedback loop that allows the system to evolve based on actual usage, addressing emerging requirements without constant manual intervention.

Transforming Enterprise Operations

Implementing reView delivers the transformative benefits outlined in the blueprint while extending them through our unique approach:

1. Enhanced Productivity: AI assistants autonomously discover and utilize appropriate tools to solve complex business problems without explicit programming, reducing time spent on routine tasks.
2. Democratized Tool Creation: Business domain experts can contribute tool definitions without requiring deep technical knowledge, accelerating the expansion of available capabilities.
3. Cross-Domain Insights: Analysis of tool usage across different departments reveals patterns and opportunities for optimization that might otherwise remain hidden in organizational silos.
4. Knowledge Accessibility: Enterprise knowledge becomes more accessible and actionable through natural language interactions, breaking down information barriers.
5. Consistent Security: Centralized authentication and authorization ensure appropriate access controls while enabling broader tool availability.
6. True Artificial Reasoning: Beyond basic tool orchestration, reView enables reasoning across structured, unstructured, and time-series data simultaneously, connecting dots that traditional systems miss.

The Data² Difference

While many organizations are still exploring basic MCP implementations, Data² has already built and deployed a comprehensive solution that addresses the enterprise challenges identified in the blueprint. Our reView platform doesn't just connect tools, it creates a unified information ecosystem where AI can reason across organizational boundaries with complete transparency and traceability.

By combining graph-based data models with advanced AI capabilities, we've created a platform that delivers on the promise of agentic tooling while maintaining the security, governance, and reliability that enterprises demand. As the industry continues to evolve toward more sophisticated approaches to AI integration, Data² remains at the forefront, not just following best practices, but defining them.

References:

• Model Context Protocol (MCP) and Amazon Bedrock
• A Deep Dive into MCP and the Future of AI Tooling

Jon Brewton is the Founder and CEO of Data Squared, a pioneering technology company specializing in AI-driven data intelligence. With extensive experience in enterprise data systems and artificial intelligence, Jon leads Data Squared in developing the reView platform, a revolutionary approach to data analysis that combines transparent AI with sophisticated graph technology. Data Squared competes in the all source intelligence and analytics market alongside companies like Palantir and C3ai, but differentiates through its unique ability to deliver explainable, trustworthy insights through a flexible, cloud agnostic architecture. The company's solutions have been successfully implemented across government and enterprise sectors, including all source intelligence and cybersecurity for US government agencies, and with industry leaders in the Oil & Gas sector.