Agentic Graph Systems: How Data² reView Is Transforming Enterprise AI

Enterprise AI deployment faces significant challenges that most organizations are still struggling to overcome: data fragmentation, security concerns, compliance requirements, and organizational adaptation barriers. While many companies are just beginning to recognize these challenges, at Data², we've been building the solution: agentic graph systems that combine sophisticated knowledge graphs with advanced AI to create truly intelligent systems capable of understanding organizational relationships and context.

The recent success of Klarna's "Kiki" implementation offers market validation for the approach we've pioneered with our reView platform. Like many enterprises, Klarna struggled with information scattered across 1,200+ SaaS applications, creating what their CEO Sebastian Siemiatkowski called "an unnavigable web of knowledge." This mirrors the challenge we've seen across industries and government agencies, fragmented data ecosystems that traditional AI approaches simply cannot navigate effectively.

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Beyond Traditional AI: The Data² Difference

Where traditional AI approaches operate on isolated data sets without understanding relationships, our reView platform was built from the ground up to represent knowledge as networks of connections rather than collections of data points. Similar to Klarna's implementation, our graph structure explicitly models connections between entities (people, projects, documents, processes), but we take this further with our proprietary artificial reasoning technology.

The key difference lies in our approach: While vector-based methods "inevitably flatten complex relationships," reView's three dimensional data landscape preserves these vital connections. This isn't just about connecting dots, it's about revealing relationships you didn't even know existed.

Foundation First: The Path to True Enterprise AI

Our implementation methodology parallels the successful approach highlighted in the Klarna case. We don't simply apply AI to existing fragmented data, we follow a methodical process:

1. Evaluate data value across your ecosystem
2. Implement our advanced graph database technology
3. Develop a unified knowledge stack
4. Connect previously siloed information
5. Standardize knowledge representation
6. Integrate our transparent, traceable AI capabilities

This foundation-first strategy has proven essential across our implementations with projects like ICON, SITEC-M, MAVERICK, and with industry leaders like Civitas in Oil & Gas.

Beyond Chatbots: True Agency and Intelligence

The capabilities we've built into reView transcend traditional AI systems, exhibiting what we call "true agency." Unlike simple question-answering systems, reView can:

• Traverse complex relationships to find contextually relevant information
• Understand how information connects across domains
• Provide comprehensive, explainable answers that incorporate surrounding context
• Reason across structured, unstructured, and time-series data simultaneously

This level of intelligence drives organizational transformation far beyond technology implementation.

The Architectural Advantage

The architecture of our agentic graph system represents a fundamental paradigm shift from traditional AI approaches. Where conventional systems treat data as isolated chunks, our graph system maintains explicit relationships between entities, enabling:

• Preserved context between information sources, allowing the system to understand the full meaning of data in relation to other data
• Cross-domain reasoning that mirrors human expertise, understanding how supply chain issues affect quarterly financials or how marketing decisions influence customer retention
• Associative intelligence the ability to make meaningful connections across traditionally separated domains of knowledge

The Future Is Connected

Organizations that succeed in the AI era won't be those with the most data or even the most sophisticated algorithms. Success will belong to those who can transform fragmented information into connected, actionable intelligence.

At Data², we're not just building another data analysis tool, we're creating a next-generation reasoning platform that reveals the connections hidden within your existing data ecosystem. Our reView platform represents the future of enterprise AI: open, explainable, adaptable, and designed for organizations looking to innovate aggressively without the downsides of black-box AI.

Join us for our webinar today where we'll explore these concepts in depth: https://lnkd.in/gt6i8-mv

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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.