Product Performance Insights
Understanding performance metrics is essential for optimizing any knowledge-driven architecture. This page details the speed, scalability, and stability that Graphwise offers to organizations managing complex information at scale.
Performance Driven by Numbers:
The Graphwise Impact
We don’t just claim better results—we deliver them. Our technology is underpinned by industry-leading KPIs that transform your data from a liability into a strategic asset.
Precision & Trust
While standard RAG often retrieves irrelevant fragments, GraphRAG maps entities and their complex connections to ensure that AI responses are based on verified facts rather than statistical probability.
The Graphwise difference: Internal benchmarks show that by grounding AI agents in knowledge graphs, accuracy rates reach 90–100%, representing a measurable 26% improvement in overall AI performance compared to vanilla LLM setups. This approach reduces hallucinations from a typical 15% down to just 4%.
Faster Knowledge Acquisition
Speed to insight is critical for high-level ROI. Graphwise accelerates the transition from raw data to actionable intelligence by automating the discovery of patterns and relationships that are otherwise hidden in data silos.
The Graphwise difference: The platform makes time-to-action nearly three times faster by streamlining how information is accessed and synthesized. GraphRAG and Semantic Search powered by Graphwise runs 40% quicker, and teams report saving more than 30 minutes per complex query, significantly lowering the barrier to acquiring new organizational knowledge.
Fewer LLM Tokens needed
Efficiency at scale is a prerequisite for multi-million dollar investments. Graphwise optimizes token usage by providing the LLM with the most relevant, context-rich input rather than massive chunks of raw text.
The Graphwise difference: Implementing a semantic knowledge graph layer allows the platform to be highly selective in what is fed to the model. This results in an 80% reduction in LLM token usage compared to conventional RAG methods, directly translating to lower operational costs
Assisted Model Creation
Traditionally, building an enterprise-grade taxonomy required months of work by scarce, high-cost specialists. Graphwise has now introduced the Taxonomy Builder, our large language model (LLM)-based tool that serves as the “semantic engine” to transforms high-cost data complexity into a high-return strategic asset.
The Graphwise difference: Using the LLM-powered hierarchical generation in PoolParty 10.1, teams can generate robust taxonomy structures from domain descriptions in minutes rather than weeks. By shifting to a human-in-the-loop model, the platform empowers domain experts to oversee automated suggestions, reducing the total specialist labor required by up to 50-70%. Thus, it automates the creation of the “semantic backbone” required to connect siloed data assets, ensuring the organization is technically prepared to scale AI across the entire enterprise.
Lower Manual Tagging Efforts
The manual maintenance of metadata is often the greatest bottleneck in enterprise knowledge management. Graphwise eliminates this overhead through automated, context-aware concept tagging.
The Graphwise difference: By utilizing sophisticated classification algorithms and a semantic knowledge layer, Graphwise reduces manual tagging efforts by 75%. This automation transforms static document libraries into dynamic, searchable repositories without the “hassle” of manual metadata entry, allowing subject matter experts to focus on higher-value strategic tasks.
Why Global Leaders Choose Graphwise
From Microsoft and BBC to top-tier financial institutions and healthcare providers, the world’s most data-intensive organizations rely on our Semantic AI Suite to:
- Break Data Silos: Connect unstructured documents with structured databases.
- Scale with Standards: Built on W3C open standards (RDF, SKOS, OWL) for future-proof interoperability.
- Enable Agentic AI: Provide the long-term memory and contextual awareness required for autonomous AI agents.
Accelerated Product Innovation
70% reduction in coordination time across R&D and business teams and 25% reduction in R&D costs through ingredient targeting
Building Automation Systems
Lower maintenance costs through enterprise-wide asset visibility and centralized management
Cross-Enterprise Publishing
Making information easily and quickly available for public engagement.
Managing Product Conformity
Read about our solution for Microsoft 365, now powered by Graphwise.