Graphwise Reviews

LM-Kit.NET serves as a comprehensive toolkit tailored for the seamless incorporation of generative AI into .NET applications, fully compatible with Windows, Linux, and macOS systems. This versatile platform empowers your C# and VB.NET projects, facilitating the development and management of dynamic AI agents with ease. Utilize efficient Small Language Models for on-device inference, which effectively lowers computational demands, minimizes latency, and enhances security by processing information locally. Discover the advantages of Retrieval-Augmented Generation (RAG) that improve both accuracy and relevance, while sophisticated AI agents streamline complex tasks and expedite the development process. With native SDKs that guarantee smooth integration and optimal performance across various platforms, LM-Kit.NET also offers extensive support for custom AI agent creation and multi-agent orchestration. This toolkit simplifies the stages of prototyping, deployment, and scaling, enabling you to create intelligent, rapid, and secure solutions that are relied upon by industry professionals globally, fostering innovation and efficiency in every project.

kama.ai is a Responsible AI Agent platform that provides organizations with a more accurate, accountable, and safe way to use AI. It supports training, compliance guidance, internal support, customer service, and specialized community needs. Unlike generic GenAI tools that create answers probabilistically, kama.ai combines deterministic Knowledge Graph AI with governed Generative AI and Trusted Collections. Trusted Collections is a RAG-based technology that helps reduce hallucinations on the generative side while giving AI Agents a reliable source of approved, accurate, and brand-safe information. This solution is a composite technology, specifically called GenAI’s Sober Second Mind™. In this case the sober element is the deterministic AI which guides and orchestrates the AI Agents to ensure hallucinations, and information sourced from nefarious sites, does NOT creep into your data or answers. kama.ai is designed for situations where answers need to be accurate, traceable, brand-safe, and aligned with approved source material. Human experts and Knowledge Managers can curate content, review AI-generated drafts, manage knowledge domains, and improve responses over time. This creates a governed-in-advance approach to AI, instead of relying on corrections after something has already gone wrong. kama.ai is especially well suited for knowledge-heavy organizations, training programs, compliance environments, Indigenous and community-focused initiatives, HR support, education, research, and other use cases where trusted and brand-safe information matters. By focusing on Responsible AI use and delivery, kama.ai helps organizations adopt AI more readily. This improves access to knowledge, reduces repetitive workloads, and provides more consistent support to the people who rely on their expertise. Think kama.ai for trusted AI, governed knowledge, and answers your organization is willing to stand behind.

Memgraph is a high performance, in memory graph database for real time AI context and graph analytics at scale. Vector search identifies what is similar. Graph reasoning reveals what is connected by traversing relationships, dependencies, and hierarchies that similarity alone cannot capture. Modern AI systems need both. Memgraph provides the graph layer that delivers precise structural context, full auditability, and sub millisecond performance. It powers GraphRAG pipelines, AI memory systems, and agentic workflows through a single high performance layer built for connected, structured context. The same architecture also supports real time graph analytics for fraud detection, network analysis, infrastructure monitoring, and other operational workloads where milliseconds directly affect outcomes. NASA uses Memgraph to connect people, skills, and projects across the agency in a queryable knowledge graph for real time expert discovery and workforce planning. Cedars Sinai uses it to connect genes, drugs, and clinical pathways in an Alzheimer’s knowledge graph spanning more than 230,000 entities, supporting drug repurposing research and multi hop biomedical reasoning. Across cybersecurity, finance, retail, and other knowledge intensive industries, organizations use Memgraph to turn connected data into real time insight.