FalkorDB Verified Customer Reviews (2026)

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.

SearchUnify is an enterprise Agentic AI platform that connects fragmented enterprise knowledge and deploys autonomous AI agents to handle customer support operations from first contact to resolution. At its core, the platform is powered by SearchUnifyFRAG™ (Federated Retrieval Augmented Generation), Agentic RAG, and the SCORE (Contextual Relevance Engine) framework, enabling accurate, grounded responses drawn from unified enterprise data. The product suite spans five core tools. Cognitive Search retrieves contextually relevant answers across distributed knowledge sources. SearchUnifyGPT™ generates cited AI responses at every support touchpoint. SUVA, the virtual assistant, handles multi-turn conversations autonomously. Knowbler supports knowledge capture, structuring, and surfacing at the point of need. Agent Helper delivers next-best-action recommendations to support agents during live case resolution. Extending these capabilities, the Agentic AI Suite comprises eight AI agents: AI Support Agent for self-service resolution, AI SupportPlus Agent for autonomous CRM ticket handling, AI Classification Agent for case tagging and routing, AI Escalation Manager for escalation risk prediction, AI Knowledge Agent for automated content creation and gap detection, AI Competency Agent for L2 technical workflow resolution, AI Agent Partner for real-time agent guidance, and AI Case Quality Auditor for evaluating every closed case. SearchUnify supports BYOLLM for LLM flexibility, Model Context Protocol (MCP) for secure system connectivity, and a governance layer covering role-based access control, PII masking, and ISO 27001, HIPAA, and SOC 2 compliance. The platform connects with 100+ enterprise tools including Salesforce, Zendesk, and ServiceNow.

InfiniteGraph is a highly scalable graph database engineered to handle rapid ingestion of extensive data volumes, processing billions of nodes and edges each hour while facilitating intricate queries. It is adept at efficiently distributing interconnected graph data across a worldwide organization. As a schema-driven graph database, InfiniteGraph accommodates very sophisticated data models and boasts an exceptional schema evolution feature that permits alterations and enhancements to an existing database structure. With its Placement Management Capability, InfiniteGraph optimizes the arrangement of data items, resulting in significant enhancements in both query execution and data ingestion speeds. Moreover, the database incorporates client-side caching that stores frequently accessed nodes and edges, allowing InfiniteGraph to operate similarly to an in-memory graph database, thus improving performance further. Additionally, InfiniteGraph’s specialized DO query language empowers users to execute complex queries that extend beyond typical graph capabilities, a feature that sets it apart from other graph databases in the market. This flexibility makes it a powerful tool for organizations that need to analyze and manage large-scale interconnected data efficiently.