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What is Kyvos Semantic Layer?

Kyvos is a semantic layer for AI and BI. It provides: 1. Unified Semantic Foundation for AI and BI- Kyvos semantic layer standardizes how metrics, KPIs, dimensions, hierarchies, relationships, calculations, and business rules are modelled across the enterprise — so that dashboards, analytics tools, notebooks, and AI systems all operate on the same understanding of the business. It enables: - Shared semantics — one common data language across every tool, team, and system - Governed access — data exploration within defined security, role, and permission boundaries - Platform interoperability — consistent semantic context across diverse platforms and environments - AI readiness — LLMs and agents work with governed business semantics rather than raw tables or ambiguous schema 2. AI Grounded in Business Context Kyvos grounds AI systems in the governed semantic model, ensuring they operate on established business context rather than raw schemas — improving the accuracy, traceability, and reliability of AI-generated insights. 3. Consistent Metrics Across BI Tools Kyvos centralizes metric and KPI definitions in the semantic layer and applies them consistently across every analytics interface — eliminating metric drift and improving trust in analytics. 4. High-Performance Analytics at Scale, enabling: - Sub-second query performance across massive datasets - High concurrency across thousands of users and workloads - Consistent response times regardless of data volume or concurrency - No performance degradation as adoption grows 5. Multidimensional Analytics on the Cloud: - Granular analysis across billions of rows - Thousands of measures and dimensions in a single model - Fast drill-down across complex hierarchies - Full analytical depth without sacrificing query speed 6. Cloud Cost Efficiency-Kyvos serves analytics through its semantic layer, reducing compute use and enabling users, workloads, and analytics to scale without increasing cost

What is Boost.space?

Boost.space is a no-code platform designed to transform fragmented business data into a structured, synchronized context layer for AI agents and automation systems. Acting as an Agentic Database, it centralizes information from CRM platforms, ecommerce tools, billing systems, marketing channels, and support software into a unified Single Source of Truth. This consolidation eliminates duplication, inconsistencies, and outdated records that typically prevent AI from operating effectively. Through continuous two-way synchronization, Boost.space ensures all connected systems remain aligned in real time. The platform enhances unified datasets with built-in AI enrichment capabilities, automatically classifying records, normalizing fields, generating structured attributes, and translating content at scale. With workflow integrations for tools like Make and planned support for Zapier and n8n, users can build automation scenarios directly on top of standardized data. Its Model Context Protocol (MCP) connects large language models to live business data, allowing AI agents to retrieve computed answers and execute cross-system actions without relying on static exports. This shifts AI from being a passive chatbot to becoming an active operator within business processes. Boost.space supports common use cases in ecommerce product information management, CRM synchronization, multichannel outreach, and performance marketing powered by first-party data. Security and compliance standards such as ISO 27001, SOC-2, GDPR, and Data Act alignment provide enterprise confidence. The platform is trusted by thousands of teams worldwide seeking scalable AI readiness without adding operational overhead. By orchestrating data centralization, enrichment, synchronization, and AI connectivity, Boost.space enables organizations to unlock real AI execution across their entire technology stack.