Context Management
Give context to AI and analytics
Bring consistency, governance, and production-readiness to AI and analytics, organization-wide.
Context management powers reliable AI and agents
Define, maintain, and apply shared business meaning and rules so insights are consistent, governed, and understood by both people and AI.
Layered architecture for safe, consistent AI analytics
Data Semantics
Define a shared meaning for AI and analytics
Define metrics, dimensions, and business logic once in a single semantic model, ensuring AI, agents, dashboards, and APIs all use the same definitions with consistent outputs no matter how the question is asked.
Governance
Set limits for what AI can access and do
Apply enterprise-grade controls to data access, usage policies, and agent behavior, ensuring AI operates within defined boundaries by default preventing misuse, leakage, and unsafe actions.
Grounding
Avoid hallucinations by using verified sources
Ground every AI response in real data and business knowledge, with answers backed by structured analytics and approved enterprise content with clear traceability to their sources.
AI-guidance
Tell AI how to reason, explain, and prioritize
Guide AI behavior using business instructions, analytical intent, and memory in order to define what terms mean, what matters most, and how results should be explained — so AI stays aligned with real business goals.
Observability
Track how context affects outcomes over time
Track prompts, inputs, outputs, and costs end-to-end enabling understanding of what context was used, what changed, and why results evolved — making AI analytics transparent and auditable in production.
Context is the foundation
that powers analytics and AI
Business Intelligence
Context connects metrics into narratives, ensuring dashboards, reports, and APIs use the same definitions, access rules, and logic
AI & Agents
Context grounds AI outputs in real data, governs behavior, and guides reasoning so agents operate safely and predictably in production.
Embedded Intelligence
One context model powers analytics delivered to end users, ensuring consistent meaning, permissions, and behavior across applications.
APIs & Developer Workflows
Developers consume context via APIs and workflows allowing efficient embedding, automation, and evolution of AI and analytics behavior.
