Context models and insights tailored to how your industry actually operates.
The missing layer for agentic AI, Syntes AI turns fragmented enterprise data into live, trusted context for analytics, AI agents, and governed action without rebuilding your data stack.
Syntes builds a continuously updated operational knowledge graph that unifies enterprise structured and unstructured data and relationships, giving teams and AI a real-time view of how the business is operating.
Syntes delivers real-time and predictive analytics for teams and AI on live operational data, uncovering hidden relationships so insights remain grounded, explainable, and actionable.
Syntes enables agentics apps and agents to reason and act across enterprise systems using live context derived from the enterprise knowledge graph beyond chat-based copilots or brittle automations.
Syntes grounds analytics, AI, and decision-making in live enterprise data and knowledge graph context, ensuring every decision is instantly source-linked, explainable, auditable, and trustworthy.
Syntes connects enterprise systems and their structured and unstructured data via AI-native connectors into a live, two-way context layer, ensuring analytics and AI operate on relationship-aware data.
How Syntes Delivers Operational Intelligence
Live Context Graph Platform
A unified, continuously updated context layer that connects enterprise data, relationships, and operational state.
Runs Across Your Cloud Stack
Designed to operate across Google Cloud, Microsoft Azure, and AWS, connecting data and AI into a context layer.
Agents That Execute Work
Syntes powers agents with live context to automate analytics, predictions, & actions across systems with human oversight.
Industry-Specific Intelligence
Context models and insights tailored to how your industry actually operates.
Precision and Governance
Source-linked, explainable decisions with lineage, controls, and auditability built in.
Delivered by Proven Experts
Enterprise teams that help you go from platform to production quickly and safely.
Faster Data Insights
Data Analytics
Data Automation
Everyone says “get your data ready for AI.” But what does that actually mean?
Across industries, companies are racing to adopt AI. They connect new tools, add copilots, and launch pilots, but most still struggle to see real business impact. The reason is simple: their data is not ready.
AI fails at scale when it lacks live context, shared state, and decision traceability.
Enterprises are investing heavily in AI pilots, copilots, and models. Yet most fail to scale because AI operates without live enterprise context and a shared view of reality.
As enterprises move from AI assistance to AI execution, the context graph is emerging as the foundation for analytics, machine learning, and operational decision-making.
Copilots answer questions. Executable AI runs the business—and that requires a different foundation.
Most enterprises already use AI to summarize content and answer questions. These copilots deliver value, but they are only the first phase. The next phase—AI that can reason, decide, and execute—requires a fundamental shift in enterprise architecture.
Speed
Time to deploy live, cross-system agents
ROI
Measurable business impact, not pilots
Trust
Every actions is linked to the source data
Semantic Search 
Graph-Native Analytics 
Decision Execution 
Simulation & Forecasting 
Real-time Operational Memory & State 
Live Context Graph and Explainable Reasoning 
Decision Control, Lineage & Enforcement 
Governance & Security