Operationalize industry-specific workflows, terminology, & decision models with configurable ontologies & context models.
Syntes uses AI-driven connectors and automation to assemble the exact operational context each workflow needs, enabling agents to search, analyze, predict, and execute with precision and governance.
Configure no-code apps and agents instantly
Answer any question with analytics and ML
Create and launch workflows with AI
AI generated reports and dashboards
Files | Emails | Videos | Images | + more
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
Ontology-Driven Intelligence Layer
Transform enterprise data, workflows, documents, & relationships into a continuously evolving intelligence layer.
Connects Across Enterprise Systems
Unify cloud platforms, enterprise apps, market intelligence, & unstructured content into one operational context.
Trusted AI Agents That Execute
Power AI agents with live enterprise context to automate analysis, workflows, predictions, & governed actions.
Industry-Specific Intelligence
Operationalize industry-specific workflows, terminology, & decision models with configurable ontologies & context models.
Precision and Governance
Every insight, recommendation, & action is traceable to source data, relationships, policies, and operational lineage.
Delivered by Proven Experts
Expert teams & forward-deployed engineers that help you set up and deploy into 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
