Connect your systems, data, and documents to power trusted AI applications and AI agents that automate business operations, improve decision-making, and help teams accomplish more. Built with enterprise-grade governance, explainability, and security. Deploy your first AI application in weeks, not months.
How a graph-native ontology layer transforms siloed enterprise data into live, relationship-rich context graphs, giving AI agents and AI-applications the situational intelligence to discover, reason, and transact with near-zero hallucination at enterprise scale.
Syntes combines live context graphs, graph-native analytics, and AI agents to deliver more accurate answers while dramatically reducing AI operating costs.
Deliver more reliable answers for complex enterprise questions, analytics, and decision-making.
Reduce LLM costs while improving response quality and scalability.
Ground every answer in enterprise data, relationships, and source references.
Deploy applications, analytics, and AI agents in weeks, not months.
Build AI applications powered by live enterprise knowledge and context. Deploy, manage, and scale intelligent applications across teams and workflows on a shared platform with enterprise-grade security, governance, and explainability built in. Deploy in weeks, not months.
Learn MoreContinuously assembled from ERP, CRM, files, and field signals, your operational truth, kept current and queryable in real time.
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Run analytics, ML, and LLM-driven reasoning directly over the graph, with semantics, lineage, and policy intact.
Learn MoreDeploy AI agents that extend your AI applications with autonomous reasoning and execution across enterprise systems, operating within your governance and business rules.
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Every recommendation and action carries lineage, policy, and reversibility, so AI behaves the way your reviewers expect.
Learn MoreBi-directional connectors let agents read, act, and write back across your stack, no rip-and-replace required.
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Search. Analyze. Predict. Execute.
Faster context assembly across enterprise data than manual stitching.
More context delivered to every AI agent, model, and analytical workflow.
Faster time-to-action when insight needs to become governed execution.
One foundation that unifies structured data, documents, and relationships into a continuously updated graph.
Deploy in AWS, Azure, or GCP, with native connectors into your existing data and application platforms.
Compose policy-bound agents that move from analysis to action under approval and audit.
Domain semantics for life sciences, financial services, retail, construction, and more, out of the box.
Policy gating, lineage, and full audit on every decision, so trusted AI is the default, not the exception.
A team that has shipped enterprise data and AI at scale, partnering closely from first deployment to production.
Native, bi-directional integrations across the systems you already run.
Enterprise interest in AI has never been higher. Boards expect results. Executives fund pilots. Teams deploy copilots, dashboards, and models across functions. Yet despite this momentum, most enterprise AI initiatives...
Enterprise AI has reached a turning point. While organizations have made progress with analytics platforms, dashboards, and AI copilots, most still struggle to operationalize AI in ways that meaningfully impact...
From Copilots to Executable AI: What Changes in the Enterprise Architecture Most enterprises are already using AI. They summarize documents. They answer questions. They generate content. These systems—often called copilots—are...
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...
One unified stack, from data sources at the foundation to decision execution at the surface. Every layer governed, every action traceable.
See Platform OverviewAutomate, optimize, and scale with autonomous AI agents built on your industry and company-specific knowledge graph.
