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Enterprise Layer Intelligence
Categories/AI Orchestration and MLOps/Synnada
Synnada

Synnada

Founded by Mehmet Ozan Kabak & Samican Tandogdu in 2021

Build and deploy persistent agent systems for production data science workflows

Pricing model

Demo

Rating

★ Mixed Reviews

Time to value

Requires Expertise

You can use Synnada to build production-grade infrastructure for running persistent AI agents at scale. It includes Mithril, a compiler that prepares ML models for efficient execution; Tenet, which handles multi-cloud deployment of AI workloads; and Agentia, a runtime for persistent agent systems with built-in code execution. Together these components let teams run continuously operating decision systems across clouds and datasets, replacing one-off analyses with agents that reason, act, and coordinate over time.

What Synnada does

Compile ML models for efficient production deploymentDeploy AI workloads across multiple cloud providersRun persistent agents that reason and act continuouslyCoordinate agent systems across datasets and decision loopsExecute code within agent reasoning pipelinesMonitor and maintain long-running intelligent decision systemsIntegrate agent runtimes with existing data infrastructureAgentia runtime runs persistent agents continuously without manual restartsMithril compiles ML models for faster, more efficient production executionTenet deploys AI workloads across multiple cloud environmentsBuilt by core contributors to Apache DataFusionAgents can execute code natively as part of reasoning loopsSupports long-running decision systems designed to operate for yearsCombines reasoning, code execution, and ML into one agent runtime

Pricing breakdown

Pricing model: Book a demo

Tutorials & Demos

Frequently asked

Apache DataFusion

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Synnada, Agentia, Mithril, Tenet, agentic AI, persistent agents, ML compiler, multi-cloud AI deployment, Apache DataFusion, AI infrastructure, agent runtime, data science automation, agent-native systems, production ML, AI decision systems