Artian delivers multi-agent AI solutions to enterprises.

Our ground-breaking Autonomous Workflow Agent Planner generates control graphs for agentic workflows instead of unmanaged code. These graphs enable the creation of risk-sensitive use cases that have the right balance between deterministic reliability and AI magic.

Artian’s Agentic Execution Harness and Multi-Agent Exchange enable governed agent orchestration. Also included are an AI-native interaction console with React UI components, a full-fledged CLI, Python/Typescript SDKs, shared AI skills, finance-specific integrations, and more.

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WORKFLOW AGENTS

Achieve objectives

Define goals for your business process using natural language as it is normally used by people in your domain. Our Workflow Planner guides you through goal clarification and other best practices. Then it generates structured or dynamic plans and composes a multi-agent solution with a system of Artian Workflow Agents. These agents are then lifecycle-managed and deployed to your chosen environment.

The agents execute task control graphs, which invoke standard or proprietary AI models and domain-specific skills. Data lineage and AI model governance is a key focus here. During execution, the Planner tracks progress towards the goals and replans as appropriate. The agents interacts with human supervisors seamlessly and provides natural language-based visibility.

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PROVIDER AGENTS

Acquire capabilities

The capabilities of Workflow Agents are enhanced through Artian Exchange, which evaluates and selects Provider Agents for integrated use. All Artian Workflow Agents are available as Providers via the Exchange, without any extra effort. External experts can also be added.

A set of services that are offered via the Exchange enable engagement of such Providers. The Exchange facilitates negotiation amongst agents to intelligently determine the value of relevant Providers with respect to a Workflow Agent’s goals. Artian’s infrastructure also manages the delivery of the engaged Provider’s outputs into the Workflow Agent’s execution context. It can also make recommendations on optimal allocation of a given budget for multi-agent collaboration.

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Works with your proprietary applications and your enterprise technology stack.

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    MCP

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    A2A

  • Black and white OpenAI logo.

    OpenAI

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    Anthropic

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    Gemini

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    Mistral

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    AWS

  • Blue letter 'A' Azure logo.

    Azure

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    GCP

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    OpenShift

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    Kubernetes

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    Docker

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    Redis

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    Mongo

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    PostgreSQL

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    RabbitMQ

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    Slack

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    Teams

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    Notion

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    Salesforce

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    ServiceNow

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    Playwright

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KEY DIFFERENTIATORS

planner

experience

predictable

reliability

conditional execution

via declarative

flow control

checkpoints

and rollbacks

for agent state management

out-of-the-box

task data

and memory

isolation

interactive

debugger

multi-agent

economics

Explore where Artian creates value.

If you’re evaluating where multi-agent AI systems  can drive the most impact, we’d be happy to help identify the right starting point for your workflows, teams, and operating environment.