---
title: "Production runtime for durable AI agents"
description: "Duale AI delivers a production runtime for durable Python AI agents, enforcing stable contracts, routing policies, deadlines, retries, and audit signals."
lang: en
lastUpdated: 2026-06-07
url: https://duale.ai/en/home
---

## AI-generated summary

The page describes Duale AI’s production runtime for durable AI agents, detailing stable input/output contracts, model routing, deadlines, retries and audit signals that let pilot agents scale to production‑ready workloads, and shows how platform leads, IT leaders and security/governance teams can use it.

- Pilots cannot scale alone; production agents need shared runtime primitives like stable contracts, routing policy, deadlines, and retry behavior.
- Models are replaceable; Duale AI keeps agent contracts stable while routing policy selects among providers like OpenAI, Anthropic, AWS Bedrock, Microsoft Foundry, and Vertex AI.
- Three views: platform leads build agents with stable contracts and routing; IT leaders see cost and provider choices; security/governance review data movement and retention.
- Managed zone runs router, task state, retries, recovery and logs runtime and audit events; configured zone holds policies, deadlines and retention expectations by the customer.
- The Trust Center offers data‑processing agreement requests, hosting details, security contacts and the list of German‑hosted subprocessors for security and audit teams.

Summaries were generated by AI. Generative AI is experimental.

---

<Hero
  title={
    <>
      Production runtime for <AccentText>durable AI agents</AccentText>
    </>
  }
  subtitle="Duale AI helps platform teams move one bounded Python agent path from pilot to production: stable input and output contracts, provider routing policy, deadlines, recovery behavior, and review inputs tied to what the integration captures."
  primaryCta={{ label: "Review a production path", dialog: "contact" }}
  secondaryCta={{ label: "Explore the Python SDK", href: "https://duale.ai/en/solutions/developers.md" }}
/>

<Section
  title="Why agent projects stall"
  subtitle="Model access is becoming easier. The hard part is turning agent work into bounded, reviewable production work that can survive provider and policy changes."
>
  <CardGrid columns={3}>
    <Card title="Pilots do not scale by themselves" icon="rocket">
      A handful of prototypes can run on scripts, notebooks, or cloud-specific services. A portfolio of production
      agents needs shared runtime primitives.
    </Card>
    <Card title="Models are replaceable" icon="layers">
      Small, cheap, specialized, and frontier models will keep changing. The platform keeps the agent contract stable
      while provider choices evolve.
    </Card>
    <Card title="Production needs proof" icon="check">
      Platform, business, security, and audit teams need the same view of task identifiers, errors, policy inputs, and
      cost signals that each project actually captures before agent work reaches production.
    </Card>
  </CardGrid>
</Section>

<Section
  title="How Duale AI fits in your stack"
  subtitle="Submit work with a deadline. A typed result returns later. Your apps bring the task, your model provider remains selectable where supported, Duale runs orchestration, and your team owns policy."
>

```mermaid
flowchart LR
    %% WHAT: Context view of three outer zones with Configured and Managed sub-zones inside Duale.
    %% WHO: Mixed home-page visitor: business sponsor, platform lead, and governance reviewer before discovery.
    %% WHY: Shows what runs where and what stays customer-owned.
    %% NOT: Real-time chat loop, customer-managed deployment, admin console, or long autonomous-run claim.
    accTitle: Duale AI platform context and containers
    accDescr {
      Your Python code submits work via the Duale AI SDK. Inside Duale,
      the Configured zone holds routing policy, deadlines, identity scopes,
      and retention expectations your team owns. The Managed zone runs the
      router, task state, retries, runtime events, tenant isolation, and
      audit events where configured. Duale sends work to the model provider
      selected for the deployment. Results return asynchronously to your apps.
    }

    Apps(Your apps and Python code)
    subgraph Duale[Duale AI platform]
        subgraph Configured[Configured by your team]
            Policy(Routing policy, deadlines, identity scopes, retention expectations)
        end
        subgraph Managed[Managed by Duale]
            Orch(Router, task state, retries, recovery)
            Records(Runtime events, tenant isolation, audit events where configured)
        end
    end
    ModelProvider(Selected model provider)

    Apps <-.-> Duale
    Configured --> Managed
    Duale <--> ModelProvider
```

</Section>

<Band>
  <Section
    title="One runtime, three operating views"
    subtitle="Submit bounded work with a deadline. The runtime returns a terminal result, and each team reads the signals available for that project."
  >
    <CardGrid columns={3}>
      <Card title="For platform leads" icon="code" href="https://duale.ai/en/solutions/developers.md">
        Build Python agents on stable input and output contracts. Route models by policy, recover failed work, use task
        identifiers, and keep the deployment path understandable.
      </Card>
      <Card title="For information technology leaders" icon="bar-chart" href="https://duale.ai/en/solutions/business.md">
        Turn scattered pilots into a portfolio with cost visibility, provider choice, and a clearer path from business
        demand to operated software.
      </Card>
      <Card title="For security and governance" icon="lock-closed" href="https://duale.ai/en/solutions/governance.md">
        Review data movement, subprocessors, retention, and incident paths from project-specific evidence instead of a
        separate after-the-fact narrative.
      </Card>
    </CardGrid>
  </Section>
</Band>

<Section
  title="What the platform provides"
  subtitle="The product boundary is the agent runtime: the stable layer between your application, your providers, and your operational controls."
>
  <CardGrid columns={3}>
    <Card title="Stable contracts" icon="file-text">
      Define the work an agent can receive and the result it must return. The model, provider, timeout, retry behavior,
      and review policy can evolve around that contract.
    </Card>
    <Card title="Model routing" icon="mixer-horizontal">
      Use policy to decide when a smaller model is enough, when a stronger model is justified, and when an automated
      attempt should stop for project-specific controls.
    </Card>
    <Card title="Durable execution" icon="commit">
      Treat agent work as production work: stateful, retry-aware, and visible through the signals the integration
      captures.
    </Card>
  </CardGrid>
</Section>

<Section
  title="Proof points"
  subtitle="Clear enough for a first review, without pretending the platform is more mature than it is."
>
  <CardGrid columns={3}>
    <Card title="Python first" icon="code" href="https://duale.ai/en/solutions/developers.md">
      The supported developer path today is Python: contracts, deadlines, typed results, runtime events, and provider
      choices for production agent work.
    </Card>
    <Card title="Managed in Germany" icon="globe" href="https://duale.ai/en/legal/subprocessors.md">
      Managed application data is hosted in Germany today. Subprocessors and transfer posture are documented in the
      legal pages.
    </Card>
    <Card title="Trust Center" icon="reader" href="https://duale.ai/en/product/security.md">
      Security posture, certification status, subprocessors, contacts, and requestable review inputs are summarized
      without unsupported badge claims.
    </Card>
  </CardGrid>
</Section>

## Questions teams ask before putting agents in production

### What should we bring to a first production review

One bounded Python agent path: the task action and typed result, the deadline, the routing policy, and the model
    providers in scope. Duale AI handles task identity, routing, retries, and the terminal result; your integration
    brings the contract and the data movement the reviewers need to inspect.

### Does Duale AI replace our model providers

No. Duale AI is not a hidden bundled provider. You keep your accounts with OpenAI, Anthropic, AWS Bedrock, Microsoft
  Foundry, Vertex AI, and others; routing policy decides which one each task uses. Models stay replaceable, the agent
  contract stays stable.

### What does durable mean here

Durable here is the product category: the agent contract your application depends on stays stable while models,
  providers, and routing policy change underneath. Models can change; production contracts must not.

### Where should security and audit teams start

Start with the Trust Center. It is the entry point for the data-processing agreement request path, the hosting
  description, the security and incident contact channels, and links into the legal pages for the current subprocessor
  list.

### How is this different from an agent framework or starter pack

Different layer. Frameworks help you write an agent; starter packs scaffold one. Duale AI is the governed runtime
    layer around the agent work: routing policy, deadlines, retries, and a typed terminal result, on a contract that
    stays stable while providers and projects change. Make models replaceable and agents durable.

<Cta
  title="Plan the path from pilots to production agents."
  primaryCta={{ label: "Review a production path", dialog: "contact" }}
  secondaryCta={{ label: "See pricing model", href: "https://duale.ai/en/product/pricing.md" }}
/>

<JsonLd
  data={{
    "@context": "https://schema.org",
    "@type": "SoftwareApplication",
    name: "Duale AI",
    applicationCategory: "BusinessApplication",
    description:
      "Production runtime for durable AI agents with stable contracts, routing policy, deadlines, recovery behavior, and review inputs tied to current integrations.",
    operatingSystem: "Web",
  }}
/>

## Related content

- [Build Python agents with routing, retries, and task IDs](https://duale.ai/en/solutions/developers.md)
- [Role-based solutions for platform, business, and governance](https://duale.ai/en/solutions.md)
- [Turn AI pilots into a production portfolio](https://duale.ai/en/solutions/business.md)
- [Govern AI agents in production with shared operating signals](https://duale.ai/en/solutions/governance.md)
- [Pricing for reliable AI agent orchestration runtime](https://duale.ai/en/product/pricing.md)
- [Security Trust Center for production AI agents](https://duale.ai/en/product/security.md)

---

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