Why agent projects stall
Model access is becoming easier. The hard part is turning agent work into bounded, reviewable production work that can survive provider and policy changes.Pilots do not scale by themselves
A handful of prototypes can run on scripts, notebooks, or cloud-specific services. A portfolio of production agents needs shared runtime primitives.
Models are replaceable
Small, cheap, specialized, and frontier models will keep changing. The platform keeps the agent contract stable while provider choices evolve.
Production needs proof
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.
How Duale AI fits in your stack
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.One runtime, three operating views
Submit bounded work with a deadline. The runtime returns a terminal result, and each team reads the signals available for that project.For platform leads
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.
For information technology leaders
Turn scattered pilots into a portfolio with cost visibility, provider choice, and a clearer path from business demand to operated software.
For security and governance
Review data movement, subprocessors, retention, and incident paths from project-specific evidence instead of a separate after-the-fact narrative.
What the platform provides
The product boundary is the agent runtime: the stable layer between your application, your providers, and your operational controls.Stable contracts
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.
Model routing
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.
Durable execution
Treat agent work as production work: stateful, retry-aware, and visible through the signals the integration captures.
Proof points
Clear enough for a first review, without pretending the platform is more mature than it is.Python first
The supported developer path today is Python: contracts, deadlines, typed results, runtime events, and provider choices for production agent work.
Managed in Germany
Managed application data is hosted in Germany today. Subprocessors and transfer posture are documented in the legal pages.
Trust Center
Security posture, certification status, subprocessors, contacts, and requestable review inputs are summarized without unsupported badge claims.