Local inference paths
Run selected speech, language, and decision components on the device or nearby infrastructure.
EDGE RUNTIME / DIFFERENTIATOR
Offline voice AI that keeps working when the cloud does not.
Build on-device and self-hosted voice agents with local inference, controlled data paths, and session continuity through network failures.
From a voice response to an operating system.
Cloud-only voice agents inherit the network as a single point of failure. In a factory, vehicle, public venue, secure facility, or robot, that assumption can turn a useful interface into an unavailable one. IronHeart.AI Edge Runtime is designed for systems that need a defined level of intelligence even when connectivity is degraded or absent.
Offline does not have to mean isolated forever. A deployment can divide responsibilities across device, edge server, private infrastructure, and cloud. Time-sensitive turn taking and essential state can remain local, while heavier processing or centralized updates synchronize when policy and connectivity allow. Teams choose the boundary based on latency, privacy, cost, and hardware.
State continuity matters as much as local speech processing. If a connection disappears midway through a task, the agent should not forget the user’s intent or restart the workflow. IronHeart.AI coordinates memory and orchestration so a supported local path can continue, defer a remote action, or communicate a clear limitation.
State continuity
Keep session intent and approved memory available through transient network failures.
Controlled synchronization
Queue or reconcile remote work when connectivity returns instead of silently dropping the task.
Fleet orchestration
Manage policies and runtime behavior across robots, kiosks, enterprise endpoints, and secure deployments.
Built for enterprise, government, and robotics constraints
Organizations can select hardware, models, and topology according to their own risk posture. A government facility may prioritize private routing; a robot may prioritize millisecond response; a field service device may prioritize power and intermittent synchronization. Edge Runtime provides a common architecture for those decisions without pretending every workload can run identically on every device.
Design begins by classifying functions into must-run-local, may-run-remote, and unavailable-offline groups. Teams then assign latency budgets, storage limits, encryption requirements, model sizes, and recovery behavior to each group. A network-loss test should interrupt real tasks at different moments, including before and after an external action. The agent must communicate what completed, what is queued, and what requires reconnection. This disciplined partitioning avoids the vague promise that everything works offline and produces a system whose degraded modes can be understood, tested, and supported.
IronHeart.AI Runtime brings realtime voice, memory, governed knowledge retrieval, agent orchestration, and edge deployment into a common execution layer. Explore the runtime architecture, review Robotics Brain, or compare options in pricing.
FAQ
Questions before you build.
Is every feature available fully offline?
No. The offline feature set depends on local hardware, selected models, data, and integrations. The architecture defines graceful behavior for unavailable remote capabilities.
Can it be self-hosted?
IronHeart.AI supports private and edge deployment patterns; the exact topology is designed for the customer environment.
What happens when the connection returns?
Approved queued actions and state can synchronize according to conflict, security, and retention policies.
Is offline voice useful only for robots?
No. It is relevant to kiosks, industrial systems, vehicles, secure facilities, government environments, and enterprise endpoints.