Sense signals and events
Observe business state and external change, initiating or adapting work when relevant conditions emerge.
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GEA Architecture
Long-Horizon Agent Runtime
Keep work moving toward long-horizon goals and outcomes.
Continuously sense enterprise and external signals, manage goals, plans, and durable state, and adapt the next action to intermediate results. Work can span multiple interactions and workflows, pause, resume, and retry—while remaining under human oversight and enterprise guardrails.
How It Works
Keep goals continuous across interactions and systems.
The runtime extends a conversation into long-running execution: sensing change, initiating action, maintaining state, using tools, and bringing people in when judgment is needed.
Manage goals and durable state
Preserve goals, plans, dependencies, and execution state across interactions so work can pause and resume.
Use skills and enterprise tools
Connect existing systems through Agent Skills, APIs, MCP, and events to take real business action.
Evaluate, recover, and escalate
Adapt to intermediate results, retry or recover from failure, and escalate high-risk moments for human judgment.
One complete run
How one question becomesa traceable enterprise decision.
In a product innovation task, models, context, runtime, and enterprise foundations operate as one sequence—not isolated modules.
Example task / Input
Redesign the opening experience of a chocolate gift box within defined cost and brand constraints.
Task result / Output
A sourced report, an approved direction, and decision memory written back.
Active phase
Frame the task
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Initiate
A product innovation question enters
The business objective and constraints become a durable task.
Capabilities in action
Intent understandingDurable task
Validation & Guardrails
Proactive does not mean uncontrolled.
Long-running reliability goes beyond retry. It depends on where state is checkpointed, whether external actions can be replayed safely, and when execution must stop and return to people.
Validated state checkpoints
Checkpoint goals, inputs, intermediate results, and external-system state at consequential steps, then validate where execution should resume.
Safe retries and failure compensation
Separate safely replayable actions from external effects that require compensation, avoiding duplicate publishing, writes, or notifications.
Authorization, escalation, and stops
Set explicit thresholds for low confidence, value judgments, and consequential actions so work pauses, requests approval, or stops when required.
Connected Technology
Every capability,working as one system.
Explore the technologies that provide enterprise memory, task evaluation, and governance for long-running work.
01
GEA Architecture
Context System
Turn enterprise knowledge into durable memory agents can understand and use.
Learn more02Enterprise Agent Foundation
Agent Reliability & Evaluation
Make long-running work observable, measurable, and recoverable.
Learn more03Enterprise Agent Foundation
Security & Governance
Keep every action within identity, access, and accountability boundaries.
Learn moreTechnical questions
Understand the mechanism, boundaries, and production requirements.
01
How is a Long-Horizon Agent Runtime different from a fixed workflow?
Fixed workflows suit tasks whose steps and branches can be defined in advance. A long-horizon runtime supports work whose path changes with new evidence, intermediate outcomes, and external events. It preserves goals and state, then adapts the next action within constraints instead of pre-writing every case.
02
Which tasks are a good fit for a Long-Horizon Agent Runtime?
It is best suited to work that runs over time, spans systems, requires repeated judgment, and changes direction as intermediate results arrive. When steps are fully deterministic, short-lived, and context does not evolve, conventional automation is usually simpler.
03
How do runtime state and the Context System differ?
Runtime state tracks where one task currently stands, including its goal, plan, dependencies, and intermediate outcomes. The Context System organizes enterprise knowledge, rules, relationships, and decision memory that can be reused across tasks. The runtime reads context to advance work, then writes validated outcomes back to complete the learning loop.
Ready when you are