Solution · 05
自律的意思決定システム
自ら判断し、行動するシステム。
手作業の介入なしに継続的に感知、判断、実行できるインテリジェントなシステムを構築します。
SIGNAL
ACTION
<5 ms
Decision-to-action loop
24/7
Always-on policy
AI + Rules
Hybrid decisioning
In-engine
No external orchestrator
Why this matters
自走し、適応するシステム
自律システムにはリアルタイムデータ、インテリジェンス、実行が密結合している必要があります。MonkDB はその三つをひとつの継続的なプラットフォームで提供します。
リアルタイムデータ + インテリジェンス + 実行
What you get
What MonkDB makes possible for 自律的意思決定システム
0101 / 04
Event-driven decision frameworks
React to events as they happen, not in scheduled batches.
0202 / 04
AI + rule-based decisioning
Combine deterministic policy with adaptive AI in the same path.
0303 / 04
Instant execution of actions
Trigger workflows, state updates, and downstream effects directly inside the engine.
0404 / 04
Continuous learning from outcomes
Outcomes feed back into the system, improving decisions over time.
How it works
Three steps, one continuous loop
SENSE
1Continuous signal capture
Events, transactions, and sensor data feed the decisioning loop in real time.
DECIDE
2Hybrid AI + rule evaluation
Models and policy run in the same execution path with full lineage.
EXECUTE
3Action in milliseconds
Approve, reroute, dispatch, or remediate from inside the engine. No orchestrator hop.
Decisions that took a workflow engine and three queues now happen inside MonkDB in single-digit milliseconds. Audit lineage is end-to-end.
Outcome in numbers
- 20×Faster decisions
- 0External orchestrators
- 100%Decisions with lineage
Other solutions