Turn AI into governed enterprise workers.
Identity, memory, planning, orchestration, execution, evaluation, and lifecycle management for enterprise AI agents.
10 Agent Types
Assistant
Role-aware conversational entry points
Domain
Experts in specific enterprise functions
Transaction
Execute bounded actions in enterprise apps
Research
Search, extract, reason over evidence
Planning
Decompose goals and manage dependencies
Critic / Verifier
Challenge assumptions and validate
Simulation / Optimization
Model scenarios and optimize
Builder
Create agents, tools, and software
Supervisor
Monitor and coordinate agent teams
Governance
Enforce policies and controls
Agent Properties
Agent Identity
Every agent has a unique identity, owner, version, scope, and lifecycle state.
Agent Memory
Short-term, long-term, and episodic memory with retrieval and context management.
Planning & Orchestration
Goal decomposition, task assignment, dependency management, and plan revision.
Tool Use
Governed access to APIs, databases, functions, and enterprise system actions.
Agent Collaboration
Structured delegation, specialist coordination, and conflict resolution.
Observability
Complete run traces, cost tracking, model usage, and performance metrics.
Evaluation
Functional, safety, security, groundedness, adversarial, and cost evaluations.
Lifecycle Management
Create, test, deploy, monitor, improve, quarantine, rollback, and retire.
“Agents may collaborate autonomously. Authority does not become autonomous.”