Agent Configuration
Configure the AI agents that power each phase of your assessment.
Architecture Overview
Friender uses a multi-agent architecture where specialized agents handle different phases of the assessment process. Each agent type has configurable parameters that affect how it collects data, identifies patterns, and generates recommendations.
For most assessments, the default configurations work well. Enterprise customers may want to fine-tune agent behavior to match specific organizational constraints or compliance requirements.
Agent Types
Observation Agents
Phase 1Configure data collection agents that connect to your tools and observe operational patterns.
Diagnosis Engine
Phase 3Tune the pattern matching engine that identifies bottlenecks and AI opportunities.
Deployment
Phase 4Configure and deploy purpose-built AI agents based on assessment recommendations.
Configuration API
Agent configurations can be managed through the dashboard or programmatically via the API. All configuration changes are versioned and audited.
GET /v1/assessments/:id/agents
PUT /v1/assessments/:id/agents/:type/config
POST /v1/assessments/:id/agents/:type/restartSee the API Reference for full endpoint documentation.