Dobby
Agents That Improve

Learning Loop

Every approval, rejection, and modification teaches your agents. Pattern detection captures organizational knowledge. Maturity scoring tracks agent growth from Novice to Expert.

Maturity Scoring

5 levels from Novice (1) to Expert (5). Score based on approval rate, quality, speed, and learning velocity.

Feedback Capture

Every human approval, rejection, or modification is captured as a learning signal for the agent.

Pattern Detection

Automatically detect recurring patterns from feedback cycles. Turn rejections into organizational knowledge.

Performance Trends

Track improvement over time with detailed analytics on quality, speed, and approval rates.

Key Capabilities

Automated feedback capture from approval workflows
5-level maturity scoring (Novice → Expert)
Pattern detection from human feedback cycles
Knowledge extraction from rejected/modified actions
Performance trend tracking and improvement insights
Organizational memory and best practices capture

How It Works

1

Agent acts

An agent proposes an action based on its current knowledge.

2

Human reviews

The human approves, rejects, or modifies the proposed action.

3

System learns

The feedback is captured and analyzed for patterns.

4

Agent improves

Future actions incorporate learned patterns and best practices.

Ready to get started?

Connect and manage AI agents with learning loop built in.