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Kredisco
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About Kredisco
Kredisco provides a credit scoring mechanism for AI agents by tracking and evaluating their actual performance rather than relying on self-reported claims. The system records receipts for each completed task, capturing metrics such as cost, latency, retries, and outcomes, which are then aggregated into a historical track record. Scores are generated by comparing an agent’s performance against benchmarks for similar tasks, ensuring that evaluations are contextually relevant. The tool integrates into existing agent workflows by wrapping API calls and logging interactions, allowing users to monitor and rank agents based on delivered results. It is designed for teams managing multi-agent pipelines where identifying underperforming agents is critical. The system operates independently of agent self-assessment, providing an objective measure of reliability and efficiency.
Key features
- Receipt-based performance tracking
- Cost and latency monitoring
- Retry and failure logging
- Task-class benchmarking
- Historical performance aggregation
- Multi-agent pipeline ranking
- API integration via Python
- Objective scoring independent of agent claims
Use cases
- Monitoring multi-agent pipelines for underperforming agents
- Evaluating agent reliability before deployment
- Ranking agents by actual delivered performance
Pros
- Tracks actual agent performance metrics
- Integrates with existing agent workflows
- Aggregates historical data for long-term scoring
- Compares performance against task-specific benchmarks
- Supports multi-agent pipeline monitoring
Cons
- Requires integration into existing agent calls
- No indication of free tier availability
- Limited to Python-based implementations
- Early-stage product with no public documentation
Frequently asked questions about Kredisco
What does Kredisco do?
Kredisco provides a credit scoring mechanism for AI agents by tracking their actual performance through receipts that log metrics like cost, latency, retries, and outcomes. It evaluates agents objectively by comparing their performance against benchmarks for similar tasks, independent of any self-reported claims.
Who is Kredisco designed for?
Kredisco is designed for teams managing multi-agent pipelines where identifying underperforming agents is critical. It suits organizations that need an objective measure of reliability and efficiency in their AI agent workflows.
How does Kredisco integrate with existing agent workflows?
Kredisco integrates by wrapping API calls and logging interactions, allowing users to monitor and rank agents based on delivered results. It operates by tracking receipts for each completed task, which are then aggregated into a historical track record.
How are scores generated in Kredisco?
Scores are generated by comparing an agent’s performance metrics against benchmarks for similar tasks, ensuring evaluations are contextually relevant. The system records receipts signed by the caller, not the agent, to ensure objectivity.
Can agents self-report their performance in Kredisco?
No, Kredisco does not rely on agent self-assessment. Every score is built from observed data, such as retries, failures, and deadlines missed, signed by the caller rather than the agent.
How do I get started with Kredisco?
To get started, users can sign in with GitHub and begin tracking agent performance by wrapping existing API calls. The system opens a file and starts scoring once integrated into the workflow.
