Klivvr Agent

How AI agents automate fintech operational workflows including compliance monitoring, fraud detection, dispute resolution, and regulatory reporting — with insights from Klivvr Agent deployments.

How to design effective human-in-the-loop workflows for AI agents, covering escalation policies, approval workflows, the autonomy ladder, and trust-building strategies.

Architecture patterns for multi-agent systems including supervisor topologies, agent-to-agent communication, task delegation, and shared state management in Klivvr Agent.

A practical guide to testing AI agents including unit testing tools, integration testing agent loops, evaluation frameworks, and mock LLM strategies used in Klivvr Agent.

A deep dive into patterns for orchestrating multiple AI agents in TypeScript, covering sequential chains, parallel execution, supervisor hierarchies, and workflow-based coordination.

A comprehensive technical guide to designing and implementing AI agents in TypeScript, covering agent architecture, tool integration, state management, and production deployment patterns.

How to implement safety guardrails for AI agents including input validation, output filtering, action limits, and prompt injection detection — with patterns from Klivvr Agent.

How to implement short-term and long-term memory for AI agents, covering conversation context management, vector stores for semantic retrieval, and session persistence patterns in Klivvr Agent.

A business analysis of deploying AI agents for customer support in fintech, covering cost reduction, response time improvements, customer satisfaction impact, and a framework for calculating ROI.

How to design effective tools for AI agents including parameter schemas, error handling, tool composition, and the patterns that make agents more reliable — with examples from Klivvr Agent.