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Automate customer service with AI-driven response solutions.

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Overview

Portkey is a production stack designed for GenAI builders, centralizing LLM access, governance, observability, prompt management, caching, and cost controls through a unified API and developer SDKs. It aims to streamline the development and management of GenAI applications by providing a comprehensive platform for LLM orchestration and governance.

Key Features:

  • Unified AI Gateway for accessing over 1,600 LLMs.
  • Real-time observability dashboard for monitoring LLM behavior and managing usage.
  • Automated PII redaction for sensitive data.
  • Real-time performance and cost monitoring with budget limits.
  • Comprehensive platform including AI Gateway, Guardrails, Governance, and Prompt Management.
  • MCP Gateway for managing MCP servers.

Use Cases:

  • Building and deploying GenAI applications.
  • Monitoring and managing LLM performance and behavior.
  • Optimizing AI infrastructure costs.
  • Ensuring data privacy and security in LLM interactions.

Benefits:

  • Focus on building by abstracting LLM management.
  • Proactive management and early anomaly detection.
  • Significant cost savings and optimized resource allocation.
  • Rapid integration with existing stacks using minimal code.

Capabilities

  • Automates responses to frequently asked customer questions
  • Resolves customer inquiries, achieving up to 70% resolution without human intervention
  • Provides instant answers to customer questions in under 6 seconds
  • Performs task automation such as checking order statuses and creating support tickets
  • Recommends products directly from integrated Shopify inventories
  • Manages customer support across multiple live communication channels
  • Responds to customer queries in multiple languages, including English, Spanish, French, German, and Portuguese
  • Integrates seamlessly with existing support solutions through Lyro Connect
  • Continuously learns and updates its knowledge base as business data grows
  • Notifies support agents when human assistance is specifically requested
  • Analyzes customer queries to deliver human-like responses
  • Adapts and improves response accuracy through interaction-based learning
  • Monitors and evaluates AI agent performance in real-time for optimization
  • Customizes behavior and responses to align with brand guidelines
  • Automatically builds a knowledge base by scraping and analyzing support content
  • Generates support tickets for inquiries beyond its knowledge base

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