Giga ML
UnclaimedAI agents for enterprise support that talk like humans and handle millions of calls.
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TL;DR - Giga ML
- Deploys highly customizable AI agents for enterprise support in two weeks.
- Utilizes Agent Canvas for building, governing, and scaling multi-modal AI agents.
- Provides Smart Insights to analyze conversations, identify root causes, and recommend KPI-driving actions.
Pricing: Paid only
Best for: Enterprises & pros
Pros & Cons
Pros
- Rapid deployment of AI agents (within two weeks)
- High degree of customization to match specific business needs
- Comprehensive platform for building, governing, and scaling AI agents
- AI-driven insights for continuous performance improvement and policy optimization
- Supports both chat and voice interactions for broad customer reach
Cons
- Specific pricing details are not publicly available
- Requires initial setup and training data for optimal performance
- The extent of integration capabilities with existing enterprise systems is not detailed
Key Features
AI agents for enterprise supportHuman-like conversational AIHandles millions of callsCustomizable agent behavior and policiesAgent Canvas for building and scaling agentsBuilt-in Copilot for agent creationMulti-modal support (Chat, Voice)Training document attachment for context
Pricing Plans
Enterprise
Contact us
- AI that talks like a human
- Handles millions of calls
- Solve your most complex support issues with AI
- Up and running in two weeks
- Extremely customizable
- Fine-tune every nuance to match your business
- Auto policy writing
- Built-in Copilot
- Agent Canvas
- Smart Insights
- Natural Voice
About Giga ML
By Toolradar Team·
Giga provides AI agents designed to solve complex enterprise support issues, capable of being deployed and operational within two weeks. These agents are highly customizable, allowing businesses to fine-tune every nuance to match their specific requirements and brand standards. The platform supports both chat and voice interactions, offering a multi-modal approach to customer service.
The core of Giga's offering is Agent Canvas, a tool for building, governing, and scaling enterprise AI agents. It enables users to define policies, design agent logic, and integrate training documents to ensure consistent and on-policy interactions. Additionally, Giga features Smart Insights, an AI-driven analytics engine that surfaces patterns, uncovers root causes, and quantifies the impact of support interactions, recommending actions to improve KPIs and revenue. This includes generating insights on resolution rates, identifying policy modifications, and suggesting knowledge gap improvements.
Giga is ideal for enterprises looking to automate and optimize their customer support operations, reduce deflection rates, and gain actionable insights from customer interactions. It aims to enhance support performance through AI-powered policy writing, performance enhancement suggestions, and dynamic conversation clustering.
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Giga ML FAQ
How does Giga's Agent Canvas facilitate the governance of AI agents across an enterprise?
Agent Canvas provides a structured environment to ground agents in brand standards, compliance rules, and workflows. This ensures every interaction is consistent and on-policy by allowing users to define policies, design logic, and monitor performance, thereby maintaining control over agent behavior at scale.
What kind of data can be used to train a Giga AI agent, and how is it integrated?
Users can attach various training documents and files to provide business context to their AI agents. This allows the agent to understand brand policies, workflows, and specific business information, ensuring relevant and accurate responses during interactions.
Beyond deflection rates, what specific KPIs can Giga's Smart Insights help improve for customer support operations?
Smart Insights is designed to help improve various KPIs beyond deflection rates, including resolution rate, escalation rate, and customer satisfaction. It achieves this by identifying patterns, uncovering root causes, and recommending policy modifications or knowledge gap improvements based on chosen success metrics.
How does the built-in Copilot assist in the creation of a new support agent within Giga?
The built-in Copilot acts as an AI assistant that helps users build their ideal support agent. It likely guides them through the process of defining policies, designing logic, and integrating necessary information, streamlining the agent creation workflow.
Can Giga AI agents handle multi-modal interactions, and what does that entail for customer engagement?
Yes, Giga AI agents are designed for multi-modal interactions, supporting both chat and voice. This allows for flexible customer engagement across different communication channels, providing a consistent and comprehensive support experience whether customers prefer typing or speaking.
What is the typical timeframe for deploying a Giga AI agent and having it operational for enterprise support?
Giga advertises that its AI agents can be up and running to solve complex support issues within two weeks, indicating a rapid deployment process for enterprise integration.
Source: gigaml.com