Twig is an AI assistant that resolves customer issues instantly, supporting both users and support agents 24/7. It's built from the ground up for customer experience teams' unique needs, offering features like personalized AI, ecosystem data access beyond internal docs, and a built-in knowledge base. Twig also provides detailed analytics to drive agent productivity and offers fast deployments with minimal IT support. The platform is SOC 2 certified and offers various integrations, including in-app AI bots, web apps, browser extensions, and native apps for Zendesk and HelpScout. Twig also boasts features like AI navigation, response citations, and action-taking capabilities via API calls. It offers memory across chats and customization options for tone and style, along with the ability to remember edits to individual questions. Security features include Google SSO and enterprise SSO options, along with user group-level permissions. Twig also provides compliance and reporting features, including SOC 2 Type 2 compliance and reporting.
Features & Capabilities
—AI-powered customer support agent that resolves issues instantly.
—In-app AI bot for seamless integration within SaaS applications.
—Session memory for faster follow-up responses.
—Outlook native plugin for streamlined inbox support.
—Detailed analytics for enhanced agent productivity.
—Customizable AI with adjustable tone and style.
—API calling capabilities for automated actions.
—Built-in knowledge base for contextual responses.
Synthetic QnA generator for improved answer quality.
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—Multiple application interfaces including web app, browser extension, and native apps for Zendesk and HelpScout.
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✓Resolve 50%+ of technical issues without human involvement
Intelligent Escalation
Identify when human touch is needed and route appropriately
Example: Detect frustration, refund requests, or technical complexity → escalate to tier 2
✓Humans handle only complex cases, improving job satisfaction and resolution quality
Architecture
Customer support agents combine LLMs with knowledge bases, ticketing systems, and escalation logic to handle customer inquiries autonomously while knowing when to hand off to humans.
LLM Core
Large language model for understanding and generating responsesParse customer intent, generate contextual responses, maintain conversation flow
Knowledge Base Integration
Vector database with company docs, FAQs, product infoRetrieve accurate information to answer customer questions
CRM/Ticketing Integration
Connection to Zendesk, Intercom, or custom ticketing systemLog conversations, escalate to human agents, track resolution
Escalation Logic
Rules engine for when to transfer to human supportHandle complex cases, angry customers, or sensitive issues appropriately
Implementation Guide
Prerequisites
Structured knowledge base (docs, FAQs in searchable format)
API access to CRM/ticketing system
Defined escalation criteria and human-in-loop workflows
Test environment separate from production support
Steps
1Audit most common support tickets (top 20 questions)
2Build knowledge base with answers to common questions
3Set up LLM with RAG over knowledge base
4Integrate with ticketing system API for logging and escalation
