Twig AI

By combining production-grade retrieval-augmented generation (RAG) with a no-code Agent Studio and 30+ deep integrations, Twig enables support organizations to dramatically reduce response times, free agents for complex work, and scale support capacity without proportionally scaling headcount.

The platform's Agent Studio provides a complete environment for building, testing, and deploying custom AI support agents across multiple channels including web chat, email, Slack, and browser extensions all manageable from a single interface with one-click deployment.

Agents are trained on the organization's existing knowledge base, support documentation, product guides, and historical ticket data, ensuring that AI responses are accurate, contextually appropriate, and aligned with the company's specific product and policies.

Twig's RAG infrastructure is engineered to enterprise standards, incorporating ingestion debugging, synthetic data generation, and confidence scoring that lets agents self-evaluate response quality before sending.

This self-evaluation mechanism is critical for enterprise deployments where accuracy matters more than speed ensuring the AI escalates appropriately when confidence is insufficient rather than delivering uncertain or incorrect answers to customers.

The platform integrates natively with the tools support teams already use, including Zendesk, Slack, Confluence, Google Drive, OneDrive, PostgreSQL, and MongoDB enabling Twig to surface relevant context from across the organization's knowledge ecosystem when generating responses.

Built-in PII detection and automatic redaction protect customer privacy and support compliance requirements across jurisdictions, making Twig suitable for regulated industries handling sensitive customer data.