Twig Cuts Customer Support Response Times by 60% Using AI Agents
Twig, an AI-powered customer support platform, is helping B2B teams automate routine inquiries and reduce first-contact resolution times by 35% or more. The system uses retrieval-augmented generation (RAG) - a technique that grounds AI responses in a company's own data - to deliver faster, more accurate answers across email, chat, and in-app channels.
The platform trains on proprietary company data, allowing support agents to handle status lookups, troubleshooting, and customer questions without manual research. Teams report automating 50% or more of incoming tickets while keeping human agents in control of escalations and complex cases.
How It Works
Twig ingests data from 30+ sources including Google Drive, Confluence, Salesforce, Slack, and databases. It cleans noisy inputs with a synthetic data engine, chunks information for efficient processing, and screens for personally identifiable information to meet compliance requirements.
The platform detects customer intent in real time, generates personalized responses, and flags when human intervention is needed. A no-code playbook builder lets teams create custom agents for specific workflows - handling RFP responses or payment status checks without writing code.
Session memory keeps context across conversations. Feedback loops let the system improve based on agent corrections and customer ratings. Automated evaluations measure accuracy across seven dimensions.
Who It Serves
Twig targets SaaS, fintech, e-commerce, and tech companies with high support volumes. Support leaders said the system cut operational hours significantly and let teams scale without hiring.
One support leader said: "Boosted our first response rate by 35% effortlessly - AI drafts are a game-changer." Another noted the feedback loops make the system "smarter daily, no more digging through docs."
Recent Updates
The 2026 version adds multi-modal capabilities to process images and audio in support tickets. Enhanced API integrations allow real-time actions like updating customer records or checking payment status directly from the AI response. A new VR-based simulation tool trains agents on complex scenarios at scale.
Limitations
Pricing follows an enterprise model with custom quotes after a demo, which may be steep for early-stage startups. The platform performs best when input data is clean; messy or incomplete information requires manual fixes upfront.
Onboarding includes support, but more interactive video tutorials would speed setup. Edge cases occasionally need human review and adjustment.
Getting Started
Support teams interested in AI for Customer Support can evaluate how AI Agents & Automation apply to their workflows. Twig offers a demo to assess fit and pricing for your team's volume and data sources.
The platform holds a 4.8-star rating, with users praising speed, integrations, and productivity gains.
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