TELCO

GenAI is calling

Equip your teams with AI assistants sporting never-before-seen accuracy and full chat history metrics.

Create AI assistants that drive right to the heart of relevancy

With Vectara’s end-to-end RAG platform, telecoms can embed GenAI quickly and easily without the risk of data or privacy violations — and without a data science or machine learning team.

Because gen AI democratizes access to powerful capabilities, any telco—a small operator or large incumbent—can reshape customer expectations and its organizational efficiency. Those at the forefront of this movement stand to position themselves to regain growth faster and capture a more significant share of the nearly $100 billion in incremental value.

McKinsey’s Technology

– Media & Telecommunications Practice

Features

Conversational history for your AI assistant

Making LLM’s better at conversation through history and relevance.

Vectara chat offers chat history that incorporates previous chat into context for a more intelligent response.

With RAG-as-a-service at its core, Vectara chat lets developers build an AI assistant with security and high relevance at a reasonable price.

Cross-lingual operation

Your users span languages and geographies; so should your AI.

Vectara breaks down every word into its meaning, enabling you to retrieve relevant information across languages and generate answers in any language.

This means users can ask a question in any language and get a response in any language, without losing response accuracy.

Advanced generation  for better RAG performance

Vectara’s Mockingbird generative model drives better relevance and context, lowering your support burden.

Mockingbird achieves the world’s leading RAG output quality, with leading hallucination mitigation capabilities, making it perfect for enterprise RAG and autonomous agent use cases.

Data never leaves Vectara’s environment and consistently outperforms major models like OpenAI’s GPT-4 and Google’s Gemini 1.5 Pro in RAG output quality, citation accuracy, multilingual performance, and structured output accuracy.

Use Cases

Agent support

AI assistants consolidate customer data and product info to improve support

R&D

Platforms that advance and simplify the development of new materials and designs across languages

Compliance

24/7 Q&A services that help navigate changing policies, regulations, and compliance

Agent training

Training platforms that upskill workers with recommendations based on historical data and employee insights

Success story

Maqsam

Maqsam, a call center automation company, has a highly technical team composed of some of Jordan’s best software engineers. See why they selected Vectara instead of taking a DIY approach to RAG.

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