T Textura

Glossary term

What is a knowledge base?

A knowledge base is a structured collection of documents with answers, product facts, regulations, scripts and standard solutions, used by people and AI systems. In the context of conversations it's also a source of context from which AI draws reliable information when processing calls and written exchanges.

Traditionally a knowledge base is a set of articles and instructions an employee or bot turns to in order to give an accurate answer. A good base turns a company's scattered knowledge into a single, up-to-date and searchable source rather than disparate files and "knowledge in the heads" of individual agents.

A special value in conversational analytics is assembling a knowledge base from the conversations themselves. Thousands of calls and exchanges already contain real customer questions, successful answers, objections and how they were handled, product and pricing facts. Extracting this knowledge and storing it in documents makes the archive self-documenting and turns agents' experience into a reusable asset.

For a business, a knowledge base solves two related tasks. The first is to speed up and standardize answers to people: a single source instead of conflicting versions. The second is to give AI systems reliable context: a voice agent, auto-tagging and data extraction need a grounding of the company's facts, otherwise they lean on the "market average."

A knowledge base is a key link in the "call → knowledge → AI training" loop: first knowledge is gathered from conversations, then the voice agent and automations are "fed" with it, and new conversations replenish and refine the base. Semantic search makes this base quickly accessible by the meaning of a query.

How it works in the platform

In the platform, the knowledge base is "Reference docs": markdown documents that plug into AI actions (auto-tags, free-form prompts, scripts) as context. An AI canvas helps fill documents with real data from records — metrics, topics, transcript fragments — turning the conversation archive into a living, up-to-date knowledge base.

Knowledge base

Related terms

Semantic search Semantic search is search by meaning rather than exact word match: it finds records close in meaning to the query even when they use different wording. It answers the question "what was the conversation about," whereas ordinary search looks for literal occurrences of phrases. Speech analytics Speech analytics is the automatic analysis of conversations (calls and written exchanges) to extract metrics, topics, tone and other data from what was said and how the dialogue unfolded. It turns recordings into structured data you can build dashboards on and make decisions from. LLM (large language model) An LLM (large language model) is an AI model trained on large volumes of text that can understand and generate natural language. It can answer questions, summarize, extract data and hold a dialogue, working with text as a flexible input and output.

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