Corthex
AI chatbot analytics dashboard for support conversations and handoffs

Corthex / Feature

Feature: analytics

Analytics that show what your AI assistant actually changes.

Corthex analytics connect conversation volume, leads, contacts, visitor history, usage, and unresolved topics so teams can improve both automation and human support workflows.

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Input

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Control

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Output

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Measure

Direct answer

AI chatbot analytics

A focused look at one operating layer inside Corthex.

Corthex analytics connect conversation volume, leads, contacts, visitor history, usage, and unresolved topics so teams can improve both automation and human support workflows.

Written for operators who need to measure ai support quality and business impact. Search intent: Learn about AI chatbot analytics in Corthex.

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See which topics generate support demand.

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Review conversation history and contact context.

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Track usage against plan limits.

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Use analytics exports for operations and reporting.

Citable facts

Concrete signals without the noise.

Short facts make the page easier to scan for buyers, operators, and search systems.

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Primary intent

AI chatbot analytics

Page type

Feature deep dive

Best fit

B2B support, commerce, developer, and operations teams

Corthex angle

Grounded answers, source context, staff control, and measurable workflows

Workflow

From source coverage to controlled customer answers.

The Corthex operating loop stays consistent, while the emphasis changes by page intent and audience.

Step 1

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Connect the knowledge that should ground the answer

Corthex indexes files, URLs, product context, and operational policies so the assistant has a controlled evidence layer before it ever speaks to a visitor.

  • Upload documents, paste text, or import URLs.
  • Chunk and embed content for vector retrieval.
  • Keep source names available for answer citations.

Step 2

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Answer with retrieval, page context, and tool policy

The assistant combines the user's message with relevant knowledge, current page context, and enabled tools such as commerce lookup or live site lookup.

  • Prefer exact source matches before general model knowledge.
  • Route unclear or risky questions to fallback behavior.
  • Show source-backed answers when evidence is available.

Step 3

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Escalate, measure, and improve the coverage loop

Human teams can take over live conversations, review unresolved questions, and turn gaps into new knowledge sources or better prompts.

  • Use staff handoff for high-intent or complex conversations.
  • Track questions, leads, contact history, and usage.
  • Improve source coverage from real support demand.

Buyer intent

Why teams search for AI chatbot analytics

Teams usually reach this page when a generic chatbot is no longer enough. They need an assistant that can answer from controlled knowledge, cite what it used, and hand off to people when confidence, compliance, or revenue risk demands it.

  • Replace ungrounded answers with retrieval-backed responses.
  • Make product, policy, and support content usable inside chat.
  • Keep operators in control of escalation and improvement loops.

Corthex approach

Measurement should improve the assistant, not just decorate a dashboard.

Corthex analytics are tied to conversations, contacts, bots, sources, and handoff state so teams can turn support patterns into knowledge updates and process changes.

  • Knowledge ingestion keeps the answer surface tied to current sources.
  • Page context and live lookup reduce stale responses on public sites.
  • Staff console and analytics close the gap between automation and support quality.

Corthex structure

Built for clear customer answers

Each Corthex page uses a direct answer, fact table, workflow, comparison framing, related questions, and structured data. That gives buyers, operators, and AI assistants clear passages to understand and reuse.

  • Short answer block near the top of the page.
  • Specific feature facts instead of vague slogans.
  • Internal links that make the Corthex platform map easy to follow.

FAQ

Questions this page should answer clearly.

What makes Corthex useful for AI chatbot analytics?

Corthex combines retrieval-augmented generation, source citations, embeddable chat, staff handoff, analytics, and APIs so teams can deploy assistants without losing control of answer quality.

Can Corthex answer from existing knowledge sources?

Yes. Corthex can ingest documents, URLs, and pasted text, then retrieve relevant chunks when a visitor asks a question. Storefront and widget flows can also include page context.

Can a human take over when the AI should not answer?

Yes. Corthex includes staff handoff workflows so support teams can pause the bot, continue the conversation, and preserve the full context for follow-up.

Does Corthex support developer integrations?

Yes. Corthex exposes API keys, REST endpoints, streaming chat, embeddable widgets, webhook-related workflows, and connector surfaces for production integrations.