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AI Chatbot Solutions

Custom AI chatbots that answer from your approved knowledge with citations, take actions through your business systems and escalate to humans when confidence is low. Built for customer support, lead qualification, employee help and product guidance. Deploy on your website, messaging platforms or internal portals.

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What is an AI chatbot solution?

An AI chatbot solution is a custom-built conversational assistant that answers questions from your approved knowledge base, cites its sources, takes actions through your business APIs and hands off to a human when it cannot resolve the query confidently. Unlike generic chatbot platforms, a custom chatbot is trained on your domain language, constrained by your business rules and integrated with your CRM, ticketing and order systems. It is measured on containment rate—the percentage of conversations it resolves without human escalation—and on answer quality, not just on whether it can produce a response.

Support agents answer the same questions repeatedly

Password resets, return policies and order status consume agent time. A chatbot resolves these instantly with cited answers.

Website visitors leave without finding what they need

Search alone is not enough. A chatbot guides users to the right product, document or action through conversation.

Lead qualification is manual and slow

Sales reps spend time on unqualified leads. A chatbot qualifies based on criteria, books meetings and routes hot leads.

Employees cannot find internal information

HR policies, IT procedures and tool guides are scattered. An internal chatbot retrieves and cites the right document.

How This Solution Can Be Built

Different situations call for different implementations. These are the most common variants.

Customer support chatbot

Answers from knowledge base, creates tickets, checks order status and escalates complex cases to agents.

Lead qualification chatbot

Asks qualifying questions, scores leads, books meetings and routes to sales—integrated with your CRM.

Employee help chatbot

Internal assistant for HR, IT and operations. Permission-aware retrieval from company systems with citations.

Product guidance chatbot

Helps customers choose products, compare options and find documentation through guided conversation.

How the System Works

From input to output, each step is engineered for a specific purpose.

1

User question

Customer or employee asks a question via website, messaging or portal

input
2

Knowledge retrieval

Relevant documents fetched from approved sources with permission filtering

data
3

Answer generation

Response composed from retrieved sources with citations to the original document

ai
4

Action check

If the request needs a business action, the system calls the right API (create ticket, check order, book meeting)

output
5

Confidence gate

If confidence is low, the chatbot escalates to a human agent with full context

control
6

Human escalation

Agent receives the conversation, retrieved sources, actions attempted and user details

human
7

Outcome logging

Resolution, satisfaction and corrections are logged for evaluation and improvement

feedback

Production and Enterprise Readiness

What makes this solution work in a real operating environment—not just in a demo.

Knowledge grounding

Every answer is grounded in retrieved documents with citations. No ungrounded claims.

Action controls

Business actions go through a tool layer with typed parameters, permission checks and approval gates.

Escalation

Configurable confidence thresholds route low-confidence queries to humans with full context.

Evaluation

Answer quality, containment and escalation accuracy are measured against evaluation sets.

Channels

Deploy on website, WhatsApp, Slack, Teams or internal portals with consistent answers.

How Success Is Measured

The right metrics depend on the solution. These are the measures that matter for this system.

Illustrative system view — metrics shown in the dashboard above are labelled examples, not client results.

Answer quality

Whether the response is correct, grounded and useful, measured against evaluation sets

Containment rate

Percentage of conversations resolved without human escalation

Escalation rate

Percentage of conversations handed to a human, and whether the escalation was appropriate

Response time

Time from question to first useful answer, at P50 and P95

Unanswered-question rate

Percentage of questions the chatbot could not address, flagged for knowledge gap review

View related case studies

Discuss Your Chatbot

Tell us the workflow, problem or system you want to improve. We respond with how we would approach it.

Discuss Your Chatbot

No finished technical specification required.

Frequently Asked Questions

How is this different from a generic chatbot platform?
A custom chatbot is trained on your domain language, grounded in your approved knowledge and integrated with your business systems. Generic platforms answer from the public internet. Custom chatbots answer from your content with citations, take actions through your APIs and escalate to your agents with full context. The containment rate is higher because the knowledge is yours.
Can the chatbot create tickets or check order status?
Yes. The chatbot connects to your CRM, ticketing and order systems through a controlled tool layer. It can create support tickets, check order status, process returns and book meetings. Each action has defined permissions and may require human approval for high-stakes operations.
What happens when the chatbot does not know the answer?
If confidence is below the configured threshold, the chatbot escalates to a human agent. The agent receives the full conversation, the retrieved sources, the actions attempted and the user's details. The unanswered question is logged and flagged for knowledge gap review so the system improves over time.
Can it work on WhatsApp and Slack as well as our website?
Yes. The same chatbot logic deploys across website, WhatsApp, Slack, Teams and other messaging platforms. Answers are consistent because they come from the same knowledge base and the same retrieval pipeline. Context is shared across channels.
How long does it take to build and deploy?
A production chatbot with knowledge grounding, integrations and evaluation typically takes four to eight weeks, depending on the number of knowledge sources, integration complexity and evaluation requirements. A pilot can be ready in two to three weeks to validate the approach.
Do we need clean knowledge base content before starting?
No. Knowledge readiness is part of the engagement. The system can work with content as it exists today and improve as content is refined. The ingestion pipeline handles chunking, embedding and metadata extraction automatically.