What is AI chatbot development?

It is building a chatbot that understands questions in plain language and answers from your own data. That includes the model, the retrieval over your documents, the links to your systems, and the handoff to a person. The Eona.ae WhatsApp chatbot and the Agent22 onboarding assistant are two examples we built.

How much does AI chatbot development cost?

Projects start from $20K, scope-driven. Five things set the price: how long the build runs, its features and integrations, the size of the team, your timeline and priority, and the level of polish. Calls and scoping are free until you get a proposal. See the pricing page for how we get to a fixed number.

How long does it take to build an AI chatbot?

A focused chatbot usually takes 3 to 5 months. Our Eona.ae WhatsApp chatbot took 3 months and the Agent22 assistant took 4. Larger scopes with many documents or systems take longer. A 7-month build, like the Manual Minds assistant, is not unusual for multimodal documents.

Will the chatbot make things up?

Any model can. We reduce it by answering from your documents, showing sources, scoring confidence, and sending low-confidence cases to a person. Before launch we test on your own questions and share the results.

What is the difference between a chatbot and an AI agent?

A chatbot answers questions. An agent also takes actions in your systems, such as updating a record. Many teams should start with a chatbot and add actions later. Our post comparing an AI agent with a chatbot walks through the choice.

Can the chatbot run on our own infrastructure?

Yes. We can deploy in your cloud account or on your own servers, so documents stay with you. Our post on a private AI chatbot for company documents covers the options. Scope and cost depend on the model and hosting you choose.

AI Chatbot Development

AI chatbot development that answers from your data

We build AI chatbots for customer support, internal knowledge, and technical manuals. They answer from your own documents and systems, hand hard cases to a person, and run on the channel your users already use. Our WhatsApp chatbot at Eona.ae now handles about 90% of support queries, as reported by the client. You own the code.

Book Strategy Call See Chatbot Case Studies

Engagement · Scope

Fixed price. Shipped in 3 to 5 months.

What you get

Answers from your own data
Human handoff with full context
Tested on your own questions
Works on WhatsApp, web, and Slack

Timeline

3 to 5 months

Typical scope

1 to 5 integrations

Payback

Modeled before you sign

Live chatbots in productionIncluded

Human handoff built inIncluded

You own the codeIncluded

Why it matters

Why Most Business Chatbots Disappoint

A chatbot is easy to demo. These are the gaps that show up in real use:

Answers That Sound Right but Are Wrong

A model with no grounding in your documents guesses. It sounds sure of itself even when it is wrong, and customers act on it.

No Link to Your Systems

A bot that cannot see orders, tickets, or policies can only give generic replies. People then ask for a human anyway.

A Dead End When It Cannot Help

When the bot gets stuck, the customer should reach a person with the full conversation attached. Most bots drop that context.

Nobody Measures It After Launch

Without a test set and monitoring, quality drifts as documents and products change. You find out from angry customers.

What we build

Custom AI Chatbot Development ServicesFour kinds of chatbot we have built and shipped, for clients including Halal CS, Chatsi, Kanto and StrideIQ:

1 · Customer Support Chatbots

Replies in Seconds, Handoff When It Counts

Chatbots on WhatsApp, web, or your helpdesk, in the languages your customers use
Delivered: a WhatsApp chatbot in English and Arabic at Eona.ae, connected to live order and delivery data
Confidence scoring, so low-confidence cases go to a person
Full conversation history carried into the handoff

2 · Internal Knowledge Chatbots

Your Policies and Docs, Searchable by Chat

Answers from Google Workspace, Slack, Notion, and your own documents
Delivered: an onboarding assistant for Agent22 that respects each person's access rights
Every answer points to its source, so staff can check it
Access rules follow each person's existing permissions

3 · Technical and Research Assistants

Cited Answers From Long Documents

Questions answered from text, tables, and diagrams in the source files
Delivered: a manual assistant that cites the page, and a research assistant over 50,000+ academic papers
One knowledge base per machine, product, or team where answers must not mix
Retrieval built on RAG, tested on your own questions

4 · Guided Advice Chatbots

Clear Guidance, With a Path to an Expert

Chatbots that ask follow-up questions, then give plain guidance
Delivered: a legal guidance chatbot for InPro AI with a route to attorneys
Guardrails on what the bot may and may not say
Review loops, so people check a share of conversations

What we measure

What we measureset against your baseline in discovery

Every engagement is scoped to a fixed price and an outcome you can measure, not billable hours.

Support

About 90%

of queries automated at Eona.ae

Result

Onboarding

12 to 4 weeks

at Agent22

Result

Delivery

3 to 5 months

from kickoff to production

ResultSee case studies

The comparison

THE EDGEFIRM DIFFERENCE

Unlike chatbot platforms:

Built around your data and systems
You own the code and the data
No per-seat or per-conversation fees

Unlike generic chatbot agencies:

Engineers who write the code are on your calls
Fixed price for a defined scope
Accuracy tested before launch

Unlike DIY with an API key:

Grounding, handoff, and monitoring included
Edge cases handled before users find them
Evaluation set built from your own questions

Common questions

Common Questions About AI Chatbot Development

: It is building a chatbot that understands questions in plain language and answers from your own data. That includes the model, the retrieval over your documents, the links to your systems, and the handoff to a person. The Eona.ae WhatsApp chatbot and the Agent22 onboarding assistant are two examples we built.
: Projects start from $20K, scope-driven. Five things set the price: how long the build runs, its features and integrations, the size of the team, your timeline and priority, and the level of polish. Calls and scoping are free until you get a proposal. See the pricing page for how we get to a fixed number.
: A focused chatbot usually takes 3 to 5 months. Our Eona.ae WhatsApp chatbot took 3 months and the Agent22 assistant took 4. Larger scopes with many documents or systems take longer. A 7-month build, like the Manual Minds assistant, is not unusual for multimodal documents.
: Any model can. We reduce it by answering from your documents, showing sources, scoring confidence, and sending low-confidence cases to a person. Before launch we test on your own questions and share the results.
: A chatbot answers questions. An agent also takes actions in your systems, such as updating a record. Many teams should start with a chatbot and add actions later. Our post comparing an AI agent with a chatbot walks through the choice.
: Yes. We can deploy in your cloud account or on your own servers, so documents stay with you. Our post on a private AI chatbot for company documents covers the options. Scope and cost depend on the model and hosting you choose.