AI chatbot development

AI Chatbot Development Company for AI-Powered Conversations and Workflows

Build AI chatbots that connect your business knowledge, customer context, and workflows to answer questions, complete approved actions, and hand off to your team when needed. From RAG and system integrations to guardrails and monitoring, tkxel engineers conversational AI for real-world use.

featured AI CLIENTS

Are customer expectations outpacing
your support capacity?

72%

of service operations professionals say data readiness is a major blocker to AI, showing how fragmented, inconsistent, or inaccessible data can slow production deployments.

74%

of consumers are frustrated when they have to repeat their information across interactions, exposing the cost of disconnected channels, customer data, and service handoffs.

55%

of customer service leaders are handling higher customer volumes with no increase in staffing, putting more pressure on existing teams to keep response times and service quality from slipping.

AI chatbot development services across the full build lifecycle

AI chatbot development

Chatbot discovery and scoping

We analyze support tickets, chat logs, call notes, knowledge sources, and workflows to identify high-value chatbot use cases. The output defines priority conversations, required data and integrations, escalation paths, and measurable targets for resolution, task completion, and handoff.

AI chatbot development

Conversation design and intent modelling

We map dialogue flows, fallback paths and escalation triggers for every ranked intent. Conversation design covers disambiguation prompts, multi-turn slot filling and the exact wording the chatbot uses when it cannot answer.

AI chatbot development

Custom chatbot development

We build the chatbot application, the orchestration layer and the admin console your team uses to update responses. Prompt templates, routing logic and response policies stay editable without a developer release.

AI chatbot development

RAG and knowledge base engineering

We prepare and structure your help center, product documentation, policies, and other knowledge sources for reliable retrieval. We configure chunking, embeddings, search, and reranking strategies so the chatbot can ground responses in relevant business content and surface supporting sources where required.

AI chatbot development

Voice and multilingual chatbot development

We add speech-to-text (STT) and text-to-speech (TTS) layers for voice channels, plus language detection and per-language retrieval. Tone and terminology are tuned separately for each supported language.

AI chatbot development

Chatbot integration and workflow automation

We connect the chatbot to your customer relationship management (CRM) system, ticketing tool, order database and payment gateway. Read access answers account questions, and scoped write access completes actions like status updates.

AI chatbot development

Guardrails, evaluation and QA

We build a held-out question set with approved answers, then gate every release on accuracy, refusal and escalation thresholds. Input filters, output policies and topic boundaries constrain what the chatbot answers.

AI chatbot development

Chatbot support and retraining

We monitor containment, escalation and accuracy monthly, then retrain on the queries the chatbot handled worst. Knowledge base changes are re-indexed so answers track your current documentation.

AI chatbot types built around real business use cases

Customer service chatbots

Customer service chatbots handle routine questions, retrieve relevant information, and help customers complete common service requests. When an issue requires judgment or additional support, the conversation can be passed to an agent with the available context.

Use cases: order status, returns and exchanges, billing questions, password resets, shipping policies, warranty claims, appointment changes.

Knowledge assistants

Knowledge assistants help customers or employees find answers across product documentation, policies, procedures, and other approved business content. Retrieval-augmented generation can be used to ground responses in relevant source material.

Use cases: policy lookup, product specification search, contract information retrieval, onboarding questions, standard operating procedure guidance, internal knowledge search.

Transactional chatbots

Transactional chatbots connect conversations to business systems and APIs so users can complete approved actions without leaving the interaction. Permissions, confirmations, and audit controls can be applied based on the sensitivity of each workflow.

Use cases: booking changes, subscription renewals, order placement, appointment scheduling, address updates, refund requests, account changes.

Sales and lead qualification chatbots

Sales chatbots engage prospects, answer common questions, collect qualification information, and route relevant opportunities into your sales workflow. They can connect with customer relationship management systems and scheduling tools to reduce manual follow-up.

Use cases: visitor qualification, demo scheduling, pricing questions, budget and timeline capture, campaign follow-up, event lead capture.

Employee support chatbots

Employee support chatbots provide conversational access to internal knowledge and routine HR, IT, and finance workflows. They can retrieve policies, guide employees through common requests, and create or route tickets when further support is required.

Use cases: leave and benefits questions, expense policies, IT access requests, payroll queries, equipment requests, onboarding support.

Voice AI assistants

Voice AI assistants let customers and employees interact with AI through natural spoken conversations. They can combine speech recognition, conversational AI, business-system access, and human handoff for use cases where voice is the preferred channel.

Use cases: customer service calls, appointment confirmations, call routing, field service assistance, accessibility support, callback triage.

Not sure where an AI chatbot fits in your business?

We’ll help you identify the conversations and workflows worth automating first, then map the data, integrations, and controls needed to take the right use case into production.

Our AI chatbot development process

01

01 Discovery and scoping

We identify the conversations and workflows where an AI chatbot can create the most value, then define users, knowledge sources, system dependencies, human handoffs, and success measures.

Deliverables: prioritized use cases, requirements, data and integration map, success metrics

02 Conversation and solution design

We define how the chatbot should understand requests, maintain context, retrieve information, complete actions, and escalate when needed. The architecture is shaped around the use case rather than forcing every chatbot into the same technical pattern.

Deliverables: conversation flows, solution architecture, knowledge strategy, integration requirements

03 Chatbot and knowledge layer development

We build the conversational experience and configure the appropriate knowledge and retrieval approach, which may include RAG, search, structured data, APIs, or a combination. Models are selected based on quality, latency, cost, security, and the capabilities the use case requires.

Deliverables: working chatbot, configured knowledge layer, model and orchestration setup

04 Integration and workflow automation

We connect the chatbot with the systems required to move conversations beyond answers, from customer relationship management and service platforms to internal databases, APIs, and business workflows.

Deliverables: system integrations, tool and API connections, workflow logic, access controls

05 Evaluation and staged rollout

We test the chatbot against representative conversations and failure scenarios, evaluating response quality, retrieval, task completion, guardrails, escalation behavior, and performance before widening access.

Deliverables: evaluation results, issue remediation, rollout plan, production-ready release

06 Monitoring and continuous improvement

After launch, we track how the chatbot performs and improve the areas that need attention. Updates may include knowledge refreshes, retrieval tuning, prompt and routing changes, workflow improvements, guardrail adjustments, and model changes where appropriate.

Deliverables: performance monitoring, optimization backlog, knowledge updates, ongoing improvements

Our AI chatbot development process

step 1

Discovery and scoping

We identify the conversations and workflows where an AI chatbot can create the most value, then define users, knowledge sources, system dependencies, human handoffs, and success measures.

Deliverables: prioritized use cases, requirements, data and integration map, success metrics

step 2

Conversation and solution design

Deliverables: conversation flows, solution architecture, knowledge strategy, integration requirements

step 3

Chatbot and knowledge layer development

Deliverables: working chatbot, configured knowledge layer, model and orchestration setup

step 4

Integration and workflow automation

We connect the chatbot with the systems required to move conversations beyond answers, from customer relationship management and service platforms to internal databases, APIs, and business workflows.

Deliverables: system integrations, tool and API connections, workflow logic, access controls

step 5

Evaluation and staged rollout

Deliverables: evaluation results, issue remediation, rollout plan, production-ready release

step 6

Monitoring and continuous improvement

Deliverables: performance monitoring, optimization backlog, knowledge updates, ongoing improvements

Which AI chatbot development
approach fits your business?

Comparison of 3 AI chatbot buying paths across 6 decision criteria, including the failure condition for each path.

CRITERION

Speed to get started

Customization

Integration flexibility

AI and engineering expertise required internally

Control over architecture

Ongoing management

Best fit

OFF-THE-SHELF PLATFORM

Usually fastest for standard use cases

Best within platform capabilities

Strong for supported connectors and APIs

Lower

Primarily determined by the platform

Platform administration and vendor management

Standard chatbot needs with limited customization

IN-HOUSE BUILD

Depends on available internal skills and capacity

High

Depends on internal engineering capacity

Highest

Owned internally

Teams with established AI and engineering capability

Development partner

Faster than building a team internally, but varies by scope

High, based on business requirements

Designed around required systems and workflows

Shared with the delivery partner

High, within the agreed solution architecture

Can transition in-house or continue as a managed engagement

Businesses needing custom workflows, integrations, or AI engineering without building the full capability internally

The last row is the honest one. A tkxel build depends on source content, so a project
with no usable documentation starts with a content phase before any chatbot work begins.

Core capabilities behind the AI chatbots we build

The architecture depends on what the chatbot needs to know, access, and do. We combine the right conversational, retrieval, integration, and control capabilities around each use case.

Retrieval-augmented generation (RAG)

Connect approved business knowledge to the chatbot so responses can be grounded in relevant documents and supporting sources surfaced where needed.

Intent recognition and routing

Identify what users are trying to accomplish and route requests to the right knowledge source, workflow, tool, or human support path.

Context and conversation memory

Maintain relevant context across multi-turn conversations so users do not have to repeat information unnecessarily.

Human escalation and handoff

Define when the chatbot should involve a person and pass available conversation context into the handoff.

System and API integration

Connect the chatbot with CRM, service, commerce, scheduling, and internal systems so conversations can move beyond answers into approved actions.

Multilingual support

Support conversations across required languages, with retrieval, terminology, and response behavior configured for each use case.

Voice AI

Add speech recognition and text-to-speech capabilities for phone, kiosk, field, and other voice-based interactions where required.

Guardrails, evaluation, and analytics

Apply response policies, permission controls, evaluation frameworks, and performance monitoring to track quality, task completion, escalation, and other relevant metrics.

AI chatbot use cases across industries

Financial services
Healthcare
Retail and ecommerce
Logistics
Real estate
Software and IT

AI chatbots can give customers faster access to account, product, and service information while applying the permissions, escalation paths, and controls required for the use case.

Answer account, transaction, and product questions through authorized data access
Guide customers through card, loan, and service application processes
Collect fraud, dispute, and service requests and route them into existing workflows
Escalate sensitive or regulated interactions to the appropriate team with conversation context

Healthcare chatbots can automate administrative conversations and make it easier for patients to access information and services while supporting applicable privacy, security, and governance requirements.

Book, confirm, and reschedule appointments
Answer billing, coverage, and administrative questions from approved information sources
Collect intake and pre-visit information
Send appointment, medication, and follow-up reminders where appropriate

AI chatbots can support shoppers before and after purchase by connecting product information, order data, and service workflows in one conversational experience.

Answer product, availability, order, and delivery questions
Guide customers through returns and exchanges
Provide product recommendations based on available catalog and customer context
Initiate approved refund, replacement, or order-service workflows

AI chatbots can give customers and operations teams conversational access to shipment information, documentation, and service workflows.

Provide shipment status and updated delivery information
Answer shipping and customs documentation questions
Collect damage, shortage, and delivery exception reports
Support pickup scheduling and exception-related customer communications

AI chatbots can respond to property inquiries, qualify prospective buyers or tenants, and connect routine conversations with scheduling and property-management workflows.

Answer questions about listings, availability, amenities, and property details
Qualify buyer and tenant inquiries based on defined criteria
Schedule viewings through connected calendars
Capture maintenance requests and route qualified leads to the appropriate team

AI chatbots can give customers and employees conversational access to product knowledge, technical support, and routine IT workflows.

Answer setup, configuration, and product questions from approved documentation
Guide users through common access, licensing, and troubleshooting requests
Create or update support tickets from within the conversation
Identify recurring unanswered questions that may indicate knowledge-base gaps

What businesses can achieve with AI-powered customer service

Lower customer service costs

Reduce cost to serve by 20–30% by automating routine interactions, expanding self-service, and reducing dependence on agent-led support for every request.

Faster issue resolution

Service teams using AI agents expect case resolution times to improve by around 20%, helping customers get answers and complete common requests faster.

Higher customer satisfaction

Improve customer satisfaction by 15–20% through faster, more contextual, and more consistent customer interactions.

Greater support capacity

Handle more routine conversations through AI-powered self-service while giving support teams more time for complex cases, exceptions, and interactions that require human judgment.

More efficient customer service teams

Use conversational AI to reduce repetitive work, surface relevant knowledge, and automate common service workflows, improving productivity without requiring support capacity to grow at the same rate as demand.

Ready to scope your chatbot?

Book a chat discovery call

Success Stories in Spotlight

50% faster discovery with an AI-powered knowledge sharing agent

AgricultureArtificial Intelligence

View case study

"I’m going over testing feedback about the chatbot; overall, testers found the product to be fantastic. We’re very happy with this."

Chris Head

Director of IT, CCOF

60% reduction in response times through AI-automated email workflows

Hospitality & TravelArtificial Intelligence

View case study

WATCH TESTIMONIAL

Don Sgouridis

CIO, BBJ Latavola

50% reduction in support workload with AI-powered document retrieval

AgricultureArtificial Intelligence

View case study

"tkxel built an AI assistant that delivers accurate guidance fast and reduces manual work."

Director of Operations

Why businesses choose tkxel for AI chatbot development

Start focused, then scale what works

With 18+ years of technology delivery experience, we help businesses start with one high-value conversation or workflow, validate performance and business value, then expand into additional use cases, channels, and integrations based on results.

AI engineering beyond the chat interface

Backed by engineers across AI, data, cloud, and software engineering, we bring together conversational AI, RAG, integrations, workflow automation, and product engineering so your chatbot can do more than generate responses.

Security and controls built in from the start

As an ISO 27001-certified technology partner, we design access permissions, data boundaries, human handoffs, guardrails, governance, and monitoring into the solution from the beginning rather than adding them after deployment.

Built to work with your existing technology

With technology partnerships across Microsoft, AWS, andn Salesforce, we connect AI chatbots with the applications, data sources, APIs, and workflows your business already uses instead of forcing your operations into a one-size-fits-all platform.

Latest insights & resources

We’ve been recognized by the best, year after year

AMERICA’S FASTEST GROWING COMPANY

Top 15 inspiring workplaces for 2026

titan business PLATINUM award AI & AUTOMATION

FINANCIAL TIMES

mogul people leader

FORBES COACHES COUNCIL

ISO 27001 CERTIFIED

ISO 20000 CERTIFIED

ISO 9001 CERTIFIED

CMMI DEV 3 CERTIFIED

Identify the right chatbot opportunity for your business

“tkxel completely transformed the way we manage our customer relationships. Their customized CRM system streamlined our processes and improved customer satisfaction. We highly recommend their services to any business looking for real results.”

Nick Drogo

Global Director IT, Knowles

“They helped us build a docketing app with an intuitive user interface, allowing our attorneys to track over 10,000 U.S. and international patent systems.”

Robert K Burger

COO, Sterne Kessler

“tkxel has proven beyond par that they excel not just in building and integrating with our team but building at a level that is at par with any US development team. Working with tkxel is one of the best decisions we have made.”

Umair Bashir

CTO, Replenium

“tkxel shared our vision right from the get go, and helped us achieve the unthinkable through perseverance and a thorough attention to detail. Their team was highly professional and possessed a firm grasp on technicalities, a combination that is hard to find in the industry.”

Pam Chitwood

Product Manager, ABB

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Nick Drogo

Global Director IT, Knowles

“They helped us build a docketing app with an intuitive user interface, allowing our attorneys to track over 10,000 U.S. and international patent systems.”

Robert K Burger

COO, Sterne Kessler

Umair Bashir

CTO, Replenium

Pam Chitwood

Product Manager, ABB

Frequently asked questions

What does an AI chatbot development company actually deliver?

An AI chatbot development company designs and builds the conversational experience, knowledge and retrieval layer, integrations, workflow logic, guardrails, evaluation framework, and monitoring needed to run the chatbot in production. The exact architecture depends on the use case. Some chatbots rely heavily on retrieval-augmented generation (RAG), while others combine APIs, structured data, business systems, and automated workflows.

How much does AI chatbot development cost?

AI chatbot development costs depend on the number of use cases, required integrations, knowledge complexity, channels, security requirements, and level of automation. A focused chatbot for one workflow costs significantly less than a multi-channel solution connected to several business systems. tkxel typically starts by scoping the use case and technical requirements before estimating the build.

How long does it take to build an AI chatbot?

A focused AI chatbot use case can typically move from discovery to a working release within weeks. More complex solutions involving multiple integrations, channels, workflows, or security requirements take longer. tkxel usually begins with a focused use case, validates it, and expands the solution based on results.

Can an AI chatbot answer using our internal documents?

Yes. Retrieval-augmented generation can connect an AI chatbot to approved internal documents, policies, product information, and other business knowledge. The quality of the responses depends on the quality, structure, accessibility, and freshness of the source content, so knowledge preparation and retrieval evaluation are important parts of the build.

What happens when an AI chatbot cannot answer confidently?

The chatbot can be designed to ask clarifying questions, provide a limited response, refuse unsupported requests, or escalate the conversation to a person. The appropriate fallback behavior depends on the use case, risk level, and type of information or action involved.

Should we buy a chatbot platform or build a custom AI chatbot?

An off-the-shelf platform can work well for standardized use cases with limited customization. Custom development becomes more valuable when the chatbot needs to connect with proprietary knowledge, business systems, workflows, permissions, or user experiences that a standard platform cannot easily support. The right choice depends on your requirements, internal capabilities, and long-term ownership model.

How can an AI chatbot support our security and compliance requirements?

AI chatbot solutions can be designed around requirements including access controls, data handling, auditability, human oversight, data residency, and industry-specific policies. The exact controls depend on your regulatory environment, technology stack, and the data the chatbot needs to access.

How is AI chatbot performance measured after launch?

Performance can be measured through metrics including response quality, task completion, resolution rate, escalation rate, customer satisfaction, latency, adoption, and cost per interaction. For RAG-based chatbots, retrieval quality and groundedness can also be evaluated to identify where knowledge, prompts, or retrieval logic need improvement.

AI Chatbot Development Company for AI-Powered Conversations and Workflows

featured AI CLIENTS

Are customer expectations outpacing your support capacity?

72%

of service operations professionals say data readiness is a major blocker to AI, showing how fragmented, inconsistent, or inaccessible data can slow production deployments.

74%

of consumers are frustrated when they have to repeat their information across interactions, exposing the cost of disconnected channels, customer data, and service handoffs.

55%

of customer service leaders are handling higher customer volumes with no increase in staffing, putting more pressure on existing teams to keep response times and service quality from slipping.

AI chatbot development services across the full build lifecycle

AI chatbot development

Chatbot discovery and scoping

AI chatbot development

Conversation design and intent modelling

AI chatbot development

Custom chatbot development

AI chatbot development

RAG and knowledge base engineering

AI chatbot development

Voice and multilingual chatbot development

AI chatbot development

Chatbot integration and workflow automation

AI chatbot development

Guardrails, evaluation and QA

AI chatbot development

Chatbot support and retraining

AI chatbot types built around real business use cases

Customer service chatbots

Knowledge assistants

Transactional chatbots

Sales and lead qualification chatbots

Employee support chatbots

Voice AI assistants

Not sure where an AI chatbot fits in your business?

Our AI chatbot development process

01

Our AI chatbot development process

Discovery and scoping

Conversation and solution design

Chatbot and knowledge layer development

Integration and workflow automation

Evaluation and staged rollout

Monitoring and continuous improvement

Which AI chatbot development approach fits your business?

Core capabilities behind the AI chatbots we build

Retrieval-augmented generation (RAG)

Intent recognition and routing

Context and conversation memory

Human escalation and handoff

System and API integration

Multilingual support

Voice AI

Guardrails, evaluation, and analytics

AI chatbot use cases across industries

What businesses can achieve with AI-powered customer service

Lower customer service costs

Faster issue resolution

Higher customer satisfaction

Greater support capacity

More efficient customer service teams

Ready to scope your chatbot?

Success Stories in Spotlight

50% faster discovery with an AI-powered knowledge sharing agent

Chris Head

60% reduction in response times through AI-automated email workflows

Don Sgouridis

50% reduction in support workload with AI-powered document retrieval

Start focused, then scale what works

AI engineering beyond the chat interface

Security and controls built in from the start

Built to work with your existing technology

Latest insights & resources

We’ve been recognized by the best, year after year

AMERICA’S FASTEST GROWING COMPANY

Top 15 inspiring workplaces for 2026

titan business PLATINUM award AI & AUTOMATION

FINANCIAL TIMES

mogul people leader

FORBES COACHES COUNCIL

ISO 27001 CERTIFIED

Are customer expectations outpacing
your support capacity?

Which AI chatbot development
approach fits your business?