AI chatbots / assistants

Development of AI chatbots and assistants for customer support and presales

Artificial intelligence in business today is no longer an experiment or a fashionable trend, but a real working tool. Companies that implement AI ahead of their competitors gain an advantage through unique solutions and services that are not available with standard approaches.

Today, AI chats and assistants have become fully integrated products that advise customers, answer their questions, qualify requests, and create tickets, leads, and briefs. They are connected to websites, applications, personal accounts, various messengers, and helpdesks in order to have an effective and reliable virtual assistant at hand.

How an AI assistant works in practice: what it can do

• automatically creates a lead, ticket or brief;
• answers based on the knowledge base and shows the source;
• unlike a regular chatbot, it can perform other actions besides text responses (search, suggest, calculate, recommend);
• understands the client's intentions and asks clarifying questions;
• transmits a signal to the operator if there is a risk/uncertainty;
• writes logs and provides analytics on requests.

Business effect of an AI assistant

Artificial intelligence for business is not just a trend or an experiment. An artificial intelligence chatbot can positively affect efficiency, quality, and scalability. In addition, it automates routine processes, relieves the team of workload, guarantees stable quality of customer responses, and gives businesses real results that can be seen after the first weeks of implementation. Below are more advantages why you should start working with AI assistants now.

1. Reducing the load on the support service. AI tools process typical requests: consultations, statuses, rules and instructions. Thus, the load on operators is reduced, and they are involved in the work in cases where a human solution is required.
2. Prompt response to customer requests. The user instantly receives the first response to their request — at any time and regardless of the number of simultaneous requests or high load.
3. Strict adherence to standards. AI chatbots and assistants work according to established rules. This has a positive effect on reducing errors and preventing discrepancies in responses from different operators.
4. Automatic data collection and structuring. The assistant collects information and stores it by parameters: budget, deadline, contacts, product or region. Thus, the operator immediately receives data ready for processing - without the need for manual sorting.
5. Integration with business systems. Smart chatbots work directly with CRM, helpdesk, catalogs, ERP, analytics. They create leads and tickets, check statuses, and transfer information without copy-pasting.
6. Monitoring the effectiveness of support and presales processes. With the help of AI tools, you can see real numbers: how many requests were resolved automatically, where the load is increasing, which topics are repeated, how the response speed is changing.
7. Scale without having to expand your team. Automated assistants can handle many customer calls. Even if your user base grows significantly, you don’t need to hire new agents and spend additional budget.
8. Price calculation and selection of the optimal solution. The AI assistant can also pre-calculate the cost of certain services or products if you enter parameters: tariff, volume, terms, region, configuration, etc. Thus, the client immediately sees the optimal offer, and the manager's help is not required.
9. Formation and sending of commercial offers and documents. The virtual assistant is able to generate commercial offers, make calculations, create presentations or other types of documents according to a certain template. Subsequently, he sends the finished file to the client in a convenient format for him - PDF, email, CRM. As a result, the path from the user's request to the agreement with him is shortened.
10. Recommendations like a personal consultant. By analyzing the history of requests, customer behavior and scenarios, artificial intelligence is able to recommend services, products, tariffs or upsell solutions as if a live expert would do it, not just a static FAQ.

Metrics that the AI assistant improves:

• deflection rate (how many calls were resolved without an operator);
• first response time;
• CSAT/NPS (if applicable);
• conversion to lead/meeting;
• speed of triage and ticket routing.

Where the assistant actually works (channels)

An AI assistant works where customers interact with your solution. It provides a prompt response to the user, collects information about the request, and thus automates a routine process that an operator would perform manually. An AI assistant can be connected to a website or smartphone, as well as to various messengers, in order to improve the customer experience, reduce the workload of the team, and speed up the processing of requests. We describe different types of AI assistant integrations and explain how they work in these channels.

Website widget

In this case, the assistant works directly on the website and responds to visitors' requests in real time. It is used for consultations, pre-sales, collecting contacts and creating leads in CRM.

Web-office / SaaS

When integrated into a personal account or SaaS product, the assistant helps users understand the functionality. It answers “how to” questions, minimizes the support workload, and captures events for analytics.

Mobile app (in-app chat)

By connecting an AI assistant to a mobile app, it can provide support to customers without having to switch to other channels. In addition, the intelligent assistant can help with statuses, navigation, settings, and overall user retention.

Telegram / WhatsApp

An assistant that works in messengers handles customer requests in the place where they prefer to communicate. Such an AI assistant is suitable for operational consultations, information gathering, transferring requests to internal systems, and bookings.

HelpDesk / email intake

The AI assistant independently receives requests from email or helpdesk, classifies them, and creates tickets with the necessary fields. This speeds up triage, reduces manual processing, and improves routing between teams.

Who is most suited to using an AI assistant?

You can use an intelligent assistant in any business that needs to quickly and accurately process user requests, as well as collect a large amount of information and automate workflows. Artificial intelligence assistants are actively working in various industries: from e-commerce and SaaS to clinics and service companies. They have already successfully helped many businesses increase the efficiency of workflows, reduce the workload on employees and speed up the response to client requests. We will tell you in more detail in which areas and how smart assistants work.

• E-commerce. The AI assistant advises customers on products, answers questions about delivery, payment, or returns. It also independently creates tickets and leads for managers. This speeds up the purchase process and reduces the load on the support service.
• SaaS. In SaaS products, an AI assistant provides answers to customers about features, settings, and possible integrations. A smart assistant can suggest how to perform certain actions in the system, help them learn how to use the product faster, and also record all events for analytics.
• Logistics. In this area, the AI consultant reports on the delivery status, route, rate and timing. If a certain problem arises, it can automatically create a ticket. Thus, the response time to the user is reduced, and the work of the support service is optimized.
• Production. An intelligent assistant can be used in production to provide advice on products, specifications, inventory, and delivery times. The AI assistant also tracks orders, communicates with managers, and gathers information about customer needs.
• Clinics: In healthcare settings, the assistant is used to answer patients’ questions about certain services, prepare for procedures, and schedule doctors. In addition, the digital assistant can create appointment reminders, relay important requests to staff, and collect past data.
• B2B services. Qualifying leads, responding to inquiries about terms of cooperation and rates, creating commercial offers and briefs for managers — all this is done by a digital assistant for B2B companies. This way, you can speed up pre-sales and increase conversion into deals.
• Marketplaces. An AI assistant helps buyers and sellers answer questions about shipping, purchases, and returns. It also collects information about the most popular queries and shares it with the marketplace to improve its performance.
• Education/online courses. In the education sector, an intelligent assistant answers various questions students have about courses, class schedules, assignments, and access to materials. It also provides step-by-step guidance on the platform, helps teachers with learning analytics, and tracks user progress.
• Developers and PropTech. An AI assistant provides clients with real estate advice, talks about prices, layouts, and properties. It independently collects inquiries for the agent, processes applications, and generally improves communication with potential buyers and tenants.
• Service companies. Team efficiency and reducing customer waiting time are important for service companies. AI assistant helps with these key tasks: it seamlessly responds to a large number of customer requests, records services, transfers these requests to CRM, and optimizes task routing.

Most often, we are approached by companies that have outgrown manual request processing and want to scale their service and sales without proportionally growing their team. We help build AI assistants that support current processes rather than disrupt them.

When using an AI assistant is NOT appropriate

• there is no knowledge base and it is impossible to prepare one;
• legal obligations are required without human verification;
• business is not ready for escalation regulations;
• high-risk communication “only human”.

Typical application scenarios

AI assistants are actively used in various business areas and processes. Below, we demonstrate structured universal scenarios for using a digital assistant: from customer support and pre-sales to in-product assistance, mobile applications and document management. Each scenario describes specific actions of the assistant, data sources, integrations, business impact and the limits when human intervention is required.

Customer Support Assistant

Bottom line: Resolves typical support requests.
What does: answers the FAQ, explains processes and rules, provides links to sources, clarifies the details of the problem, creates a ticket (if necessary), updates the status of the request.

Data: knowledge base, regulations.
Integrations: helpdesk, CRM.
Effect: deflection rate increases, FRT decreases.
AI stop: conflict, compensation, uncertainty.

Pre-Sales Qualification Assistant

Bottom line: Qualifies a potential client.
What does: clarifies needs, checks product compliance, explains the options, collects contact information, forms a brief, creates leads in CRM.

Data: catalog, conditions, cases.
Integrations: CRM, calendar.
Effect: conversion to lead/meeting.
AI stop: non-standard requirements.

Assistant for 2D/3D configurators

Bottom line: helps gather requirements.
What does: asks follow-up questions, explains options, checks compatibility, forms technical specifications, transfers for sale.

Data: configurator, rules.
Integrations: ERP, CRM.
Effect: fewer errors, faster calculation.
AI stop: complex exceptions.

Mobile App Assistant

The bottom line: support + retention.
What does: responds to requests, explains the possibilities, reminds of actions, helps you navigate navigation and settings, records interactions for further analytics and optimization.

Data: knowledge base.
Integrations: app analytics.
Effect: retention.
AI stop: personal questions.

E-commerce Product Selection Assistant

Bottom line: helps you choose a product.
What does: clarifies needs, filters the directory, compares options, recommends, checks for availability.

Data: catalog, warehouse.
Integrations: CMS, ERP.
Effect: conversion, fewer bounces.
AI stop: controversial cases.

In-product Assistant

Bottom line: it helps within the system.
What does: explains functions, suggests steps, answers the question "how to do it", warns about common mistakes, directs to the desired section, records events.

Data: documentation.
Integrations: analytics.
Effect: Onboarding.
AI stop: system errors.

Ticket Triage & Routing Assistant

Essence: classification of appeals.
What does: determines the topic of the appeal and its type, assesses priority and level of urgency, routes the request to the appropriate command or queue, creates a ticket with filled fields and context, detects duplicate or related requests, adds a short summary of the problem for the operator.

Data: history of requests.
Integrations: helpdesk.
Effect: faster triage.
AI stop: critical incidents.

Document / Policy Q&A Assistant

Essence: answers to requests from internal and public documents.
What does:

• searches for relevant fragments in contracts and regulations;
• cites the source of the answer with a link to a specific document or section;
• explains the rules in plain language without adjusting the content of the document;
• helps to find the desired item or condition at the user's request;
• compares wording from different documents within the permitted rules;
• records the requests that most often require escalation.

Data: contracts, policies, regulations, instructions.
Integrations: optional. The assistant can work autonomously only with a document database, but if necessary, integrates with a DMS, corporate repository, or knowledge portal.
Effect: less workload.
AI stop: legal interpretations.

Example with non-standard price calculation: "I want to order 500 units of a product with individual packaging and delivery to several different countries. How much will it cost?". AI assistant actions:

• determines that this is a non-standard price miscalculation, so it does not provide the client with the exact amount on its own.
• selects relevant rules, policies, and base rates to prepare the context.
• creates an escalation and transfers the request to the competent person who generates the final settlement.

If one of these scenarios applies to your business, the CortexIntellect team will help you design, develop, and implement an AI assistant tailored to your processes — with integrations, human-in-the-loop control, and measurable KPIs.

Examples of real questions (intents)

We provide examples of real user queries that the assistant responds to in order to demonstrate its focus on specific business scenarios rather than general conversations.

Support (delivery/payment/return/status)

• Where is my order now?
• When to expect delivery?
• How do I change my delivery address?
• Can you speed up delivery?
• Why hasn't my order shipped yet?
• How to track a shipment by track number?
• What payment methods are available?
• Why didn't the payment go through?
• Can I pay partly by card and partly in cash?
• How do I cancel a payment or get a refund?

Pre-sales (cost/timing/integration/suitable or not)

• How much does your service cost?
• Which tariff is best for our business?
• What are the implementation deadlines?
• Can your product be integrated with our CRM?
• Is the system suitable for e-commerce/SaaS/B2B?
• Is there a limit on the number of users?
• What support channels are included in the plan?
• What integrations with ERP or analytics are possible?
• Is multilingualism supported?
• Can I test the system before paying?
• How is the user team trained?

In-product (how to perform an action in the interface)

• How to create a new project in the system?
• Where can I find reports for the past month?
• How do I add a new user or access rights?
• How do I change my profile settings?
• How to create a brief or ticket within a product?
• How to connect an external service or API?
• How to export data to CSV/Excel?
• How do I restore a deleted item or record?
• How to track the status of tasks in the system?
• How do I activate my subscription or upgrade my plan?

Docs/Policies (terms/regulations/rules)

• What are the conditions for returning goods or services?
• Where can I find your personal data processing rules?
• How is a product warranty issued?
• What documents are required to receive compensation?
• What are the restrictions on using the service?
• How are tariffs and payment terms changing?
• Where can I view the privacy policy?
• What are the rules for escalating support requests?
• Can I transfer my account to another person?
• What are the security rules and restrictions for users?

A virtual assistant can be designed to meet the real needs of your business. It helps with both typical and more specific queries and provides accurate, structured answers. As a result, customers get the information they need in a timely manner, even in complex or non-standard situations.

Mini-scenarios (user flows)

How does an AI assistant work in practice? We demonstrate step by step, in real user interaction scenarios. Each flow reflects data collection, escalation logic, creation of leads, tickets or events in analytics. The development of an AI assistant is based on a clear request from your business, and not on general conversations.

Flow A: website → consultation → lead in CRM

1. The client asks a question.
2. The assistant clarifies needs and collects contact information and request details.
3. If the request is complex or the data is incomplete, escalate to a manager for manual review.
4. Based on the information received, a lead is created in CRM with all the details of the request.
5. The assistant transfers leads to the manager for future processing and communication with the user.

Flow B: support → answer + link to source → helpdesk ticket

1. The client sends a support request via chat, email, or form.
2. The AI assistant checks the knowledge base and collects data: the subject of the request, user ID, and history of previous requests.
3. If the confidence in the answer is low or the request is non-standard, a ticket is created in the helpdesk and escalated to an operator. If the confidence is high, the assistant provides the user with an answer with a link to the source.
4. All data and source references are recorded for analytics and knowledge base improvement.

Flow C: in product → prompt → action → event in analytics

1. Inside the product, the customer asks a question “how to perform an action” or clicks on the “hint” button.
2. The AI assistant collects information about user actions: context, steps, button presses, history of previous requests.
3. A smart chatbot provides step-by-step instructions: where to click and which fields to fill out.
4. If the client cannot perform the action, or a system error occurs, escalation occurs to an operator for manual intervention.
5. After successful completion of the action, the assistant creates an event in the product's internal analytics, records the completion of the request and user parameters.

Flow D: messenger → data collection → recording/booking

1. The user contacts Telegram, WhatsApp or another messenger regarding a consultation/appointment/reservation.
2. The artificial intelligence assistant collects information: name, contact details, desired time and service, additional parameters, for example, number of participants or product.
3. If this information is not enough, or the request is complex, escalate to the operator to clarify the details.
4. Using the collected data, the AI assistant creates an artifact: a record, booking, or lead in CRM.
5. The digital assistant notifies the user that a recording or reservation has been created and adds this data to the system for processing.

An example of a non-standard request with a price calculation: "We want to book three different services at the same time for 10 participants in different cities, is that possible?". Assistant actions:

• collects basic information and understands that this is a non-standard situation that requires manual intervention.
• creates an escalation to the operator with all the data collected to prepare an accurate record or booking.

How it works inside (AI-pipeline)

• AI chatbots and assistants determine intent and context;
• search for an answer in the knowledge base (RAG) and display the source;
• check the confidence (threshold);
• trigger an action via API, for example, create a ticket or lead, check status, record, formulate a brief (if necessary);
• call actions via API;
• transmit a signal to a person when a risk occurs;
• track logging and collect analytics.

Architecture and security

The architecture and security of an AI assistant determine how reliably and effectively it works in business processes. Below are key mechanisms and practices to consider when designing a digital assistant that affect security, access control, and stability when interacting with users:

• an isolated assistant environment that minimizes the risks of data leakage and guarantees secure communication with the client;
• role and access rights management - each employee has access only to the necessary functionality and data;
• personal data masking — users' personal data is hidden or encrypted in order to provide confidentiality and compliance with information protection standards;
• Audit and logs — all actions of the assistant and users are recorded in logs. This allows you to track events, check the correctness of work and analyze the causes of errors;
• test queries and negative scenarios make it possible to verify the stable operation of the system under any circumstances;
• Constant monitoring of the AI assistant allows you to keep control of its work in real time and quickly respond to failures.

Limitation and control (AI stop)

For an AI assistant to operate safely and responsibly, it is important to define clear boundaries for its actions. Here are scenarios where human intervention or additional verification is required to avoid risks and ensure correct decisions:

• Legal wording is always checked and confirmed by a human.
• Compensation/conflicts are resolved by the operator or other responsible person.
• Final prices without rules are never reported without verification and agreement according to standards.
• medical/financial advice (if relevant) is not given without the involvement of a competent professional.
• risky actions require operator confirmation.

How is the implementation of an AI assistant taking place?

Developing an AI assistant or chatbot is a systematic process that results in an AI solution for your business that works efficiently, securely, and best meets your needs. Each design stage — from defining goals to final launch — has a clear structure. What are the stages of developing an AI assistant? How do they help you seamlessly integrate the solution into your business and get value to your company as quickly as possible? Read on.

1. Discovery → together with the client, we form goals, KPIs, scenarios, and create an integration map to understand how the solution will work within the company.
2. Conversation design → at this stage, we form the intents, the tone of communication of the AI assistant, and also prescribe escalation rules. We observe how the system behaves in situations when it cannot respond.
3. Knowledge base & RAG → we structure the database and determine the sources of information. To ensure that the artificial intelligence assistant quickly finds the necessary answers in documents, we use the RAG approach (retrieval-augmented generation).
4. Integrations & Actions → we integrate the AI assistant into analytics, Helpdesk, CRM and other systems. We configure automatic actions: creating leads/tickets, entries in corporate systems.
5. Testing → we test the system by working through negative cases and loads. This allows us to check whether the intelligent assistant processes requests smoothly under all circumstances.
6. Launch → we put the AI assistant into working mode. We give the team regulations, access, and conduct training.
7. Continuous improvement → once the launch has taken place, we monitor the analytics,
   We add new intents and optimize scenarios. This helps increase the efficiency of the digital assistant and minimize customer costs.

Cost and terms

Below are approximate examples of AI assistant implementation costs and timelines. They demonstrate different levels of complexity, estimated implementation timelines, and budgets, and will help you choose the solution that best meets your business objectives.

The cost and implementation time may vary depending on the number of communication channels, complexity of integrations, knowledge base size, security requirements, and personal information (PII) processing. We also take into account the assistant's multilingualism, human-in-the-loop, and analytics.

What data is needed to start a project?

Before creating a functional and reliable AI assistant, it is important for us to receive all the necessary information and materials from you as a client. The table below reflects the most important elements that are needed to study your service and create a digital assistant for the individual needs of your business. We provide examples of what data needs to be collected from the start of the project to the integration of the AI assistant, as well as responsible persons and submission formats.

Smart virtual assistants will open up new horizons for your business. Fast processing of requests, reducing the workload on the team, standardizing processes, generating commercial offers - these and many other advantages of AI assistants allow businesses to operate at a modern, progressive level, as well as save time and resources.

AI assistants are a digital asset for your business and an investment in its sustainability and competitiveness. The solutions developed by CortexIntellect increase the efficiency and manageability of processes, allowing you to focus on your company's strategic goals and scaling.

Submit a request, and we will analyze your scenarios, show you a demo, and propose an AI assistant architecture tailored to the real tasks of your business.