AI Virtual Assistant for business with voice, text, and integrations
Goal: Create a virtual assistant that can handle incoming calls and messages, engage in dialogue with clients, record orders, answer questions, and integrate with CRM/messengers. Operates 24/7.
1. Assistant functionality
1.1. Incoming and outgoing calls
- Receiving calls via VoIP/SIP (Twilio, Voximplant, Zadarma or similar)
- Ability to make outgoing calls (for example, order confirmations)
- Real-time speech recognition (ASR)
- Speech synthesis (TTS) with a natural voice
1.2. Message processing
- Integration with WhatsApp Business API, Telegram, Facebook Messenger, Email
- Support for multilingualism (minimum: English, Russian, Ukrainian)
1.3. Intelligent dialogue
- Using an LLM model (locally on the server or via API)
- Setting up a knowledge base for each client (FAQ, sales scripts)
- Ability to connect to CRM (HubSpot, Bitrix24, Zoho, Pipedrive, etc.)
1.4. Task management
- Recording orders/applications in CRM or Google Sheets
- Booking time/services (Google Calendar or built-in module)
2. Technical requirements
2.1. Hosting and performance
- Deployment on a Dell PowerEdge R740 server (40 cores, 544 GB RAM, RTX A5000, 21.6 TB)
- Ability to simultaneously operate at least 50 voice channels without lag
- Local installation of ASR/TTS (Whisper + Coqui TTS or Piper) to reduce costs
2.2. Architecture
- Modular system (ability to add new channels)
- Ability to operate in the cloud and locally (hybrid)
- API for connecting external applications
2.3. Control panel
- Web interface for adding/editing clients, tariffs, scripts
- Viewing call, chat, and statistics history
- Setting up voices and languages
3. Monetization
- SaaS subscription: monthly payment (€50–150)
- Additional payment for integrations (+€100–200 one-time)
- White Label (branding for the client)
4. Developer requirements
- Experience with ASR/TTS and LLM
- Understanding of VoIP and CRM integrations
- Skills in optimization for high load
- Experience in deploying solutions on dedicated servers with GPU
5. Development stages
- MVP
- Voice calls + integration with 1 CRM
- Support for the English language
- Basic control panel
- Expansion
- Adding messengers
- Support for 3+ languages
- White Label
6. Result
- Fully functional AI Virtual Assistant ready for subscription sales to businesses
- Installation and operation documentation
- Scalability for 100+ clients
AI Virtual Assistant + Omnichannel AI Call Center + Referral System
Goal: Create a SaaS platform for businesses that combines call handling, messaging, and online chats with customers through AI, with an integrated referral program to attract new users. The platform operates 24/7, supports voice, text, CRM integrations, and communications.
1. Functionality
1.1. Voice Calls (AI Virtual Assistant)
- Incoming and outgoing calls via VoIP/SIP (Twilio, Voximplant, Zadarma or similar)
- Real-time speech recognition (ASR)
- Natural voice speech synthesis (TTS)
- Scripts and knowledge base for responses
- Call recording and saving in CRM
1.2. Messengers and Social Networks (Omnichannel)
- WhatsApp Business API, Telegram, Facebook Messenger, Instagram DM
- AI automatic responses
- Ability to switch to a live operator
1.3. Online Chat on the Website
- Widget for the client's website
- Support for real-time AI responses
- Transfer of chat to a manager if necessary
1.4. CRM and Knowledge Base
- Storage of call, chat, and request history
- Automatic lead addition
- Editable knowledge base for AI (FAQ, scripts)
1.5. Referral System
- Generation of unique referral links for clients
- Tracking registrations and payments through referral links
- Dashboard for viewing referral statistics (number, status, accruals)
- Automatic bonus accrual (cash or subscription discount)
- Customizable rules (e.g., 10% of the payment from the referred client or 1 month of free use for each active referral)
2. Technical Requirements
2.1. Hosting and Performance
- Deployment on Dell PowerEdge R740 server (40 cores, 544 GB RAM, RTX A5000, 21.6 TB)
- Simultaneous operation of at least 50 voice channels and 500 chat sessions
- Local installation of ASR/TTS (Whisper + Coqui/Piper) to reduce costs
2.2. Architecture
- Modular system (adding new channels without complete redesign)
- API for connecting to third-party systems
- White Label capability (branding for the client)
- Referral program module integrated into the control panel
2.3. Control Panel
- Web interface for managing clients, tariffs, scripts
- Statistics on calls, chats, requests
- Configuration of voices, languages, FAQs
- “Partnership” section for managing referral links and bonuses
3. Monetization
- SaaS subscription: €150–300/month for the full package (calls + chats + CRM)
- Additional charge for CRM integrations and customization (+€100–200 one-time)
- White Label for agencies
- Referral system as a marketing tool
4. Developer Requirements
- Experience with ASR/TTS and LLM
- Knowledge of VoIP/SIP, integrations with messengers
- Experience building high-load SaaS
- Experience developing referral systems
- Ability to work with Docker/Kubernetes
5. Development Stages
- MVP
- Messenger voice assistant
- Basic CRM
- Control panel
- Basic version of the referral program (registration tracking, manual accruals)
- Expansion
- Full Omnichannel
- White Label
- Analytics module
- Automatic referral system with payouts
6. Result
- Ready SaaS platform for businesses
- Documentation for installation and use
- Scalability for 100+ clients
- Built-in referral system for organic growth of the client base
AI Virtual Assistant + Omnichannel AI Call Center + Referral System
Цель: Создать SaaS-платформу для бизнеса, которая объединяет обработку звонков, сообщений и онлайн-чатов с клиентами через AI, с интегрированной реферальной программой для привлечения новых пользователей. Платформа работает 24/7, поддерживает голос, текст, интеграции с CRM и коммуникации.
1. Функционал
1.1. Голосовые звонки (AI Virtual Assistant)
- Приём и исходящие звонки через VoIP/SIP (Twilio, Voximplant, Zadarma или аналог)
- Распознавание речи (ASR) в реальном времени
- Синтез речи (TTS) с естественным голосом
- Скрипты и база знаний для ответов
- Запись звонков и сохранение в CRM
1.2. Мессенджеры и соцсети (Omnichannel)
- WhatsApp Business API, Telegram, Facebook Messenger, Instagram DM
- Автоматические ответы AI
- Возможность переключения на живого оператора
1.3. Онлайн-чат на сайте
- Виджет для сайта клиента
- Поддержка AI-ответов в реальном времени
- Передача чата менеджеру при необходимости
1.4. CRM и база знаний
- Хранение истории звонков, чатов, заявок
- Автоматическое добавление лидов
- Редактируемая база знаний для AI (FAQ, скрипты)
1.5. Реферальная система
- Генерация уникальных реферальных ссылок для клиентов
- Учёт регистраций и оплат по реферальным ссылкам
- Панель для просмотра статистики рефералов (кол-во, статус, начисления)
- Автоматическое начисление бонусов (денежных или в виде скидки на подписку)
- Настраиваемые правила (например, 10% от платежа привлечённого клиента или 1 месяц бесплатного использования за каждого активного реферала)
2. Технические требования
2.1. Хостинг и производительность
- Развёртывание на сервере Dell PowerEdge R740 (40 ядер, 544 GB RAM, RTX A5000, 21.6 TB)
- Одновременная работа минимум 50 голосовых каналов и 500 чат-сессий
- Локальная установка ASR/TTS (Whisper + Coqui/Piper) для снижения затрат
2.2. Архитектура
- Модульная система (добавление новых каналов без полной переделки)
- API для подключения к сторонним системам
- Возможность White Label (брендирование под клиента)
- Модуль реферальной программы интегрирован в панель управления
2.3. Панель управления
- Веб-интерфейс с управлением клиентами, тарифами, скриптами
- Статистика по звонкам, чатам, заявкам
- Настройка голосов, языков, FAQ
- Раздел «Партнёрка» для управления реферальными ссылками и бонусами
3. Монетизация
- SaaS-подписка: €150–300/мес за полный пакет (звонки + чаты + CRM)
- Доплата за интеграции с CRM и кастомизацию (+€100–200 разово)
- White Label для агентств
- Реферальная система как маркетинговый инструмент
4. Требования к разработчику
- Опыт работы с ASR/TTS и LLM
- Знание VoIP/SIP, интеграций с мессенджерами
- Опыт построения SaaS с высокой нагрузкой
- Опыт разработки реферальных систем
- Умение работать с Docker/Kubernetes
5. Этапы разработки
- MVP
- Голосовой ассистент мессенджера
- Базовая CRM
- Панель управления
- Простейшая версия реферальной программы (учёт регистраций, ручные начисления)
- Расширение
- Полный Omnichannel
- White Label
- Модуль аналитики
- Автоматическая реферальная система с выплатами
6. Результат
- Готовая SaaS-платформа для бизнеса
- Документация по установке и использованию
- Возможность масштабирования на 100+ клиентов
- Встроенная реферальная система для органического роста клиентской базы
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1315 7 0 Good day.
I am ready to take your project to work.
I can develop voice and text assistants for you using no-code/low-code tools.
Message me privately, we will discuss all the details and choose the best solution for you.
-
9351 20 0 1 Hello,
I am a developer in the field of AI/ML & BOT DEV. I can complete your project. Write to me, and we will discuss.
August 11, 9:22
60 days 27,000 UAH
Danilo Ch.
614 1 0
… Good day!
We create such projects personalized. We are specifically engaged in ML processes, but if this is a full-fledged SaaS with an application/website, backend, etc., we can easily hire outstaffing/outsourcing, we have partners. Hosting and deploying is not a problem; we are certified providers. (on a dedicated server, GPU is not a problem)
The question is how you will scale this later if the training process for AI agents in the business of selling sneakers and tours in Ukraine will be radically different. Also, each business has different end goals - some businesses focus on product sales, while others focus on collecting contacts and passing them to sales for finalizing the sale (it is also worth noting that such an AI assistant performs the function of a lead qualifier better by collecting contacts and passing warm leads to the manager for follow-up).
Also, the question is how the model should be configured - by the client themselves or do you provide the client with MLops that integrates this technology for them?
The question about integrations with CRM systems - this is a completely separate layer of work, for example, when it is necessary to integrate with Bitrix, Zoho, Monday, Pipedrive, etc. We need to look at the most popular CRMs on the market to form a pipeline in advance and target only clients with these CRM systems or take a higher price for CRMs where the API is more difficult (is this Ukraine or Europe?).
I will say right away that for such a project, if we want to integrate with CRM systems, we need to choose systems with open lines only; everything else will be very labor-intensive and inconvenient.
In general, if you want SaaS - we need to do a small discovery to understand how this will work. If you already have a discovery - okay, we need to study it to understand the project better.
August 11, 2:30
1 day 27,000 UAH
Sergey Grechukha
166 1 0
Greetings! I am currently working on a similar project. I have questions regarding the required quality (depends on the provider), and why not use ready-made solutions. But, one way or another, I can also implement your project.
August 11, 0:34
1 day 1,000 UAH
Alina S.
300
Hello!
Yes, we can implement an AI Virtual Assistant with support for voice and text channels, integrations with CRM and messengers, local ASR/TTS, and the ability to scale to 50+ simultaneous channels.
We have experience working with VoIP/SIP (Twilio, Voximplant, Zadarma), LLM models, as well as optimization for
-
1616 8 0 Hello,
I am a developer in the field of AI/ML & BOT DEV. I can complete your project. Write to me, and we will discuss.
-
427 1 0 Good day!
We create such projects in a personalized manner. We handle the ML processes ourselves, but if it’s a full-fledged SaaS with an application/website, backend, etc., we can easily hire outstaffing/outsourcing, we have partners. Hosting and deploying is not a problem, we are certified providers. (on a dedicated server GPU is not a problem)
The question is how to scale this for you later, if the training process for the AI agent in the business of selling sneakers and tours in Ukraine will be radically different. Also, each business has different end goals - some businesses aim for product sales, while others focus on collecting contacts and passing them to sales for finalizing the sale (it’s also worth noting that such an AI assistant better performs the function of a lead qualifier by collecting contacts and passing warm leads to the manager for follow-up)
Another question is how the model should be configured - by the client themselves or do you provide the client with MLops that integrates this technology for them?
The question regarding integrations with CRM systems - this is a completely separate layer of work, for example, when it is necessary to integrate with Bitrix, Zoho, Monday, Pipedrive, etc. We need to look at the most popular CRMs on the market to form a pipeline in advance and target only clients with these CRM systems or charge a higher price for CRMs where the API is more difficult (is this Ukraine or Europe?)
I will say right away that for such a project, if we want to integrate with CRM systems, we should only take systems with open lines; everything else will be very labor-intensive and inconvenient.
In general, if you want SaaS - we need to do a small discovery to understand how this will work. If you already have a discovery - okay, we need to study it to understand the project better.
…
There are no questions regarding technologies - we work with such. In 100% of cases, we only work with Eleven Labs (yes, it is more expensive than alternatives, but 1000% better in quality). If necessary, we will look for alternatives, as I see the monthly fee is small. The question right away is how many free minutes do you want to include in the monthly fee.
Let’s get in touch and discuss your project in more detail, it’s interesting but there are many pitfalls that we have already encountered and which are critical to understanding the correct creation of an MVP.
Thank you!
-
93 1 0 Hello! I am currently working on a similar project. I have questions regarding the required quality (it depends on the supplier), and why not use ready-made solutions. However, one way or another, I can also implement your project.
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