Hai App
Ment Tech Labs collaborated with Hai App to develop an advanced AI-powered chatbot platform that blends productivity and conversation in one intuitive experience. Designed for both personal and professional users, Hai enables intelligent task automation, real-time assistance, and contextual interactions through a sleek and scalable AI interface.
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Hai App is an innovative AI startup that set out to redefine personal and professional productivity through intelligent conversation. Unlike traditional chatbots built for single-purpose tasks, Hai functions as an all-in-one conversational assistant managing schedules, generating ideas, writing drafts, and automating everyday workflows through a natural chat interface.
The client’s vision was to design a platform that feels human-like yet highly functional, capable of integrating with calendars, note-taking tools, and productivity systems while maintaining seamless data privacy and personalized responses. Ment Tech Labs was chosen to architect and develop the full AI ecosystem from prototype to launch.
Your AI Should Work the Way You Do
Fragmented Productivity Ecosystem
Users had to switch between multiple apps for messaging, task management, and creative assistance.
Lack of Contextual Understanding
Existing chatbots struggled to retain memory across conversations, leading to repetitive prompts and poor continuity.
Real-Time Integration Complexity
Syncing live data from tools like Google Calendar, Notion, and Slack within conversations required advanced API orchestration.
Scalability of AI Interactions
The system needed to support thousands of concurrent chat sessions without performance lag or response delay.
Multi-Modal Functionality
The client aimed to include text, voice, and image-based interactions, each requiring optimized processing and memory retention.
Secure Data Management
Ensuring privacy and compliance for user data across personal and enterprise accounts demanded robust encryption and permission control.
Ment Tech Labs’ Development Approach
Ment Tech Labs approached the Hai App project with a clear objective — to create an intelligent, human-like chatbot that could act as a personal assistant and productivity companion. The development strategy was divided into structured phases to ensure technical precision, scalable infrastructure, and intuitive design.
Discovery and Requirement Analysis
The team conducted deep research on user behavior, productivity workflows, and conversation patterns. Multiple use cases were defined, from freelancers managing projects to executives organizing daily tasks. These insights formed the foundation for the AI flow and interface logic.
System Architecture and Model Selection
Ment Tech Labs designed a modular architecture capable of supporting conversational memory, natural language reasoning, and external tool integration. The system used a combination of fine-tuned GPT models and LangChain pipelines to ensure long-term contextual recall and smooth multi-turn conversations.
Backend Development and Data Layer Setup
The backend was built using FastAPI and PostgreSQL, optimized for scalability and latency-free responses. Redis caching handled conversational state management, while WebSocket protocols were implemented to power real-time, multi-session chats without delay.
Frontend and UX Engineering
The front-end team created a clean, distraction-free chat interface using Next.js with Tailwind CSS. A dual-pane layout was developed, one for conversations and another for tasks, reminders, and automation summaries. Special attention was given to accessibility, ensuring a seamless experience across desktop and mobile devices.
Integration of External Tools and APIs
Custom connectors were developed for Google Calendar, Slack, Notion, and Trello to allow Hai App to schedule meetings, summarize chats, and organize notes directly from user prompts. The integration layer was designed to let users manage multiple tools through one central conversation thread.
Context Memory and Personalization
Ment Tech Labs implemented a dynamic memory layer that stored contextual data such as user preferences, tone, and task history. This allowed the AI to remember instructions like “Remind me every Monday” or “Draft messages in a friendly tone,” ensuring continuity between sessions.
Quality Assurance and Security Implementation
Extensive testing was performed to validate the accuracy of AI responses and prevent data overlap between users. AES-256 encryption, token-based authentication, and anonymized data handling were enforced for full privacy and compliance with GDPR standards.
Deployment and Continuous Optimization
The final system was deployed on AWS Lambda for dynamic scaling and high availability. Ment Tech Labs also set up analytics dashboards to track AI performance, response accuracy, and user engagement. Continuous monitoring allowed for rapid updates, ensuring consistent improvements post-launch.
Ment Tech Labs delivered a complete AI-driven productivity ecosystem for Hai App transforming it from a simple chatbot concept into an intelligent assistant that manages workflows, automates daily actions, and adapts to every user’s behavior. Each solution was engineered to meet specific goals of usability, personalization, and performance.
Unified Conversational Interface
Developed a seamless chat experience that merges communication, task management, and information retrieval into one interface, eliminating the need for multiple productivity apps.
Context-Aware AI Engine
Integrated a conversational memory layer that allows the AI to recall previous chats, preferences, and incomplete tasks ensuring continuity and human-like understanding during long sessions.
Workflow Automation and Smart Commands
Enabled users to automate tasks such as meeting scheduling, note creation, and project updates through simple prompts like “Remind me to follow up on design feedback at 3 PM.”
Multi-Platform Connectivity Layer
Built a secure integration framework that connects Hai App with Google Workspace, Notion, Trello, and Slack, allowing users to manage data and communications in real time.
Voice and Text Interaction Engine
Introduced dual input modes where users can switch between text and voice seamlessly. This was powered by speech-to-text AI and optimized latency processing for instant responses.
Custom AI Routine Builder
Developed a no-code interface that lets users design recurring workflows such as “Morning Summary,” “Meeting Recap,” or “Daily Focus List” directly through chat prompts.
Our clients
Intelligent Conversation Hub
A centralized space where users chat, create tasks, ask questions, and get instant answers from the AI without switching between apps.
Memory-Powered Responses
The system remembers past interactions, pending tasks, and user preferences, allowing the AI to deliver consistent and context-aware responses.
Integrated Task Panel
Each conversation can trigger actionable tasks like setting reminders, creating lists, or assigning team follow-ups directly from the chat window.
Multi-App Integration Dashboard
A unified control center that connects with tools like Google Calendar, Slack, Notion, and Trello, letting users automate actions within external apps.
Voice Command Activation
Users can talk naturally to the AI to schedule meetings, manage notes, or request summaries using speech recognition and instant response delivery.
Personalized Routine Builder
A feature that allows users to set recurring daily workflows such as “Morning Report” or “End-of-Day Summary,” customized entirely through chat instructions.
Knowledge Summarizer
The AI can condense long conversations, meetings, or documents into short summaries and key takeaways for quick decision-making.
Secure Cloud Architecture
Every message, task, and file is processed through encrypted cloud servers with strict data privacy and user-level control.
Multi-Device Continuity
Sessions remain synced across mobile, desktop, and web so users can start a conversation on one device and continue seamlessly on another.
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