Around 85%
Artificial Intelligence and Business Automation
NovaMind AI
Multilingual Conversational AI Platform
NovaMind AI is a multilingual AI assistant that supports voice and text conversations in English, Hindi, and Hinglish.
SingaporeMarket
2 MonthsTimeline
4 MembersProject Team
Artificial IntelligenceIndustry
Executive Summary
NovaMind AI
- Client
- Albert Joe
- Market
- Singapore
- Industry
- Artificial Intelligence
- Timeline
- 2 Months
- Team
- Project Team - 4 Members
- Services
- AI Agent Development, Generative AI Development, RAG Development Services, AI Application Development
- Technology
- Next.js, Express.js, REST APIs, MongoDB Atlas
- Primary Outcome
- Around 85% Monthly Active Users
Verified project metrics
Project Outcomes
Teams often had to answer the same questions and check different sources to find the right information. Because of this, routine communication took more time. NovaMind AI made this process simpler and easier to manage. It improves response consistency and allows employees to focus on more important work instead of answering the same questions repeatedly. The platform also gives the business a practical way to use AI in daily operations and expand its use as business needs grow.
Project Overview
NovaMind AI is a multilingual AI assistant that supports voice and text conversations in English, Hindi, and Hinglish.
Users can speak or type their questions. The platform identifies the language and gives a suitable answer. It also remembers previous messages, so users can continue the same conversation without repeating the details.
OpenAI, RAG, and LangChain help the platform understand questions, find useful information, and give answers based on earlier messages. It works smoothly on both desktop and mobile devices.
What We Built
We built a voice and text-based AI platform that supports English, Hindi, and Hinglish conversations. The platform includes automatic language detection, real-time speech-to-text conversion, AI-generated responses, voice playback, conversation history, session management, RAG-based knowledge retrieval, secure authentication, and responsive layouts. Backend APIs, MongoDB Atlas connections, OpenAI integration, LangChain workflows, Python-based AI processing, security controls, and real-time response handling were also developed to run the platform smoothly.
Client Background
Albert Joe works in the technology and AI solutions space. He wanted to develop an AI platform that could communicate with users in more than one language. Many users speak in English, Hindi, or Hinglish during everyday conversations. Basic chatbots often struggle when users switch between these languages or ask follow-up questions based on earlier messages. He needed a platform where users could speak or type, switch languages naturally, and receive helpful answers based on previous conversations and business-related information.
Project Scope
We worked on the complete project, from planning and design to deployment, including:
- Requirement gathering
- Conversation and user-flow planning
- Voice, text, and multilingual interaction planning
- UI/UX design
- Frontend development
- Backend and REST API development
- User authentication
- MongoDB Atlas setup
- OpenAI, RAG, and LangChain implementation
- Python-based AI processing
- Conversation memory
- Speech-to-text and text-to-speech setup
- Real-time response streaming
- Performance optimisation
- Security implementation
- Cross-browser and device testing
- VPS configuration, deployment, and live review
Target Audience
NovaMind AI is built for businesses that want to use AI for customer support or daily internal work. The main users include:
- Product teams
- Customer support teams
- Operations teams
- Service-based businesses
- SaaS companies
- Enterprises
- Businesses serving English, Hindi, and Hinglish-speaking users
Objectives
The main objectives were to:
- 01Create an AI platform for voice and text conversations
- 02Support conversation in English, Hindi, and Hinglish
- 03Identify the user’s language automatically
- 04Allow users to switch languages during a conversation
- 05Give answers based on previous messages
- 06Save and manage conversation history
- 07Find useful information from connected business data
- 08Provide fast, real-time responses
- 09Avoid repeated or unrelated answers
- 10Protect user accounts and conversation data
- 11Support future integrations and new AI features
Business Challenge
Before development, we looked at the main problems users face when talking to AI in different languages.
- 01Basic chatbots often struggle when users switch between languages. Sometimes, users have to select a language manually or repeat their message.
- 02Voice conversations were also more complex. The system had to convert speech into text, understand the language and question, and then give the reply in voice.
- 03The platform also needed to remember earlier messages so users could ask follow-up questions without repeating the same details.
- 04The main challenge was to bring language detection, voice support, conversation memory, and useful AI responses into one simple platform.
Our Solution
We developed a multilingual AI platform for voice and text conversations.
- The platform identifies English, Hindi, and Hinglish automatically, so users do not need to select a language manually.
- For voice input, speech is converted into text. The system then understands the question and gives the reply in both text and voice.
- It also remembers earlier messages, allowing users to continue the conversation without repeating the same details.
- Conversation history is saved in MongoDB Atlas. OpenAI uses previous messages and connected business information to give helpful answers. The response appears gradually on the screen, making the conversation feel faster and smoother.
Before → After
How Conversations Changed
Before
Users mainly depended on text-based chatbots
After
Users can communicate through voice or text
Before
Language had to be selected manually
After
The system detects English, Hindi, Hinglish, and Roman Hindi automatically
Before
Language changes could interrupt the conversation
After
Users can switch languages during the same conversation
Before
Follow-up questions often lost earlier details
After
Previous messages help continue the conversation
Before
Answers mainly depended on general AI knowledge
After
The system uses connected business information when needed
Before
Users had to wait for the complete response
After
Answers appear on the screen in real time
Before
Voice processing required separate tools
After
Voice input, AI response, and playback work in one flow
Before
Earlier discussions were difficult to continue
After
Conversation history is saved across sessions
Delivery ownership
THE TISA's Role
Product Strategy
Discovery
UX/UI Design
AI Architecture
Backend Engineering
Frontend Engineering
Mobile Development
Integrations
QA
Key Features
The platform includes the following features:
03Voice and Text Conversations
01
Voice and Text Conversations
- Chat through voice or text
- Switch between speaking and typing
- Receive replies in text or voice
Development Process
The project began with a discussion about the client’s goals and the kind of experience expected from the platform. We studied how users would communicate through voice and text, what language support was needed, and how earlier conversations should be handled. This gave the project a clear direction.
Technical Challenges
Technology Stack
Next.js
Express.js
REST APIs
MongoDB Atlas
OpenAI
LangChain
Retrieval-Augmented Generation
Python
JWT Authentication
WebSockets
Ubuntu VPS
Nginx
PM2
SSL
Git and GitHub
Design Decisions
The platform was designed to keep voice and text conversations simple and easy to follow. Important decisions included:
- Conversation-focused interface
- Voice and text controls in one place
- Clear user and AI messages
- Easy access to previous conversations
- Visible listening and processing states
- Automatic language detection
- Real-time response display
- Simple login and account flow
- Responsive layouts across devices
- Clear error and retry messages
- Only essential controls in the chat area
- Easy voice playback for generated responses
SEO and Indexing
NovaMind AI includes a public website and private user conversation pages. SEO work focused on the public website, while private account and conversation pages were kept out of search results. The work included:
- Clear page titles
- Proper page headings
- Relevant AI platform keywords
- Multilingual AI-related content
- Voice assistant-related content
- Clean page URLs
- Meta descriptions
- Mobile-friendly layouts
- Image optimisation
- Fast public-page loading
- Restricted indexing for private pages
- Clear feature and technology sections
Performance Optimisation
We improved the platform’s performance through:
- Real-time AI response streaming
- Fast language detection
- Controlled use of previous messages
- Reduced duplicate AI requests
- Reusable Next.js components
- Optimised backend APIs and lighter frontend code
- Faster MongoDB searches
- Conversation pagination
- Better RAG document organisation
- Caching for non-sensitive information
- Fast WebSocket communication
- Smooth voice processing
- Clear loading and error states
- Proper failed-request handling
- PM2 monitoring with automatic restarts
Security
The platform handles private user and business information, so security was important throughout development. Security measures included:
- Secure login with password hashing
- JWT authentication for user sessions
- Protected pages, APIs, and conversation records
- Input validation with request sanitisation
- API rate limiting
- CORS protection
- Secure environment variables
- HTTPS encryption
- Secure MongoDB Atlas connections
- Protected business knowledge
- Controlled OpenAI API access
- Safe error handling with backend logging
Architecture Diagram
Results
For Users
- 01Users can communicate with the AI through voice or text in English, Hindi, and Hinglish. They can switch languages, ask follow-up questions, and continue earlier discussions without repeating the same details. Responses appear in real time, making conversations faster and easier to follow.
For the Client
- 01The client received a secure multilingual AI platform built for regular business use and future growth. The platform can support new integrations, more AI features, and more users as the business grows.
Project Showcase
Visual Identity
Visual Identity
NNovaMind AI
InterAa
NovaMind AI
Color
- #7C3AED01Primary Purple124 58 237
- #8B5CF602Bright Violet139 92 246
- #05081603Dark Background5 8 22
- #0F172A04Secondary Background15 23 42
- #11182705Card Background17 24 39
- #FFFFFF06White255 255 255
- #E2E8F007Light Text226 232 240
- #94A3B808Secondary Text148 163 184
- #3B82F609Blue Accent59 130 246
Type
- 01 · Primary4 weights
Inter
ABCDEFGHIJKLMNOPQRSTUVWXYZ
abcdefghijklmnopqrstuvwxyz
0123456789- Regular
- Medium
- Semibold
- Bold
Client Testimonial
We wanted an AI platform where users could speak or type in English, Hindi, and Hinglish without selecting a language each time. Team TISA understood this requirement clearly and developed NovaMind AI around the way our users communicate. Users can switch languages, use voice, and continue conversations without interruption. We are impressed with the final platform and satisfied with how the team managed the development process.
Albert Joe
Future Scalability
Future improvements can include:
- 01
Support for more Indian and international languages
- 02
Business-specific AI assistants
- 03
CRM and customer support integration
- 04
WhatsApp, Slack, and Microsoft Teams integration
- 05
Team accounts with role-based access
- 06
Advanced conversation analytics
- 07
Human support handover
- 08
Workflow automation
Lessons Learned
While building NovaMind AI, we learned that:
- 01
Multilingual AI needs more than translation
- 02
Hinglish and Roman Hindi need custom handling
- 03
Clear voice states and retry options improve usability
- 04
Useful context helps answer follow-up questions
- 05
Long chat history should be managed carefully
- 06
RAG works better with organised business data
- 07
Real-time streaming makes responses feel faster
- 08
Private chats need secure access
- 09
Performance metrics should be tracked from the start
Conclusion
NovaMind AI is a multilingual AI assistant created for smooth voice and text conversations in English, Hindi, and Hinglish. It understands language changes, remembers earlier messages, and gives useful answers using connected information. It provides the client with a secure system for customer support, virtual assistance and future AI features.
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