Nexa: Advanced AI Screen-content Assistant
Budget: ₹12,500 – ₹37,500 INR
Project: MVP Development – Floating AI Screen Assistant
Overview:
We are developing an MVP for a desktop-based floating AI assistant that analyzes screen content in real-time — including text, images, video, and audio — and provides context-aware suggestions, Q&A, summaries, and voice/text interaction. The assistant will operate non-intrusively on the user's screen to enhance productivity and learning without disrupting workflow.
Primary MVP Goals
Minimize Cost – Design for scalability with a hybrid cloud-local model
High Accuracy – Use accurate models for OCR, NLP, audio, and image analysis
Low Latency – Responses within 4–5 seconds
Target Users
Students
Professionals in virtual meetings (Zoom, Google Meet, Teams)
Researchers and analysts
Content creators
Remote workers
Core MVP Features
1. Floating Window Assistant (Main UI)
Draggable, resizable floating icon or window
Can be minimized or expanded
Two Modes:
Passive Mode: Analyzes screen silently
Active Mode: User invokes the assistant for responses, suggestions, or notes
Voice activation with a wake word (e.g., “Hey Nexa”)
Light, Dark, and Transparent themes
2. Real-Time Screen Analysis
Continuous screen content capture
Identifies and processes text, images, video, and audio
Key functionalities:
Text: OCR and context analysis
Images: Vision models like CLIP or BLIP
Video: Scene/frame analysis
Audio:
Transcribes live or recorded conversations (Zoom, Meet, etc.)
Summarizes ongoing speech
Detects keywords and user intent
3. AI Assistant Functions
Real-time Q&A based on screen content
Voice and text commands (e.g., “Summarize this”, “Take a note”)
Auto-suggestions based on detected screen context
Context-aware responses during meetings, chats, or presentations
4. Built-in Notes Panel
Floating notes window with quick access
Add screenshots directly from the screen
Text or voice input
Organize with tags and folders
Sync or export functionality (planned for future)
5. Meeting and Call Assistant
Detects video calls (Zoom, Meet, Teams)
Transcribes and understands conversations
Enables contextual queries during meetings
Post-meeting summary with key points and action items
Option to save summary to notes
Non-Core (Planned for Future Versions)
Multi-language support
Translation of on-screen content
Task manager and calendar integration
Personalized AI memory
Adaptive learning mode for improved suggestions
MVP Timeline and Scope (2–3 Months)
Month 1:
Build floating window prototype
Implement text and image analysis from screen
Enable basic voice command and chat-based Q&A
Month 2:
Implement audio/video capture and transcription
Detect meetings and generate live summaries
Develop note-taking panel with screenshot functionality
Add voice/text interaction with screen-aware suggestions
Output Formats
Text-based chat and suggestions
Visual summaries (bullet lists, cards)
Downloadable files (PDF, DOCX format for meeting notes)
Developer Requirements
Experience with screen capturing, OCR, and audio processing
Strong knowledge of integrating NLP and AI models (e.g., OpenAI, Whisper, etc.)
Ability to create low-latency, lightweight desktop apps
Privacy-first approach (local processing preferred where feasible)
Modular and scalable codebase for future upgrades
To Apply:
Please include the following in your proposal:
Relevant past work (AI apps, screen/audio processing, etc.)
Your preferred tech stack for this project
Estimated timeline and cost
Suggestions or feedback to improve the MVP
Overview:
We are developing an MVP for a desktop-based floating AI assistant that analyzes screen content in real-time — including text, images, video, and audio — and provides context-aware suggestions, Q&A, summaries, and voice/text interaction. The assistant will operate non-intrusively on the user's screen to enhance productivity and learning without disrupting workflow.
Primary MVP Goals
Minimize Cost – Design for scalability with a hybrid cloud-local model
High Accuracy – Use accurate models for OCR, NLP, audio, and image analysis
Low Latency – Responses within 4–5 seconds
Target Users
Students
Professionals in virtual meetings (Zoom, Google Meet, Teams)
Researchers and analysts
Content creators
Remote workers
Core MVP Features
1. Floating Window Assistant (Main UI)
Draggable, resizable floating icon or window
Can be minimized or expanded
Two Modes:
Passive Mode: Analyzes screen silently
Active Mode: User invokes the assistant for responses, suggestions, or notes
Voice activation with a wake word (e.g., “Hey Nexa”)
Light, Dark, and Transparent themes
2. Real-Time Screen Analysis
Continuous screen content capture
Identifies and processes text, images, video, and audio
Key functionalities:
Text: OCR and context analysis
Images: Vision models like CLIP or BLIP
Video: Scene/frame analysis
Audio:
Transcribes live or recorded conversations (Zoom, Meet, etc.)
Summarizes ongoing speech
Detects keywords and user intent
3. AI Assistant Functions
Real-time Q&A based on screen content
Voice and text commands (e.g., “Summarize this”, “Take a note”)
Auto-suggestions based on detected screen context
Context-aware responses during meetings, chats, or presentations
4. Built-in Notes Panel
Floating notes window with quick access
Add screenshots directly from the screen
Text or voice input
Organize with tags and folders
Sync or export functionality (planned for future)
5. Meeting and Call Assistant
Detects video calls (Zoom, Meet, Teams)
Transcribes and understands conversations
Enables contextual queries during meetings
Post-meeting summary with key points and action items
Option to save summary to notes
Non-Core (Planned for Future Versions)
Multi-language support
Translation of on-screen content
Task manager and calendar integration
Personalized AI memory
Adaptive learning mode for improved suggestions
MVP Timeline and Scope (2–3 Months)
Month 1:
Build floating window prototype
Implement text and image analysis from screen
Enable basic voice command and chat-based Q&A
Month 2:
Implement audio/video capture and transcription
Detect meetings and generate live summaries
Develop note-taking panel with screenshot functionality
Add voice/text interaction with screen-aware suggestions
Output Formats
Text-based chat and suggestions
Visual summaries (bullet lists, cards)
Downloadable files (PDF, DOCX format for meeting notes)
Developer Requirements
Experience with screen capturing, OCR, and audio processing
Strong knowledge of integrating NLP and AI models (e.g., OpenAI, Whisper, etc.)
Ability to create low-latency, lightweight desktop apps
Privacy-first approach (local processing preferred where feasible)
Modular and scalable codebase for future upgrades
To Apply:
Please include the following in your proposal:
Relevant past work (AI apps, screen/audio processing, etc.)
Your preferred tech stack for this project
Estimated timeline and cost
Suggestions or feedback to improve the MVP