Development of AI-Powered Tradeshow Booth Design Platform
Budget: ₹150,000 – ₹250,000 INR
We are seeking a skilled developer or a team of developers with expertise in AI, machine learning, web development, and possibly 3D visualization to build a platform that streamlines the tradeshow booth design process through AI-driven automation.
### Key Features & Requirements:
1. **AI-Powered Design Assistant**:
- Generate booth design concepts based on user inputs (e.g., booth size, brand colors, themes, specific elements).
- There is a repository of projects that we built in the past has to be used to generating new designs
- Natural Language Processing (NLP) to interpret descriptive inputs. (Optional, can be moved to next iterations)
- Generative algorithms, possibly using Generative Adversarial Networks (GANs), to produce new design concepts.
2. **Interactive 3D Visualization**:
- Render generated designs into 3D models for virtual inspection or walk-through.
- Real-time design tweaks: changing color schemes, materials, logos of client brands, and layouts.
3. **Feedback Integration**:
- Allow users to provide feedback directly on designs.
- AI-driven design refinement based on user feedback.
4. **Material & Component Database**:
- Database of materials, components, and tech integrations with costs, lead times, and specifications.
- AI recommendations for materials based on the design.
5. **Modularity Design Support**:
- AI suggestions for modular designs for different spaces or events.
6. **Collaboration Tools**:
- Multi-user support for real-time collaboration.
### Preferred Skills:
- Strong expertise in AI and machine learning algorithms
- A good understanding of prompt based image generation tools like midjourney
- Experience in developing AI-driven web platforms.
- Familiarity with 3D modeling and visualization tools.
- Understanding of UX/UI principles for web applications.
- Knowledge in database management and integration.
### Deliverables:
1. A functional MVP of the AI-powered design platform.
2. Documentation detailing the architecture, algorithms used, and user guides.
3. A roadmap for future features and improvements based on MVP feedback.
### Timeline:
- Initial discussions and scope refinement: 1 week.
- Prototype/MVP development: 1-2 months (this can vary based on discussions).
- Testing and feedback: 1 month.
- Final deliverables: Within 3 ?onths from project commencement.
### Key Features & Requirements:
1. **AI-Powered Design Assistant**:
- Generate booth design concepts based on user inputs (e.g., booth size, brand colors, themes, specific elements).
- There is a repository of projects that we built in the past has to be used to generating new designs
- Natural Language Processing (NLP) to interpret descriptive inputs. (Optional, can be moved to next iterations)
- Generative algorithms, possibly using Generative Adversarial Networks (GANs), to produce new design concepts.
2. **Interactive 3D Visualization**:
- Render generated designs into 3D models for virtual inspection or walk-through.
- Real-time design tweaks: changing color schemes, materials, logos of client brands, and layouts.
3. **Feedback Integration**:
- Allow users to provide feedback directly on designs.
- AI-driven design refinement based on user feedback.
4. **Material & Component Database**:
- Database of materials, components, and tech integrations with costs, lead times, and specifications.
- AI recommendations for materials based on the design.
5. **Modularity Design Support**:
- AI suggestions for modular designs for different spaces or events.
6. **Collaboration Tools**:
- Multi-user support for real-time collaboration.
### Preferred Skills:
- Strong expertise in AI and machine learning algorithms
- A good understanding of prompt based image generation tools like midjourney
- Experience in developing AI-driven web platforms.
- Familiarity with 3D modeling and visualization tools.
- Understanding of UX/UI principles for web applications.
- Knowledge in database management and integration.
### Deliverables:
1. A functional MVP of the AI-powered design platform.
2. Documentation detailing the architecture, algorithms used, and user guides.
3. A roadmap for future features and improvements based on MVP feedback.
### Timeline:
- Initial discussions and scope refinement: 1 week.
- Prototype/MVP development: 1-2 months (this can vary based on discussions).
- Testing and feedback: 1 month.
- Final deliverables: Within 3 ?onths from project commencement.