Problem statements

Problem statements

• 1. 1. Lyzr Personalized Investment Portfolio Advisor In the realm of financial advisory, personalization is key to meeting diverse client needs. Individuals vary significantly in their risk tolerance, financial goals, and investment timelines, making a one-size-fits-all approach ineffective. The objective is to develop a Personalized Investment Portfolio Advisor using Lyzr's API, enabling financial institutions or individual advisors to provide tailored investment strategies. The advisor should analyze inputs such as the client’s: ● Risk tolerance (conservative, moderate, or aggressive) ● Financial goals (retirement, education, wealth accumulation, etc.) ● Timeline (short-term, medium-term, or long-term) ● Current financial standing (income, expenses, savings, debt levels) ● Market data to align strategies with ongoing trends and opportunities. Desired Outcomes The solution should ensure: 1. Hyper-personalization by dynamically adjusting strategies based on real-time client inputs and market data. 2. Scalability to handle multiple clients without sacrificing quality or accuracy. 3. Transparency by explaining the rationale behind each recommendation. 4. Automation to reduce manual intervention in generating recommendations. 5. Compliance with local financial regulations and ethical practices. Deliverables for Evaluation To select the winner, the solution submissions will be assessed based on the following deliverables: 1. Technical Feasibility Report ○ Explanation of how Lyzr’s API was utilized to integrate client data, market trends, and risk assessment. ○ Demonstration of the personalization logic. 2. Prototype Demo ○ A working prototype showcasing how the investment strategies are generated, including client input interfaces and strategy dashboards.

• 2. 3. Pitch Presentation: A concise 5–10 minute presentation summarizing: ○ The problem solved. ○ Features of the solution. ○ How it aligns with the buildathon theme. 2. Sentient Request for Agents (RFA): Building "Truth Terminal" Inspired AI Agents for Twitter Using Eliza We're launching Request for Agents (RFA) to create Twitter-centric AI agents using the Eliza library. Turn Twitter into an interactive playground for AI-powered interactions, insights, and creative experiences across multiple categories. If you’re passionate about building AI tools, leveraging Twitter’s rich ecosystem, and using cutting-edge technology, this is your call to action. Below, you'll find inspiration for potential agent categories and functionality. What We’re Looking For Agents that can: 1. Interact with Tweets in real-time – enabling new conversational dynamics. 2. Deliver actionable insights – summarizing, researching, or enhancing information on Twitter. 3. Create entertaining or productive experiences – providing value beyond simple automation. 4. Building on Eliza: Eliza ‣ provides a powerful, modular framework for creating multi agents and Twitter connectors. Example Agent Use Cases 1. Picture Perfect Agent ● Idea: Drop a comment on a tweet with a picture of yourself, and the agent generates an instant, AI-powered response.

• 3. ● Example: Compliments, jokes, or even a personality analysis based on the picture. 2. Screenshot + Research Agent ● Idea: Use an agent that can screenshot a tweet, research its context, and respond with relevant insights or summaries. ● Example: "What’s the background of this thread?" → Agent provides a concise breakdown. 3. Impersonation Agent ● Idea: Mimic the tone, style, or perspective of a specific individual or persona on Twitter. ● Example: "What would Elon Musk say about this tweet?" → Generates an on-brand response in his voice. 4. Viral Thread Generator ● Idea: Analyze a trending topic and create a viral Twitter thread based on historical patterns and audience preferences. ● Example: “Here’s a 5-tweet breakdown on AI hype cycles.” 5. Fact-Checker Agent ● Idea: Analyze a claim made in a tweet and provide a fact-checked response with supporting references. ● Example: "This statistic is actually from a 2019 report by XYZ, and here’s the link." 6. Sentiment Analyzer ● Idea: Provide instant sentiment analysis of a conversation or a tweet thread. ● Example: "Overall, this thread has a positive sentiment with some critical outliers." 7. Meme Creator ● Idea: Suggest meme captions for images in a tweet or convert text tweets into memes. ● Example: "Caption this pic: When the team finally agrees to your idea." 8. Context Bridge ● Idea: Translate complex tweets into simpler language or vice versa. ● Example: "Here’s what this jargon-filled tweet means in plain English." Categories for RFA Submissions

• 4. 1. Entertainment & Creativity: Meme generators, impersonators, and fun tools for user engagement. 2. Knowledge & Research: Fact-checking, sentiment analysis, and content summarization. 3. Personal Productivity: Time-saving agents for scheduling tweets, drafting threads, or filtering content. 4. Social Good: Tools to counter misinformation, amplify diverse voices, or foster healthy conversations. 5. Finance: Agents that provide real-time stock updates, financial news summaries, or personalized investment insights. 6. Web3: Tools that monitor blockchain trends, provide cryptocurrency market analyses. Who Should Apply? ● Builders excited by AI Agents and Social media. ● AI developers with experience in LLMs and conversational agents. ● Creators passionate about making AI accessible and fun. Submission Guidelines 1. Proposal: Outline your agent idea, category, and key use case. 2. Prototype: Include a GitHub link or demo showcasing initial progress. 3. Impact: Explain how your agent improves or enhances the Twitter experience. 4. Scalability: Describe the potential for your agent to grow and evolve. 3. Glovera.in Video Bot Challenge Bounty Details 💰 Total Prize: Rs. 1,00,000 ● Cash Prize: Rs. 60,000 ● Study Counseling: Rs. 15,000 ● Admission Scholarship: Rs. 25,000 Challenge Overview

• 5. Create an AI-powered video bot that revolutionizes student counseling for international education by providing human-like interactions and personalized guidance. Core Requirements 1. Student Interface Information Collection Page ● Pre-session student detail form ● Data validation and storage ● Profile creation capabilities Video Bot Interface ● Human-like avatar ● Voice and text input options ● Natural language processing ● Real-time response generation ● Context-aware conversations ● Program recommendation engine 2. Administrative Dashboard Program Management ● Add new programs with eligibility criteria ● Edit existing program details ● Program deactivation/deletion ● Bulk upload capabilities Analytics & Monitoring ● Session tracking ● Conversion metrics ● Student engagement analytics ● Query pattern analysis Technical Specifications Data Integration ● University program database

• 6. ● Eligibility criteria matrix ● Student information schema ● API integration capabilities AI Components ● Natural Language Processing ● Speech Recognition ● Text-to-Speech ● Sentiment Analysis ● Recommendation Engine User Experience ● Mobile-responsive design ● Low-latency responses ● Intuitive navigation ● Seamless handoff to human counselors Evaluation Criteria Technical Excellence (40%) ● Code quality and architecture ● Performance optimization ● Security implementation ● Scalability considerations User Experience (30%) ● Interface design ● Conversation flow ● Response accuracy ● Loading times Business Impact (30%) ● Lead generation effectiveness ● Counselor time optimization ● Student engagement metrics ● Conversion potential 4. BuildShip AI Workflows Hackathon

• 7. Prize Pool 💰 Total Rewards ● $500 prize money across categories ● 1 month BuildShip Pro plan for winners (~$500 value) Challenge Overview Create AI workflows using BuildShip that will be published to the BuildShip community marketplace under MIT license. Categories 1. Best Overall Implementation 2. Most Impactful Business Use Case Workflow Core Requirements AI Workflow Development ● Build using BuildShip platform ● MIT licensed for public access ● Attribution to creator's name ● Categorized and themed appropriately ● Serves as problem statement solution repository Submission Guidelines ● Complete workflow documentation ● Use case demonstration ● Implementation details ● Impact analysis Support & Resources Workshop Access ● Live build-style session at hackathon start ● Hands-on workflow creation guidance ● Real-time problem-solving Marketing Support ● Promotion across:

• 8. ○ 100xEngineers ○ Instagram ○ LinkedIn ○ Discord ● Continuous visibility throughout hackathon Technical Specifications Workflow Requirements ● BuildShip platform compatibility ● Clear input/output definitions ● Error handling ● Performance optimization ● Scalability considerations Documentation ● Setup instructions ● Usage guidelines ● API documentation ● Example implementations Evaluation Criteria Technical Excellence (40%) ● Code quality ● Implementation efficiency ● Platform utilization ● Error handling Business Impact (30%) ● Use case relevance ● Market potential ● Scalability ● Value proposition Documentation (30%) ● Clarity ● Completeness ● Example quality ● Setup guidance

• 9. Timeline ● Workshop: Beginning of hackathon ● Development: Duration of hackathon ● Submissions: End of hackathon period Success Metrics 1. Workflow functionality 2. Business use case impact 3. Documentation quality 4. Community adoption potential 5. Technical innovation Submission Process 1. Complete workflow development 2. Document implementation 3. Submit for review 4. Present use case 5 . Relevant Venture Studio. AI Market Edge Agent Challenge Problem Context Startups struggle with: ● Finding competitive advantages in new markets ● Achieving product-market fit (PMF) ● Resource optimization while scaling ● Quick market adaptation ● Customer understanding and validation Solution Requirements 1. Market Analysis Engine ● Real-time market trend analysis ● Competition mapping ● Opportunity identification

• 10. ● Data-driven differentiation strategies 2. Customer Discovery Module ● ICP generation and refinement ● Need-mapping algorithms ● Validation process automation ● Customer journey simulation 3. Competitive Intelligence System ● Competitor offering analysis ● Market gap identification ● Product positioning optimization ● Strategic advantage mapping 4. Product Evolution Engine ● Automated feedback collection ● Feature prioritization ● Market-specific adaptation recommendations ● Iteration tracking and analysis 5. Market Expansion Advisor ● International market analysis ● Cultural compatibility assessment ● Regulatory compliance guidance ● Localized growth strategy generation Technical Specifications AI Components ● Natural Language Processing ● Predictive Analytics ● Market Intelligence APIs ● Sentiment Analysis ● Recommendation Systems Data Integration ● Market research databases ● Customer feedback systems ● Competitor tracking tools ● Regulatory compliance databases ● Economic indicators

• 11. Evaluation Criteria Technical Innovation (35%) ● AI/ML implementation sophistication ● Integration capabilities ● Scalability architecture ● Performance optimization Business Impact (35%) ● Market analysis accuracy ● Strategy effectiveness ● Resource optimization ● Time-to-market improvement User Experience (30%) ● Interface intuitiveness ● Insight clarity ● Implementation guidance ● Feedback incorporation Required Deliverables Technical Implementation ● Working AI agent prototype ● API documentation ● Integration guides ● Scalability blueprint 6. AEOS labs Problem Statement Details Title of the Challenge AI-Powered Dynamic Infographic Generation for Data Storytelling Problem Description Creating engaging infographic videos for data-driven stories is currently a time-consuming and skill-intensive process. We need an AI-powered solution that can automatically convert textual data and statistics into compelling animated infographics. The solution should

• 12. understand the context of the data and choose the most appropriate visualization method, making data storytelling more efficient and scalable. Current Situation ● What is the existing solution/process? ○ Manual creation of infographics using design tools ○ Requires skilled designers and animators ○ Time-intensive process for each new piece of content ○ Limited scalability for rapid content production ● Main limitations: ○ High production costs ○ Long turnaround times ○ Dependency on specialized skill sets ○ Difficulty in quickly updating visualizations with new data ● Stakeholders affected: ○ Content creators ○ Video editors ○ Designers ○ Data analysts ○ Viewers/audience Expected Outcome A solution that can: 1. Accept text input containing data/statistics 2. Automatically understand the type of data being presented 3. Select appropriate visualization methods 4. Generate animated infographics dynamically 5. Export as video files ready for content production Example Scenario: Input: "20% of users own an iPhone, 50% own a Samsung, and the rest own a variety of brands" Output: An animated pie chart video showing the distribution with appropriate labels and transitions Technical Requirements ● Required technologies/platforms: ○ Natural Language Processing for text understanding ○ Computer Vision/Graphics Generation ○ Animation frameworks ○ Video rendering capabilities ● Input/Output Specifications: ○ Input: Text files, CSV data, or direct text input ○ Output: MP4 video files with animations ● System Requirements: ○ Ability to handle various data types (percentages, numbers, comparisons)

• 13. ○ Support for different visualization types (pie charts, bar graphs, line graphs, etc.) ○ Scalable processing pipeline Submission Guidelines 1. Provide a working prototype with source code 2. Include documentation for setup and usage 3. Submit test cases showing various data types handled 4. Provide sample output videos 5. Include performance metrics