## Inspiration

My recent job application experience with a small company opened my eyes to the hiring challenges faced by recruiters. After taking time to thoughtfully evaluate each candidate, they explained how even a single bad hire wastes significant resources for small teams. This made me realize the need for a better system that saves time and reduces stress for both applicants and hiring teams. That sparked the idea for CareerChain.

## What it does

CareerChain allows job seekers and recruiters to create verified profiles on our blockchain-based platform.

For applicants, we use a microtransaction system similar to rental deposits or airport carts. A small fee is required to submit each application, refunded when checking status later. This adds friction against mass spam applications, ensuring only serious, passionate candidates apply.

For recruiters, our AI prescreens applicants, filtering out unqualified candidates. This reduces time wasted on low-quality applications, allowing teams to focus on best fits. Verified profiles also prevent fraud.

By addressing inefficiencies for both sides, CareerChain streamlines hiring through emerging technologies.

## How I built it

I built CareerChain using:

* XRP Ledger for blockchain transactions and smart contracts
* Node.js and Express for the backend REST API
* Next.js framework for the frontend

## Challenges we ran into

Implementing blockchain was challenging as it was my first time building on the technology. Learning the XRP Ledger and wiring up the components took significant learning and troubleshooting.

## Accomplishments that I'm proud of

I'm proud to have gained hands-on blockchain experience and built a working prototype leveraging these cutting-edge technologies.

## What I learned

I learned so much about blockchain capabilities and got exposure to innovative tools from sponsors. The hacking experience really expanded my skills.

## What's next for CareerChain

Enhancing fraud detection, improving the microtransaction UX, and exploring integrations like background checks to further optimize hiring efficiency.
## Inspiration 🤔

Has there ever been a topic you wanted to learn about, and wished there was a fun, digestible, educational video for it? Whether it's about Newton's laws of physics or Locke's social contract.
In today's age, kids consume hours upon hours of video content every week (AACAP, Statista). What if there were a way for curious kids to instantly create a short educational video on any topic they wanted?
Or for teachers to created a curated lesson with a custom video and quiz following it.

## What it does 😯

Enter World of Vidcraft! Vidcraft is a website that allows users to enter in a topic they want to learn about (e.g. "What are Newton's laws of physics?") and sit back as a whole new video is automatically crafted on the topic they enter, complete with visuals and narration. While watching the video, users can interact with Vidcraft's video chat interface to ask questions about the content they've seen so far.

Upon completing the video, users are taken to a quiz page where their knowledge is tested on the new topic they learned. If they select a wrong answer choice, they are provided an explanation for why it is wrong, so that they can learn from their mistake.

In this manner, Vidcraft allows users of any age to instantly create a novel, never-seen-before educational video on ANY topic they want. Making learning more accessible, easy, and fun than before.
All in the matter of a minute. 🖐️🎤

## How we built it 🛠️

Vidcraft is built with a React & Next JS front-end hosted on Vercel, with Node as our backend.
We use OpenAI’s GPT API to perform tasks such as script writing, image prompt generation, and question generation; OpenAI’s Dall-E API for image generation; and ElevenLabs for text-to-speech generation.

## Challenges we ran into

There were a couple challenges we ran into. Several arose because of Node. For one, integrating the ffmpeg and videoshow libraries for video creation posed some issues with errors of missing modules, in particular one saying ‘Module not found ./lib-voc/fluent-ffmpeg’. We tried several things such as modifying our package.json, package-lock.json, reinstalling packages, uninstalling certain ones and consulted GitHub, StackOverflow, and chatgpt. The issues still persisted but we were able to resolve them. We had other issues with Node.
Prompt engineering for GPT took some trial and error before getting it to output the desired content in the correct format. Especially because there are several steps to the video generation process, we needed to ensure that GPT reliably generates video scripts and image prompts.
We also ran into issues with using image generation APIs due to content policy and moderation of the APIs. Stability AI doesn’t allow prompts with keywords related to children, something GPT might pick as example illustrations for the video. Similarly, OpenAI’s Dall-E API automatically revises prompts and the prompts that it itself revises violate OpenAI’s content policies. In addition to this, the Dall-E API has strict rate limits. These posed some challenges we had to overcome through carefully designed prompting, and handling of cases where certain images may be missing from the video.

## Accomplishments that we're proud of

We overcame the challenges we ran into to create a polished website that is fully functional. Given a topic or question as input, it crafts together a cohesive video teaching users about a topic.

We also only exposed our API keys one time 😀.

## What we learned

In general, we all gained further knowledge about Node.js as we relied on it heavily for our API logic and video generation, the core of our project. Another significant learning experience was dealing with issues, ranging in everything from sneaky API issues due to content policy moderation (which pervaded us for some time) to issues with libraries like ffmpeg. These challenges pushed us to develop better problem-solving skills and a deeper understanding of the tools we were working with.

## What's next for VidCraft

We want to build out additional features. Some ideas include:
incorporating Redis to store previously-made videos and quizzes
incorporating Redis’s vector database to provide relevant video suggestions via vector search
supporting mixed question types for quizzes (so mcq, full response, true-false, multi-select, etc)
Increasing the number of images per video (currently we are constrained by rate limits) and doing interpolations between images would also be nice.
And we want to start getting users! We’d love for the tool to be used in classrooms and just in general, by people who are curious and want a quick video to learn.

---

Discord usernames:
ishaanjav (Ishaan Javali)
aditya.k1 (Adi Kulkarni)
tonyyamin (Tony Yamin)
alexsima\_09642 (Alex Sima)
## FLEX [Freelancing Linking Expertise Xchange]

## Inspiration

Freelancers deserve a platform where they can fully showcase their skills, without worrying about high fees or delayed payments. Companies need fast, reliable access to talent with specific expertise to complete jobs efficiently. "FLEX" bridges the gap, enabling recruiters to instantly find top candidates through AI-powered conversations, ensuring the right fit, right away.

## What it does

Clients talk to our AI, explaining the type of candidate they need and any specific skills they're looking for. As they speak, the AI highlights important keywords and asks any more factors that they would need with the candidate. This data is then analyzed and parsed through our vast database of Freelancers or the best matching candidates. The AI then talks back to the recruiter, showing the top candidates based on the recruiter’s requirements. Once the recruiter picks the right candidate, they can create a smart contract that’s securely stored and managed on the blockchain for transparent payments and agreements.

## How we built it

We built starting with the Frontend using **Next.JS**, and deployed the entire application on **Terraform** for seamless scalability. For voice interaction, we integrated **Deepgram** to generate human-like voice and process recruiter inputs, which are then handled by **Fetch.ai**'s agents. These agents work in tandem: one agent interacts with **Flask** to analyze keywords from the recruiter's speech, another queries the **SingleStore** database, and the third handles communication with **Deepgram**.

Using SingleStore's real-time data analysis and Full-Text Search, we find the best candidates based on factors provided by the client. For secure transactions, we utilized **SUI** blockchain, creating an agreement object once the recruiter posts a job. When a freelancer is selected and both parties reach an agreement, the object gets updated, and escrowed funds are released upon task completion—all through Smart Contracts developed in **Move**. We also used Flask and **Express.js** to manage backend and routing efficiently.

## Challenges we ran into

We faced challenges integrating Fetch.ai agents for the first time, particularly with getting smooth communication between them. Learning Move for SUI and connecting smart contracts with the frontend also proved tricky. Setting up reliable Speech to Text was tough, as we struggled to control when voice input should stop. Despite these hurdles, we persevered and successfully developed this full stack application.

## Accomplishments that we're proud of

We’re proud to have built a fully finished application while learning and implementing new technologies here at CalHacks. Successfully integrating blockchain and AI into a cohesive solution was a major achievement, especially given how cutting-edge both are. It’s exciting to create something that leverages the potential of these rapidly emerging technologies.

## What we learned

We learned how to work with a range of new technologies, including SUI for blockchain transactions, Fetch.ai for agent communication, and SingleStore for real-time data analysis. We also gained experience with Deepgram for voice AI integration.

## What's next for FLEX

Next, we plan to implement DAOs for conflict resolution, allowing decentralized governance to handle disputes between freelancers and clients. We also aim to launch on the SUI mainnet and conduct thorough testing to ensure scalability and performance.