Verity

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  Verity Coverpage

Inspiration

Verity was inspired by our own experience coming into Canada as immigrant students. Starting our journey and trying to find work was not easy. Even when we found jobs, it still felt like it was not enough to fully support school, food, bills, and moving around. Because of that, we started looking at remote jobs as a way to make extra income and have more flexibility. But that also became frustrating. We spent long hours searching and applying, only to later realize that some of those jobs were never really accessible to people in our situation. Verity was built for people like us. It helps newcomers understand the story behind a job posting before they spend time applying. Instead of simply saying a job is “good” or “bad,” Verity explains the opportunity better.

What it does

Verity is an AI-powered web tool that helps newcomers understand how accessible a remote job really is before they apply. A user can paste a job posting into the platform, and Verity analyzes the opportunity for explicit signals, hidden expectations, missing information, and accessibility-positive signs.

How we built it

We designed Verity as an AI interpretation layer. The tool reads a job posting, extracts important signals, and groups them into clear categories:

1. Accessibility
2. Friction
3. Missing or unclear information
4. Its Conclusion

Verity was built using Next.js with the App Router architecture, React, TypeScript, and TailwindCSS for the frontend experience and UI system. We used Framer Motion for transitions and interaction polish. The analysis engine was custom-built using TypeScript and structured interpretation logic designed specifically for newcomer accessibility analysis in remote job postings. No external APIs, databases, cloud services, or third-party AI platforms were used in the current prototype. The focus of the hackathon build was on creating a lightweight, explainable, and deployable proof of concept with a strong interpretation framework rather than infrastructure complexity.

Challenges we ran into

Actually building up the platform took a lot of time, and aligning our different views on what it should look like and how it would work.

Accomplishments that we're proud of

We are proud that we built a working prototype in 3 days

What we learned

One major thing we learned is that there is more to a job posting than we see. The problem isn't us but the hidden languages, expectations, or missing details. A job posting can look open and still carry assumptions that make it harder for newcomers to access. We also learnt the usefulness of AI and how quickly it helps us churn out information

What's next for Verity

Next, we want to make Verity more personalized and useful for real job searching. This includes live job scans, salary checks, multilingual support, personalized newcomer profiles, mentorship support, and user feedback.

Built With

• framer
• motion
• next.js
• react
• tailwindcss
• typescript