Project Info
Inspiration
With the number of candidates rising in the industry in comparison to the job positions, conducting interviews and deciding on candidates carefully has become a critical task. Along with this ratio imbalance, there are an increasing number of candidates that are forging their experience to gain an unfair advantage over others.
What it does
The project provides AI interview solution which conducts a human-like interview and deploy AI agents in the backend to verify the authenticity of the candidate.
How we built it
The project was building NextJS as frontend, and NodeJS as backend. The AI service was provided by Hume, along with Single Store as the backend database. We also used Fetch AI to deploy the AI agents that verify the authenticity.
Challenges we ran into
Some challenges we ran into were related to integrating Hume into our frontend. Managing the conversation data and inferring it to provide feedback was also tricky.
Accomplishments we're proud of
Being able to build a working MVP within 2 days of hacking. Integrating hume AI and being able to persist and maintain conversation transcripts that was later used to make inference.
What we learned
We learned about using and integrating AI agents to help us with important tasks. Having used Hume AI also provided us with insights on different emotions captured by the AI service that can be used in a lot of downstream tasks.
What's next
We plan on expanding the scope of our candidate information verification to include more thorough checks. We also plan to partner with a couple of early stage adopters to use Candidate Compare and benefit from reduced hiring loads.

Overview
This project features a sample implementation of Hume's Empathic Voice Interface using Hume's React SDK. Here, we have a simple EVI that uses the Next.js App Router.
Project deployment
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Analysis
View
Metric
- 12
- 4
Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.
Technology
- CSSIn code
- Next.jsIn code
- PythonIn code
- ReactIn code
- Tailwind CSSIn code
- TypeScriptIn code
- Vercel AI SDKIn code
- Node.jsClaimed
7 of 8 appear in the indexed code. 1 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.
AI coding agents
No AI coding agent signals were found in this repository.
Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.
Codebase size
Source size
214 KB
Source files
46
Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.
Repository
tobyL05/hirenew
64 files · 714 KB · @ 58337df
Structure
Interface
28 files · 44%Screens, components and styles rendered to the user.
+2 moreAPI & routing
1 file · 2%Request entry points: routes, handlers and controllers.
Application logic
21 files · 33%Domain rules, services and shared utilities.
Supporting
Layers are inferred from where files sit in the tree, not from reading the code. A project that names its directories unconventionally will read oddly here — open the file browser to check anything the diagram implies.
Languages
- YAML60%
- TypeScript29%
- Python10%
- CSS1%
- Markdown0%
Share of indexed source by file size. Binary and vendored files are excluded.
Dependencies
package.json
npm · 34- @ai-sdk/groq
- @humeai/voice-react
- @radix-ui/react-label
- @radix-ui/react-slot
- @radix-ui/react-switch
- @radix-ui/react-toggle
- @types/react-virtualized
- ai
- class-variance-authority
- clsx
- framer-motion
- geist
- groq-sdk
- hume
- lucide-react
- next
- react
- react-dom
- +16 more
Declared in the repository’s manifests at the indexed commit. A declared package is not proof it is used, and runtime dependencies are listed first.
This project’s features have not been analysed yet.
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