Solomon Protocol is an AI-powered job search platform that filters opportunities according to sovereign values and user protection, combining real-time job feed aggregation with ML-based recruiter analysis to avoid ghost jobs and predatory listings. The application was developed with React, Node.js, and RedisAI.
Demo and code available at the following links: https://youtu.be/DcrJQhsaJMM and https://github.com/LooneyRichie/Solomon-Protocol
Use of Redis 8 and technical architecture: a solution designed to operate in real time and at scale, leveraging multiple Redis modules to transform the system beyond a simple cache.
Real-time ghost job detection: Redis TimeSeries is used to track job posting age and exposure by views, with automated 60-day retention. The detection engine combines multiple indicators such as number of flags received, days since publication, and view count, requiring 4 or more suspicious signals to mark a listing as potentially fraudulent and thus protect candidates.
Tensor-based recruiter analysis: RedisAI enables fast inferences to score the legitimacy of a listing or recruiter. Tensor operations for feature extraction and scoring with inference latencies below 5 ms in optimal cases and confidence rates above 95 percent according to trained models.
Global job search architecture: country-specific caching for localized results using JSON storage in Redis and 5-minute invalidation policies. Sorted sets are used as a fallback to manage volatility and priority of listings, ensuring performance and consistency in global searches.
Multi-criteria analysis engine: probabilistic filters with Bloom filters to detect suspicious keywords and reduce false positives, complemented by vector similarity searches to recognize recurring fraud patterns or anomalous behavior. Reliability threshold based on 4 or more indicators for automated actions.
Results and performance metrics: 98 percent reduction in exposure to fake listings, average ML inference latency of 23 ms in the production environment, global coverage across 7 regions, and more than 5000 job analyses per hour.
Q2BSTUDIO and collaboration: Q2BSTUDIO is the company responsible for development and support, specialized in custom applications and custom software with strength in artificial intelligence, cybersecurity, and aws and azure cloud services. We offer business intelligence services, AI solutions for companies, AI agent development, and advanced visualization with power bi to improve decision-making. Our comprehensive approach covers everything from secure architectures to scalable cloud deployments and custom product development.
Featured services driving projects like Solomon Protocol: custom applications, custom software, artificial intelligence, cybersecurity, aws and azure cloud services, business intelligence services, AI for companies, AI agents, and power bi.
About the creator: Richie Looney is the lead developer and creator of Solomon Protocol, working as an independent developer on this project. We are open to collaborations, job opportunities, and donations to continue driving innovation and protection for job seekers.
Solomon Protocol demonstrates how Redis 8 can transcend the role of cache and become the backbone of a real-time AI platform, helping find quality employment while avoiding fraud and predatory practices.
