Shuvel offers an AI‑powered talent acquisition platform that automatically parses resumes, scores candidate fit against job requirements, and generates context‑aware outreach and interview content. The system routes recruiting tasks based on workload and expertise, provides predictive hiring analytics, and integrates bidirectionally with existing ATS via API. It targets corporate recruiting teams, staffing agencies, and RPO providers handling high‑volume hiring.
Funding
Funding not disclosed
Founders
Product
Problem
Recruiters spend extensive manual effort parsing resumes, crafting outreach, and routing candidates, leading to slow time‑to‑fill, low match accuracy, and uneven workload distribution across hiring teams.
Solution
SHUVEL provides an AI‑driven talent acquisition platform that automates candidate sourcing, resume extraction, and fit scoring. The system uses large‑language‑model prompt chaining to ask context‑aware questions at each stage of the hiring pipeline, producing refined candidate lists and role‑specific interview questions. Parsed resume data are matched against job descriptions with weighted skill, experience, and cultural criteria, generating a quantitative match score. An AI routing engine assigns tasks—such as resume review, interview scheduling, or candidate nurturing—to the most appropriate recruiter based on expertise, current workload, and priority. Predictive analytics forecast hiring timelines, candidate dropout risk, and emerging skill gaps, enabling data‑driven planning. The platform integrates bi‑directionally with existing ATS via API, allowing real‑time updates and seamless workflow continuity.
Target Audience
The primary customers are corporate recruiting departments, staffing agencies, and RPO providers that manage high‑volume hiring for technology, finance, and other knowledge‑intensive sectors.
Features
- Deep‑learning resume parser that extracts skills, certifications, and experience, then maps them to structured job requirements.
- AI match scoring engine with configurable weighting (technical skills, experience, culture fit, location) delivering a percentage fit metric.
- Prompt‑chaining interface that lets recruiters pose sequential, context‑rich queries to the LLM for sourcing, Boolean string generation, and outreach content creation.
- Automated workflow routing that balances task assignment across recruiters using workload, domain expertise, and candidate priority flags.
- Predictive analytics dashboard forecasting time‑to‑fill, candidate attrition probability, and industry skill‑gap trends.
- Bi‑directional ATS integration via RESTful API and webhook support for real‑time candidate status synchronization.
- Auto‑generated personalized outreach emails and interview question banks tailored to each candidate’s profile and the target role.
- Secure, role‑based access control and end‑to‑end encryption to meet data‑privacy compliance standards.