Signol Labs builds a data infrastructure that transforms fragmented resumes, job descriptions, and other workforce documents into structured, portable, and verifiable signals. By enabling education providers, hiring platforms, and state agencies to exchange consistent data, the company speeds up decision‑making and improves the reliability of AI‑driven hiring and training tools. Their solution connects the entire workforce ecosystem, turning raw documents into actionable intelligence for better hiring outcomes.
Funding
Funding not disclosed
Founders
Product
Problem
Workforce systems such as job boards, ATS platforms, and talent marketplaces still rely on digitized resumes and job descriptions that were never redesigned for data use. These documents remain unstructured, inconsistent, and hard to verify, which slows decision‑making and reduces trust in hiring and training outcomes.
Solution
Signol Labs builds verifiable data pipelines that convert fragmented resumes, job postings, and other workforce signals into structured, portable formats. By aligning data with the needs of downstream systems, the company enables AI and analytics to consume reliable signals for matching, evaluation, and skill assessment. Their approach connects the three layers of the ecosystem—data producers (education and training providers), system operators (employment platforms, ATS vendors), and infrastructure owners (state workforce agencies)—so that structured signals can move across platforms and be activated where decisions are made. This creates a more efficient, trustworthy talent market without requiring organizations to replace existing data sources.
Target Audience
Signol Labs works with education and training providers, employment platforms and HR technology vendors, employers, and state workforce agencies that need reliable, interoperable talent data to improve hiring and training outcomes.
Features
- Extraction and normalization of resume and job‑description content into a standardized schema for skills, credentials, and experience
- Verification layer that adds provenance and authenticity metadata to each signal, supporting trust in AI‑driven decisions
- Interoperability APIs that enable seamless integration of structured signals into ATSs, talent marketplaces, and HR tech workflows
- Portable data format that allows signals to be shared across organizations while maintaining consistency and compliance
- System‑level design framework that maps “systems,” “signals,” and “activation” to guide partners in embedding structured data into their products