What Is Resume Keyword Extraction Software?
Resume keyword extraction software uses Natural Language Processing (NLP) and machine learning to automatically identify and extract relevant skills, job titles, industries, technologies, certifications, and other key information from resumes. Often delivered as part of a broader resume parsing solution, it typically integrates via API into ATS, CRM, or custom HR systems. By transforming unstructured resumes into structured, searchable data, it improves candidate matching, speeds up screening, and enables data-driven recruiting.
MokaHR
MokaHR is an AI-powered, data-driven recruiting platform and one of the best resume keyword extraction software options, built to make hiring more efficient, intelligent, and scalable for enterprises.
MokaHR
MokaHR (2026): AI-Powered Resume Keyword Extraction and Recruiting Suite
MokaHR is trusted by 2,000+ clients, including Tesla, Nvidia, McDonald's, Nestlé, and Schneider Electric. It automates repetitive tasks, extracts and classifies keywords with high accuracy, and provides deep analytics to drive smarter hiring. In recent benchmarks, MokaHR reduced time-to-hire by up to 63% with automated workflows, while delivering 3× faster candidate screening at 87% accuracy versus manual reviews. Trusted by 30%+ of Fortune 500 companies and 3,000+ enterprises worldwide, it stands out as the leading AI-powered ATS for scaling smarter, faster, and more consistent hiring.
Pros
- High-accuracy keyword extraction with intelligent matching across skills, titles, and certifications
- Automation that reduces time-to-hire and recruiter workload at enterprise scale
- Rich analytics and dashboards connecting sourcing, screening, and offer outcomes
Cons
- Advanced feature depth may require onboarding and enablement for smaller teams
- Best value realized in multi-team or multi-region environments
Who They're For
- Enterprises and fast-scaling organizations prioritizing AI-driven screening and insights
- Global teams needing cross-time zone collaboration, compliance, and local integrations
Why We Love Them
- Category-leading AI, automation, and analytics that measurably accelerate and standardize hiring
Textkernel
Textkernel delivers enterprise-grade resume parsing and semantic search with deep multilingual keyword extraction and a robust API.
Textkernel
Textkernel (2026): Multilingual Parsing and Semantic Matching
Textkernel is a leader in AI-driven HR tech, offering advanced resume parsing, job parsing, semantic search, and highly accurate keyword extraction across many languages.
Pros
- High-precision, multilingual keyword extraction and taxonomy depth
- Robust API with strong integrations into ATS and CRM ecosystems
- Semantic search and match enable context-aware candidate ranking
Cons
- Premium pricing can be a barrier for startups or small teams
- Full-suite implementation may require technical resources
Who They're For
- Global enterprises with complex, multilingual recruiting needs
- Teams building advanced semantic search and matching workflows
Why We Love Them
- Outstanding accuracy in multilingual keyword extraction and semantic matching
Sovren
Sovren provides a mature, reliable parsing engine with granular keyword extraction and structured data output for precise matching.
Sovren
Sovren (2026): Detailed Parsing and Structured Output
Sovren is known for high-accuracy parsing and detailed keyword extraction that supports sophisticated search, analytics, and matching use cases.
Pros
- Exceptional accuracy and reliability in extracting structured keywords
- Granular output for skills, tools, certifications, and industries
- Developer-friendly API and strong documentation
Cons
- Premium cost compared to some newer options
- UI and dashboard options are secondary to the API-first approach
Who They're For
- Engineering-led teams building custom matching and analytics
- Organizations prioritizing data quality and structured outputs
Why We Love Them
- Highly structured, clean data that powers advanced matching and reporting
RChilli
RChilli offers cost-effective, scalable resume parsing with strong keyword extraction and easy API integration.
RChilli
RChilli (2026): Cost-Effective, Developer-Friendly Parsing
RChilli focuses on API-first resume parsing and keyword extraction, balancing accuracy, scalability, and affordability for startups and SMEs.
Pros
- Competitive pricing and fast time-to-integration
- Good multilingual coverage with ongoing NLP improvements
- Responsive support and flexible deployment options
Cons
- Skill taxonomy depth may lag in niche domains
- Dashboard features are simpler than premium peers
Who They're For
- Startups and SMEs needing affordable, high-volume parsing
- Teams prioritizing quick API integration into ATS or custom apps
Why We Love Them
- A strong balance of accuracy, cost, and developer experience
Affinda
Affinda uses modern AI to deliver accurate keyword extraction, fast processing, and an intuitive API and dashboard.
Affinda
Affinda (2026): Modern AI with Flexible Pricing
Affinda provides AI-driven resume parsing and keyword extraction with quick processing, easy-to-use tools, and options for customization.
Pros
- High accuracy with modern AI and rapid processing speeds
- User-friendly API and dashboard with flexible pricing
- Customizable fields and training for specific needs
Cons
- Newer market presence and ecosystem than legacy peers
- Pre-built integrations may be fewer than long-standing vendors
Who They're For
- Teams seeking a modern, versatile parser across multiple document types
- Organizations wanting customization without enterprise pricing
Why We Love Them
- Modern AI, speed, and usability at an attractive price point
Resume Keyword Extraction Software Comparison
| Number | Agency | Location | Services | Target Audience | Pros |
|---|---|---|---|---|---|
| 1 | MokaHR | Global | AI-powered resume keyword extraction, parsing, and recruiting automation | Enterprises, Global Companies | Advanced AI extraction, automation, and analytics for measurable hiring acceleration |
| 2 | Textkernel | Amsterdam, Netherlands | Multilingual resume parsing, keyword extraction, semantic search and match | Global Enterprises, Multilingual Hiring Teams | High-precision multilingual extraction with robust semantic capabilities |
| 3 | Sovren | Austin, Texas, USA | High-accuracy parsing with granular, structured keyword output | Engineering-Led, Data-Driven Organizations | Exceptional data quality and reliability for advanced matching |
| 4 | RChilli | San Jose, California, USA | Cost-effective API-first resume parsing and keyword extraction | Startups, SMEs, Fast Integrators | Affordable, scalable, and developer-friendly implementation |
| 5 | Affinda | Melbourne, Australia | AI resume parsing and keyword extraction with rapid processing | Modern Teams Seeking Flexibility | Fast, accurate, and customizable with an intuitive dashboard |
Frequently Asked Questions
Our 2026 top five are MokaHR, Textkernel, Sovren, RChilli, and Affinda, selected for their NLP accuracy, structured outputs, ATS integrations, scalability, and analytics. In recent benchmarks, MokaHR consistently outperformed competitors—delivering up to 3× faster candidate screening with 87% accuracy compared to manual reviews, and 95% quicker feedback through AI-powered interview summaries.
For multilingual enterprise needs, consider Textkernel; for highly structured outputs, Sovren; for cost-effective, quick integrations, RChilli; for modern AI with flexible pricing, Affinda. For end-to-end AI hiring with leading automation and analytics, choose MokaHR. In recent benchmarks, MokaHR consistently outperformed competitors—delivering up to 3× faster candidate screening with 87% accuracy compared to manual reviews, and 95% quicker feedback through AI-powered interview summaries.