A Quick Look at Kula:
Kula positions itself as a "Gen 3 AI-Native ATS" that combines recruiting workflow management with AI-powered candidate screening and sourcing. The platform offers AI scoring and ranking based on job descriptions, contextual resume parsing, automated scheduling, an AI notetaker for interviews, and candidate sourcing capabilities. Kula emphasizes being "built for AI from the ground up" rather than adding AI features to legacy ATS architecture.
The Mokka Difference:
Kula is an all-in-one ATS with AI screening features built in. Mokka complements and integrates with your existing ATS (including Kula) to provide the deep screening intelligence that workflow management systems cannot deliver on their own.
- ATS with AI Features vs. Dedicated Screening Depth: Kula manages your recruiting workflow and adds AI resume scoring. Mokka specializes exclusively in evidence-based screening—conducting pre-screening interviews, collecting accomplishment evidence, and running integrity checks that go far beyond what an ATS's built-in features can provide.
- Resume Scoring vs. Evidence Generation: Kula's AI scoring ranks candidates based on resume content matched against job descriptions. Mokka generates new evidence through structured pre-screening interviews—collecting specific accomplishments, measurable outcomes, and verifiable examples that don't exist on any resume.
- Contextual Parsing vs. Multi-Source Verification: Kula parses resumes with contextual understanding to extract information. Mokka cross-checks every candidate response against their resume, LinkedIn profile, and third-party data through our Profile and Answer Integrity analytics—detecting inconsistencies and AI-generated applications.
- System of Record vs. Screening Intelligence: Kula excels at being your recruiting system of record—managing pipeline stages, scheduling, notes, and workflow. Mokka excels at generating the screening intelligence that determines who moves through that pipeline—providing rich, evidence-based candidate profiles that integrate directly into your ATS.
- AI Notetaker vs. AI Pre-Screener: Kula's AI notetaker captures insights from recruiter-led interviews. Mokka's AI conducts the pre-screening interview itself—automating the tedious data collection phase so recruiters only invest time in candidates backed by verified evidence.
- Built-in Features vs. Best-of-Breed Integration: Kula offers an integrated suite of features within a single ATS platform. Mokka integrates with any ATS (including Kula) as a specialized screening layer—giving you best-in-class screening depth without vendor lock-in if you ever switch ATS systems.
Key Questions to Consider:
- How does your ATS's AI scoring verify that candidates actually accomplished what they claim on their resumes beyond keyword matching?
- When candidates optimize resumes with AI to match job descriptions perfectly, how do you differentiate genuine qualifications from well-optimized documents?
- What mechanisms detect inconsistencies between a candidate's resume and their LinkedIn profile, or identify AI-generated application responses?
- How deeply can your ATS screen candidates before you invest valuable recruiter time in interviews—resume analysis only, or evidence-based pre-screening?
- If you decide to switch ATS systems in the future, what happens to your screening capabilities and historical candidate intelligence?