List of MokaHR Moka Eva Customers
Beijing, x,
China
Since 2010, our global team of researchers has been studying MokaHR Moka Eva customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased MokaHR Moka Eva for Cognitive Computing from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using MokaHR Moka Eva for Cognitive Computing include: Tesla, a United States based Automotive organisation with 125665 employees and revenues of $97.69 billion, Luckin Coffee, a China based Leisure and Hospitality organisation with 84191 employees and revenues of $4.72 billion, Trip.Com, a United States based Automotive organisation with 10 employees and revenues of $2.0 million and many others.
Contact us if you need a completed and verified list of companies using MokaHR Moka Eva, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The MokaHR Moka Eva customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight | Insight Source |
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Luckin Coffee | Leisure and Hospitality | 84191 | $4.7B | China | MokaHR | MokaHR Moka Eva | Cognitive Computing | 2024 | n/a | In 2024, Luckin Coffee implemented MokaHR Moka Eva to support high-volume frontline hiring and candidate engagement across its China HR operations. The deployment of MokaHR Moka Eva drew on Cognitive Computing capabilities to automate candidate interaction and screening workflows for large applicant volumes. The implementation used Moka Recruiting together with Moka Eva as inferred from vendor customer listings, with Moka Eva providing chatbot driven AI screening and conversational candidate engagement. Functional capabilities emphasized automated resume processing, NLP based candidate screening, scripted chatbot interview prequalification, and faster interview feedback loops, aligning with standard Cognitive Computing recruiting workflows. Operational scope concentrated on HR operations in China and on frontline store hiring where application volumes are high, shifting initial screening workload from human screeners to Moka Eva and the Moka Recruiting intake pipeline. The solution routed qualified candidates into recruiter queues and support workflows for scheduling and follow up, enabling continuous processing of large batches of resumes and candidate conversations. Governance changes centered on redefining the initial screening step and embedding Moka Eva into recruiter workflow orchestration, with process updates to handoff rules and feedback capture for interviewers. Vendor materials cited reduced manual screening work, large scale resume processing, and faster interview feedback as observable outcomes from the MokaHR Moka Eva deployment. | |
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Tesla | Automotive | 125665 | $97.7B | United States | MokaHR | MokaHR Moka Eva | Cognitive Computing | 2024 | n/a | In 2024, Tesla deployed MokaHR Moka Eva, a Cognitive Computing application, to unify recruitment workflows across functions within HR and recruiting in the United States. Tesla implemented MokaHR Moka Eva to centralize candidate intake and to accelerate screening and interview-to-offer conversion across its recruiting organization. The implementation used Moka Recruiting together with Moka Eva to establish automated prescreening, standardized candidate scoring, and prioritized candidate shortlists, leveraging Cognitive Computing capabilities for consistent evaluation. Configuration emphasized templated evaluation rubrics and automated candidate qualification routing, aligning recruiter workflows and hiring manager review processes. Operational scope targeted HR, corporate talent acquisition teams, and hiring managers across Tesla functions in the United States, with governance focused on centralized screening criteria and standardized interview evaluation workflows. Rollout included adoption of common evaluation forms and calibrated interviewer scoring to reduce variability in candidate assessment. Reported outcomes include faster and more consistent screening and improved interview-to-offer conversion rates, reflecting the combined use of Moka Recruiting and Moka Eva to streamline candidate progression and decisioning in Tesla’s recruiting function. | |
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Trip.Com | Automotive | 10 | $2M | United States | MokaHR | MokaHR Moka Eva | Cognitive Computing | 2024 | n/a | In 2024 Trip.Com deployed MokaHR Moka Eva to handle large seasonal hiring volumes in the APAC region. The deployment targeted HR and recruiting workflows to scale intake for seasonal and campaign-driven hiring cycles. The implementation leveraged Moka Recruiting and MokaHR Moka Eva modules to provide AI resume screening, tailored interview question generation, and intelligent interview summaries. This use of MokaHR Moka Eva applies Cognitive Computing capabilities to automate candidate triage, surface shortlisting recommendations, and generate standardized interview intelligence for recruiter review. Operational coverage focused on HR and recruiting teams across APAC, embedding screening and interview intelligence into recruiter workflows for high-volume campaigns. Governance emphasized standardized shortlisting workflows and consistent evaluation criteria, and reported benefits included faster shortlisting and more consistent evaluation across high-volume campaigns. |
Buyer Intent: Companies Evaluating MokaHR Moka Eva
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