EVA ROBOT (Ева) is a voice AI robot used to automate phone communications. According to official information, it can perform outbound and inbound calls, conduct conversations with customers, handle objections, and sync data to CRM.
Uses:
- Sales automation: cold calling, initial lead handling, facilitating deal closure.
- Recruitment automation: parsing resumes, automatically contacting candidates, inviting to interviews, and can integrate with HH.ru.
- Customer service: answering incoming calls, answering questions, booking services, routing requests, advertised as 24/7 without breaks.
- Messaging: bulk messaging via WhatsApp, customer reactivation and follow-up.
- Call center optimization: reducing human agents, increasing call volume, providing call analytics.
Main capabilities (according to official information):
- Up to 200 calls per minute, up to 30,000 per day.
- Natural conversation, with objection-handling capability, officially described as "no robot tone."
- Integrations with Bitrix24, amoCRM, 1C, Telegram, WhatsApp, etc., with CRM integration officially stated as free.
- Provides call recording and analytics.
- In recruitment scenarios, can process 120–180 resumes per day and arrange interviews for 11–14 candidates.
How to use: The officially described implementation process has 4 steps: 1) analyze business processes, identify growth points, calculate ROI; 2) train the AI, write scripts, integrate CRM (about 2 weeks); 3) test on a real database and adjust scripts; 4) full launch, monitoring, and onboarding new tasks. Users can submit a request via the official website; it is officially stated that they will call back within 2 hours and provide a free business audit.
Applicable scenarios: Suitable for enterprises with large outbound or inbound call needs, such as sales teams, recruitment departments, customer service centers, etc., especially in the Russian-language market.
Limitations and information not provided: Official information does not provide details such as specific pricing, plans, technical architecture, language support scope, data storage location, compliance certifications, SLA, etc. Some performance data comes from customer cases, and actual results may vary by business.
