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VoiceOwl is transforming sales through AI powered conversations
The People Behind VoiceOwl
VoiceOwl’s leadership team brings together extensive expertise in AI, business strategy, and technology, gained through years of success across various industries.
- Vivek Jain (Chief Executive Officer and Founder): A serial entrepreneur with over 20 years of experience in driving technological change, Vivek is focused on advancing generative AI and leveraging it for growth and innovation. In addition to his entrepreneurial ventures, he contributes to the AI conversation through writing, workshops, and conferences.
- Ruchika Drabla Keshwani (Chief Operations Officer and Founder): With over 15 years of experience in marketing, strategy, and business development, Ruchika is a seasoned entrepreneur. Her expertise in AI, sales, and B2B growth enables her to champion innovation with a “think outside the box” approach, focusing on brand development and effective solutions.
- Piyush Keshwani (Chief Technical Officer and Founder): A leader in digital technology with over 15 years of experience, Piyush believes in the transformative power of technology. His diverse experience spans eCommerce, security, publishing, and more, with a focus on building AI/ML voicebot and chatbot platforms, as well as conversational user interfaces.
The Challenges VoiceOwl Aims to Solve with AI Automation
VoiceOwl addresses the specific challenges faced by industries such as B2B sales, BFSI, NBFC, insurance, recruitment, and eCommerce. Their AI automation solutions focus on the following key areas:
- Personalized Pre-Sales Engagement: By harnessing data from AI interactions, VoiceOwl enables sales representatives to personalize their outreach with relevant information, improving engagement and conversion rates.
- Boosting Sales Productivity: VoiceOwl’s AI-powered voicebots can verify leads, answer product inquiries, and schedule demos, freeing up sales teams to concentrate on closing deals.
- Enhanced Account-Based Marketing: Their targeted voice campaigns nurture relationships, provide personalized product information, and schedule meetings with decision-makers, fostering stronger account engagement.
- Effortless Appointment Scheduling: AI-driven virtual assistants automate the scheduling of appointments, allowing customers to book at their convenience and reducing administrative workloads.
- Actionable Call Analytics: With AI-powered analytics, VoiceOwl uncovers hidden insights from sales calls, identifying patterns and sentiments to improve customer interactions and agent performance.
Insights Gained from VoiceOwl’s Startup Journey
Throughout VoiceOwl’s startup journey, several valuable insights have helped shape its direction. CEO and Founder Vivek Jain reflects on the key lessons learned:
- The Need for Efficiency: While the team initially explored broad applications of AI, the most pressing need emerged in the sales, BFSI, NBFC, and insurance sectors, where high-volume, repetitive tasks were taxing human resources. VoiceOwl’s AI agents now automate these tasks, allowing employees to focus on more strategic efforts and improving the overall customer experience.
- Security and Compliance as Priorities: In industries with stringent regulatory environments, trust is essential. VoiceOwl has prioritized secure data handling by implementing industry-standard security measures like ISO 27001, SOC 2, GDPR, and DPDP to protect client data and ensure compliance.
- Building Trust with AI: VoiceOwl recognizes that skepticism toward AI solutions is common. The team has learned that transparency and a human-centric approach are crucial to gaining trust. VoiceOwl’s AI solutions complement human interaction rather than replace it, improving efficiency and empowering employees.
- Customer Feedback Drives Innovation: VoiceOwl’s evolution has been fueled by continuous learning and adaptation based on customer feedback. This focus on customer needs has led to a platform that seamlessly integrates into existing workflows, delivers measurable business results, and achieves over 95% accuracy across various use cases.