Gnani.ai
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About
Gnani.ai is a comprehensive enterprise-grade suite of "Agentic AI" tools designed to transform customer experience (CX) and operational efficiency. The platform centers on providing sophisticated AI agents that move beyond simple chatbot responses to handle complex, end-to-end business processes. By integrating voice, chat, WhatsApp, SMS, and email, Gnani.ai allows businesses to manage customer interactions across multiple touchpoints within a single orchestration core. The platform’s primary goal is to help enterprises scale their services while maintaining a high level of personalization and local relevance, particularly through its robust support for diverse languages and dialects. At the heart of the Gnani.ai ecosystem is the Inya platform, a no-code builder that allows teams to deploy production-ready AI agents in minutes. The technology stack is powered by a multi-LLM architecture and features industry-leading proprietary components such as high-accuracy Speech-to-Text (ASR) for over 40 languages, including more than 12 Indian regional languages. Beyond speech, the suite includes specialized products like Inya Shield for voice biometrics and authentication, Inya Insights for real-time call analytics and quality assurance, and Inya Assist, which provides live guidance to human agents during customer calls. This "Agentic" approach means the AI can proactively trigger APIs, update CRMs like Salesforce or HubSpot, and negotiate outcomes such as debt settlements or appointment scheduling without human intervention. The platform is specifically engineered for high-volume, high-stakes industries including banking, telecommunications, insurance, and automotive. For instance, in the banking sector, it handles everything from automated debt collection and lead qualification to secure KYC verification using voice biometrics. It is equally effective in the hospitality and retail sectors for managing bookings and upsell opportunities. The suite’s ability to handle "code-switching" (switching between languages mid-sentence) makes it uniquely suited for markets with high linguistic diversity, where standard global NLP models often struggle with accuracy and context. What sets Gnani.ai apart from typical conversational AI providers is its deep focus on security and measurable business impact. Unlike many competitors that offer scripted NLP flows, Gnani.ai leverages generative AI to handle interruptions, objections, and context-aware empathy. The platform is built on a secure foundation, maintaining certifications for SOC2, HIPAA, ISO 27001, and GDPR, which is critical for the enterprises it serves. With reported outcomes such as a 60% reduction in operational expenditure and significant revenue impact for global brands, Gnani.ai positions itself as a core strategic tool rather than just a secondary automation project.
Pros & Cons
High accuracy for Indian languages, outperforming generic providers by up to 30%.
Robust security compliance including HIPAA and GDPR for sensitive enterprise data.
Truly agentic capabilities that trigger API workflows and close the loop on tasks.
Supports multiple deployment models including cloud, private VPC, and on-premise.
Handles complex multilingual conversations with mid-sentence language switching.
Pricing is not publicly disclosed and requires a sales consultation for a quote.
The complexity of the platform may require significant setup time for deep enterprise integrations.
Primarily designed for large enterprises, which may be overkill for smaller organizations.
Use Cases
Debt collection teams can use the Victor agent to automate reminders and negotiate settlements directly within policy limits.
Compliance officers in banking can deploy Eva to verify identities and capture biometrics for automated KYC processing.
Real estate marketing teams can use Scout to qualify leads and schedule site visits automatically 24/7.
HR departments can implement Ally to provide instant answers for employee benefits and policy queries across internal channels.
Retailers can use the Neo agent to automate service and installation bookings by syncing directly with field team calendars.
Platform
Features
• conversational analytics
• real-time agent assist
• no-code agent builder
• omnichannel orchestration
• multi-llm architecture
• hybrid/on-premise deployment
• voice biometrics & authentication
• multilingual asr (40+ languages)
FAQs
Which languages are supported by Gnani.ai?
The platform supports over 40 languages globally, including more than 12 Indian regional languages such as Tamil, Malayalam, and Hindi, with high conversion accuracy.
Can Gnani.ai integrate with my existing CRM?
Yes, Gnani.ai offers over 100 integrations with major enterprise platforms including Salesforce, HubSpot, SAP, Oracle, and Zoho to trigger real-time data updates.
What security certifications does the platform have?
Gnani.ai is highly secure and holds certifications for SOC2, HIPAA, ISO 27001, and GDPR, making it suitable for banking and healthcare industries.
Does it support voice-based authentication?
Yes, the Inya Shield product provides voice biometrics for secure customer authentication and real-time voice fraud detection during banking or support calls.
What is the Inya No-Code Builder?
Inya is a DIY platform that allows users to build and deploy production-ready AI agents in under five minutes using a drag-and-drop interface and API plugins.
Pricing Plans
Enterprise
Unknown Price• Inya Workforce Agentic AI
• Inya Assist Agent Support
• Inya Insights Analytics
• Inya Shield Biometrics
• Support for 40+ Languages
• 100+ Enterprise Integrations
• Multi-LLM Architecture
• SOC2/HIPAA Compliance
Job Opportunities
Customer Success Manager
Streamline enterprise CX with multilingual AI agents that automate voice, chat, and email workflows to reduce operational costs and improve customer satisfaction.
Education Requirements:
A bachelor or MBA degree is preferred
Experience Requirements:
3 - 7 years experience
Minimum 3 years of work experience as a Customer Success Manager or similar role
Experience in dealing with large and mid size Enterprise customers in India
Quota carrying experience
Experience working in a SAAS organization is desirable
Other Requirements:
Exceptional ability to communicate and foster positive business relationships
Technical skills in SAAS and Contact centers is a plus
Ability to travel for client meetings
Clear grasp of digital technology stacks - API's, middleware, and ecosystems
Responsibilities:
Establish clear client retention goals
Define success milestones for clients and employees
Promote the value of Gnani.ai’s software and services
Upsell and Cross-sell Gnani.ai’s software and services
Review customer complaints and seek to improve the customer experience
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AI Project Manager
Streamline enterprise CX with multilingual AI agents that automate voice, chat, and email workflows to reduce operational costs and improve customer satisfaction.
Education Requirements:
PMP/PRINCE2 certification is a plus
Experience Requirements:
8-12 years of project/program management experience in technology product companies
Proven experience handling enterprise-level Indian customers
Strong exposure to AI/ML-based product implementations or integrations
Deep understanding of Agile/Scrum delivery practices
Demonstrated ability to lead multi-disciplinary teams
Other Requirements:
Skilled in using tools like JIRA, Asana, or MS Project
Exceptional stakeholder management and communication skills
Comfortable with fast-paced environments and ambiguity
Responsibilities:
Own the full lifecycle of enterprise project delivery with a focus on AI product implementations
Serve as the key point of contact for customer communication
Lead customer onboarding and requirement gathering
Drive project governance – timelines, scope, risk management, and resource planning
Collaborate with internal product teams to align business goals
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Presales Engineer
Streamline enterprise CX with multilingual AI agents that automate voice, chat, and email workflows to reduce operational costs and improve customer satisfaction.
Education Requirements:
Degree in Computer Science, Engineering, or a related field
Experience Requirements:
3 - 5 years experience
Minimum 3 years of proven work experience as a Pre-Sales Engineer or similar role
Experience working in a SAAS organization is a must
Experience in dealing with large and mid size Enterprise customers in India
Other Requirements:
Strong problem-solving and prioritization skills
Strong presentation skills
Responsibilities:
Develop solutions for AI & ML based Omni-Channel Automation
Organize, plan, create & deliver compelling proof of concept demonstrations
Ensure solutions in Statement of Work are in line with client requirements
Manage the sales bid process by responding to RFI’s & RFP
Liaise with Product Managers to provide feedback about product requirements
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