Can you introduce Gnani.ai and its mission to our TechiExpert readers?
Gnani.ai is an industry-leading deep tech voice-first generative AI company and we specialize in automating customer interactions. Backed by our several patents, we are driving advancements in generative AI, natural language understanding, speech recognition, and the seamless interaction between humans and machines.
Our product platform powers 200+ customers across diverse domains, encompassing automating multilingual conversations, speech activity detection, speech-to-text, text-to-speech, natural language understanding (NLU), and customized generative AI models. Our offerings enable businesses to elevate customer experiences, increase efficiency, and expedite growth. Our products are highly scalable and customizable, catering to the specific needs of each industry.
Gnani.ai offers a Unified Voice First generative AI Platform with products including Automation (Automate365), Agent Assist (Assist365), Omnichannel Analytics (Aura365) and Voice Biometrics (Armour365).
We are accelerating growth given the growing use of GenAI. We intend to focus on deeper market penetration in the United States, while at the same time staying focused on markets such as India.
How does Gnani.ai’s SLM ensure high accuracy and low latency compared to existing models?
Gnani.ai’s SLMs are trained on data focused on specific vertical use cases. This ensures high accuracy with no hallucinations while solving business cases in the domains for which the SLM is built. Compared to LLMs, which often are riddled with latency, inferencing costs, and other issues, Gnani.ai’s SLMs are focused on solving business problems. This helps to keep referencing costs lower and ensures practical latency in a real-time scenario. As a result, Gnani.ai’s voice-first small language generative AI models provide a unique multi-modal solution that combines high accuracy, low latency, and reduced inferencing costs compared to generic LLMs.
How will small language models shape the future of AI in the next 5-10 years?
Given the rapid pace of innovation in AI technologies, 5-10 years is a considerable time frame. In the next few years, smaller language models will allow businesses to unlock the true value of AI by addressing industry-specific challenges. For example, we are solving real-world problems in the banking, financial services and insurance, automotive and retail sectors using our gen AI-based models.
Can you share a success story using your small language model-powered solutions?
Gnani.ai has developed small language models (SLMs) based on Gen AI, trained from scratch with data specific to the banking and insurance sectors. Our benchmark tests indicate that these models achieve over 40% higher accuracy compared to existing solutions while keeping latency low and eliminating hallucinations. Gnani.ai’s SLMs are applied to multiple use cases in the BFSI sector including customer support, lead qualification, EMI collection, insurance renewals, and many more. Recently, we helped a leading bank collect over $1B in overdue EMIs using our generative AI voicebots. Additionally, we launched an omnichannel bot with a financial institution in the US, automating customer service across multiple channels using our SLM model.
How does Gnani.ai address ethical concerns like data privacy and bias?
We prioritize customer data privacy and hold certifications like ISO, SOC2, HIPAA, PCI-DSS, and more. We don’t store or use customer data on our cloud for AI model training. We are cloud agnostic, and we offer multiple deployment options for our end customers. Our voice biometrics platform enhances security for customer authentication during voice interactions.
We also offer multiple deployment models including private cloud options for our enterprise customers. With transparent data policies, we foster trust and confidence in our services.
What are Gnani.ai’s future plans for small language models?
We are actively extending our small language models (SLMs) beyond the banking, financial services, insurance, and automotive sectors, now also focusing on retail and e-commerce. Our commitment lies in developing SLMs for various domains while continuously improving the accuracy of our AI models.