Sarvam AI Integrations

Sarvam-30B is a cutting-edge open-source language model designed as a robust platform for real-time conversational AI and intricate reasoning tasks, highlighting its effectiveness in multilingual environments and practical applications. With its impressive 30 billion parameters, the model leverages a Mixture-of-Experts (MoE) approach that activates only a fraction of its parameters for each interaction, enabling high efficiency and minimal latency, making it ideal for use in resource-constrained settings such as local devices and edge computing systems. It stands out in a variety of conversational scenarios, programming challenges, and logical reasoning tasks, delivering remarkable performance in more than 20 Indian languages, which highlights its versatility for multilingual use and voice recognition systems. Its dual-tier architecture positions it as a rapid and easily deployable "conversational workhorse," employing MoE strategies to reduce computational demands while maintaining top-notch performance. This innovative model not only improves the overall user experience but also expands its accessibility across a wide range of linguistic contexts, making it a valuable tool for developers and businesses aiming to engage diverse audiences effectively. Additionally, Sarvam-30B's design allows for continuous improvement and adaptation, ensuring that it remains relevant in the ever-evolving landscape of AI technology.

Sarvam-105B is recognized as the leading large language model in Sarvam's collection of open-source tools, crafted to deliver outstanding reasoning skills, multilingual understanding, and agent-driven functionality within a cohesive and scalable system. This Mixture-of-Experts (MoE) architecture features an astonishing 105 billion parameters, activating only a portion for each token processed, which ensures remarkable computational efficiency while handling complex tasks. It is specifically tailored for sophisticated reasoning, programming, mathematical problem-solving, and agentic functions, making it ideal for situations that require multi-step solutions and structured outputs instead of just basic dialogue. With an impressive capacity to process lengthy contexts of around 128K tokens, Sarvam-105B is adept at managing extensive texts, lengthy conversations, and intricate analytical tasks, maintaining coherence throughout these engagements. Furthermore, its versatile design allows for a wide array of applications, equipping users with powerful tools to address a multitude of intellectual challenges. This flexibility enhances its utility across various domains, further solidifying its status as a premier choice for advanced language model needs.

Sarvam-M is a cutting-edge multilingual large language model designed to excel in a variety of Indian languages while seamlessly tackling complex mathematical and programming tasks within a unified framework. Built upon the Mistral-Small architecture, it features a powerful configuration with 24 billion parameters and has undergone extensive refinement through methods like supervised fine-tuning and reinforcement learning, ensuring both accuracy and efficiency. This model is expertly crafted to support over ten major Indic languages, effectively managing native scripts, romanized text, and code-mixed entries, which promotes fluid multilingual communication across diverse settings. Furthermore, Sarvam-M incorporates a hybrid reasoning approach that allows it to switch between an in-depth “thinking” mode for challenging problems, such as mathematics and logic puzzles, and a quick response mode for more routine questions, striking an optimal balance between rapidity and performance. As such, Sarvam-M stands out as an essential resource for users who wish to navigate an increasingly varied linguistic landscape, enhancing their interaction with technology in meaningful ways. Its innovative design positions it as a key player in advancing language model capabilities in the realm of multilingual applications.

Sarvam Conversational Agents, or Sarvam Samvaad, represents a dynamic conversational AI solution designed specifically for enterprises, facilitating the development, launch, and growth of advanced, human-like agents that can function effortlessly across a variety of communication channels. This innovative platform enables organizations to manage voice calls, WhatsApp messaging, in-app communications, and web interactions through an integrated system, ensuring that the agent retains context and memory across multiple platforms. By seamlessly integrating with essential enterprise systems such as CRM, core banking, and payment solutions, it empowers agents to access real-time customer data, execute workflows, and automatically refresh business systems with the latest information. Additionally, it shines in multilingual communication, especially in Indian languages, allowing agents to accurately understand complex phrases, colloquial expressions, alphanumeric strings, and proper nouns. Specifically engineered for production settings, Sarvam Conversational Agents supports businesses in transitioning smoothly from pilot stages to comprehensive implementation, ensuring operational continuity. This flexibility significantly enriches the customer experience, rendering interactions not only more intuitive but also highly effective, ultimately leading to greater customer satisfaction and loyalty.

Indus serves as the official conversational AI platform for Sarvam, created to facilitate effortless user interaction with its advanced sovereign language models through a user-friendly real-time chat interface. Introduced in February 2026 during a limited beta phase, this platform acts as the primary means for users to engage with Sarvam's impressive 105-billion-parameter model, which integrates intricate reasoning capabilities, multilingual understanding, and conversational traits into a single application. Specifically designed for the Indian audience, Indus supports more than 22 Indian languages, incorporating native scripts and code-mixed inputs while maintaining cultural and contextual relevance for effective communication. It enables users to interact through both text and voice, allowing for natural conversations and responses that can be delivered in text form or as synthesized audio, thus creating an accessible, voice-first interface suitable for various use cases. This forward-thinking approach not only boosts user interaction but also significantly expands the reach of AI technology, making it more accessible to individuals from a multitude of backgrounds and enhancing the overall experience of engaging with artificial intelligence. Furthermore, this inclusive design aims to bridge communication gaps, ensuring that users feel empowered and understood, regardless of their linguistic preferences.