Kruti, Krutrim’s agentic AI assistant, is designed to go beyond traditional chatbots by combining advanced AI models, multi-language support, and intelligent task execution. Its core technology enables it to understand complex requests, plan multi-step actions, and interact seamlessly across languages and platforms. Below is a breakdown of how Kruti achieves this:
1. "Agentic AI" - Not Just a Chatbot
Kruti functions as an "agentic" AI, meaning it can reason, plan, and execute multi-step tasks to fulfill your requests. Instead of just responding with information, it breaks down your request into smaller tasks and completes them.
Example: If you say, "I need to get to the airport by 6 AM," Kruti will:
2. Powered by Advanced AI Models
The backend combines Ola's proprietary Krutrim V2 model (with 12 billion parameters) with several open-source large language models. This hybrid approach makes it both powerful and cost-effective.
3. Multi-Language Support
Kruti supports both text and voice in 13 Indian languages, including Hindi, Tamil, Malayalam, and English, with speech recognition built to identify regional dialects and accents.
Example: A user in Kerala can type in Malayalam "എനിക്ക് ഒരു ടാക്സി വേണം" ("I need a taxi") and Kruti will book it and respond in Malayalam.
How Kruti Processes Your Requests
Kruti doesn’t just respond to questions; it acts on them. Its processing framework combines intent recognition, task decomposition, coordinated agents, and direct integration with services to fulfill complex user requests efficiently. Here’s how it works step by step:
Step 1: Understanding Your Intent
Kruti uses intent recognition to parse queries. For example, "Order dosa" triggers the Food Ordering Agent while understanding context like "Make it quick" from previous interactions.
Step 2: Breaking Down Tasks
When a query is submitted, Kruti breaks it into smaller sub-tasks that are carried out via agent-to-agent protocols, reportedly with over 90% accuracy.
Step 3: Multiple Agents Working Together
Kruti uses a network of agents that work together to execute tasks, sometimes in sequence, sometimes in parallel, using an agent-to-agent protocol to coordinate intelligently.
Step 4: Connecting to Real Services
MCP (Model Context Protocol) allows Kruti to communicate directly with databases or APIs, letting it integrate with apps and services to actually complete Botpress.
Two Modes of Operation
Kruti adapts its response style based on the complexity of your requests, offering two distinct modes to ensure efficiency and depth. Whether you need a quick answer or a detailed analysis, Kruti switches seamlessly between Auto Mode and In-Depth Mode:
Auto Mode - For Quick Answers
Auto Mode handles straightforward queries with minimal back-and-forth, like "What's the temperature in Delhi today?" - Kruti responds quickly: "It's 32°C with clear skies."
In-Depth Mode - For Complex Tasks
When users need more than a quick answer, In-Depth Mode steps in, designed for research, learning, or tackling multi-layered questions with detailed, contextual responses.
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