As builders of AI systems for the enterprise, we build and measure our models according to the value they bring to the enterprise. That's why our benchmarks focus on comparisons with other enterprise-focused open model providers, such as Mistral, Cohere, and Llama
LLMS
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AI-Powered Development Workflow: Grok 3, o1-Pro and Cursor Stack
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This is the workflow right here. More powerful AIs like Grok 3 or o1-Pro to map out the product and decide on best stack. Cursor + Claude 3.7 + Relevant MCPs to actually build.
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Build Autonomous Deep Research Agent with LangGraph GPT-4
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Build a Deep Research Agent An autonomous research agent built with LangGraph that combines GPT-4 and Tavily AI to perform parallel research and generate structured reports, all through sophisticated state management. Check out the implementation: https://
analyticsvidhya.com/blog/2025/02/b
uild-your-own-deep-research-agent/
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Deno and LangChain.js: Building AI Apps with Local LLMs
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Deno Meets Local LLMs Build powerful AI applications with Deno and LangChain.js in this hands-on guide. Featuring local LLM integration, structured outputs, and visual workflows using RunnableSequence. Check out the guide on the Deno blog https://
deno.com/blog/the-dino-
llama-and-whale
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Hybrid RAG with EnsembleRetriever for Superior Search
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Hybrid RAG with EnsembleRetriever EnsembleRetriever enhances RAG accuracy by combining semantic search and BM25 ranking in a powerful hybrid approach, delivering superior search performance. Watch now: https://
youtube.com/watch?v=UVQxMk
fQQbw
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1.6 Excels at RAG and Long Context Grounded Question Answering
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1.6 excels at RAG and long context grounded question answering tasks – that is where enterprises see the most value.
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Text-to-SQL AI: LangChain Agents and Database Query
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Text-to-SQL Guide Build an AI system that turns natural language into SQL queries using LangChain Agents and SQLDatabaseToolkit. This comprehensive tutorial takes you from setup to deployment with practical database examples. Watch now to transform your database queries!
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AI Self-Improvement Breakthrough Shifts Product Development Bottlenecks
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Some key takeaways: 1. Anton’s team discovered a breakthrough in AI “unsticking itself”—allowing the AI to keep improving and fixing its own bugs. 2. The biggest bottleneck in product development is shifting—from “Who can build it?” to “Who knows what to build?” 3. Community
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Converting Natural Language to SQL with LangChain Agents
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NL to SQL Guide Build an AI system that converts English to SQL using LangChain Agents & SQLDatabaseToolkit. Make database querying accessible to non-technical users with natural language processing. Learn how: https://
youtu.be/YNbxw_QZ9yI -
LLMs Will Find Ways to Perceive the World
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LLMs will find a way to perceive the world https://t.co/AXkhS4vevs
— hardmaru (@hardmaru) 9 mars 2025LLMs will find a way to perceive the world