Contextual AI @ContextualAI
The unified context layer for Enterprise AI. Bridging the gap between LLMs and enterprise data. contextual.ai/blog/contextua… Bay Area Joined March 2023-
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Everyone wants to work with the company that promises the “sexy” AI agent, but ends up deploying the “boring” workflow in production instead. I’ve been hearing this a lot from customers recently. The reality is that workflows will become more agentic over time. Most…
Performance on standard retrieval benchmarks like BEIR/ MMTEB hasn't correlated with performance on real world retrieval evaluation datasets for a while now. The causes are twofold: - Relevance is ill-defined and subjective. - Popular retrieval benchmarks are gameable. Here I…
Performance on standard retrieval benchmarks like BEIR/ MMTEB hasn't correlated with performance on real world retrieval evaluation datasets for a while now. The causes are twofold: - Relevance is ill-defined and subjective. - Popular retrieval benchmarks are gameable. Here I… https://t.co/xd9jz1H39z
New tutorial added: Building RAG agents with Contextual AI Just added a new tutorial to my repo that shows how to build RAG agents using Contextual AI's managed platform instead of setting up all the infrastructure yourself. What's covered: You upload documents (PDFs, Word…
Everyone is posting about the “95%” Fortune article, but it’s worth reading the underlying MIT report, which contains a ton of interesting insights. My main takeaway is that Gen AI projects fail not because the models aren’t capable, but because the importance of context is…
🏆 It's official - Contextual AI is now at the top of the FACTS leaderboard for groundedness, beating out strong competition from Gemini 2.5 Pro and GPT-5! Congrats to our research team @w33lliam @rajan__vivek @nandita__naik @Thienhn97 @sheshanshag @shikibmehri on this awesome…
🏆 It's official - Contextual AI is now at the top of the FACTS leaderboard for groundedness, beating out strong competition from Gemini 2.5 Pro and GPT-5! Congrats to our research team @w33lliam @rajan__vivek @nandita__naik @Thienhn97 @sheshanshag @shikibmehri on this awesome… https://t.co/jNQDSy5txh
Thrilled to see ContextualAI's RAG agent included in this excellent resource for engineers building production-ready agents!
Thrilled to see ContextualAI's RAG agent included in this excellent resource for engineers building production-ready agents!
If you can’t measure generated code quality, you can’t improve it. We recently helped a customer who had an extensive, multimodal codebase and quickly discovered that the main hurdle to generating high fidelity code was evaluation at scale. Traditional token and embedding-based…
GPT-5 is out. Early results (and pricing) are truly impressive. Despite that, we may see that the pace of adoption (at least in enterprise) will be slower than we expect. AI system drift is becoming a major bottleneck slowing down SOTA LLM adoption in production systems. Model…
Open source AI development is critical because it democratizes access to cutting-edge architectures, enables researchers to experiment with the latest and greatest models, and creates a collaborative ecosystem where community-driven improvements can compound exponentially. While…
Open source AI development is critical because it democratizes access to cutting-edge architectures, enables researchers to experiment with the latest and greatest models, and creates a collaborative ecosystem where community-driven improvements can compound exponentially. While…
The future of AI agents isn't just about better models, it's about smarter context engineering. Today's manual approaches (hard-wiring tools, connecting databases, crafting prompts) are brittle and time-consuming. Where we’re headed is an adaptive context layer that learns from…
We had an interesting meta-learning at @aiDotEngineer World’s Fair from some of the organizers of the MCP track: there has been such an explosion in MCP Server creation, that one of the emerging challenges in this space is selecting the right one for your task.
Context engineering for static workflows is relatively straightforward: a unidirectional pipeline with pre-determined tools and RAG sources. Everything's compiled into context, but static workflows can't adapt when users need something outside the predefined flow. Dynamic…
Context engineering has become the critical bottleneck for enterprise AI. Your AI agent works perfectly in demos but breaks down with real-world data complexity. Why? I see 6 fundamental challenges that every AI engineer faces: from the "needle in a haystack" problem where models…
Continuing Open Source Summer with LMUnit! 🚀 Natural language unit testing that dominates the leaderboards: ✅ Top spots on RewardBench2 ✅ SoTA on Flask & BigBench Read the blog or paper, or find the model on @huggingface with the links below! 👇
Continuing Open Source Summer with LMUnit! 🚀 Natural language unit testing that dominates the leaderboards: ✅ Top spots on RewardBench2 ✅ SoTA on Flask & BigBench Read the blog or paper, or find the model on @huggingface with the links below! 👇 https://t.co/oHMqONhpIE
Introducing: Contextual AI MCP Server (now hosted) After great feedback with our local MCP server, we have added a hosted MCP server inside the platform! This mean every RAG agent is easily accessible via MCP. Added updated info on the hosted MCP server here:…
Our research team continues to push the envelope for what is possible! Topping the FACTS leaderboard is a crucial step in our mission to understand and reduce LLM hallucination - building AI systems that actually do what we want them to do. Worth reading the full thread below 👇.…
Our research team continues to push the envelope for what is possible! Topping the FACTS leaderboard is a crucial step in our mission to understand and reduce LLM hallucination - building AI systems that actually do what we want them to do. Worth reading the full thread below 👇.…
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