Contextual AI (@ContextualAI) / X

Contextual AI

259 posts

Contextual AI

@ContextualAI

Expert AI for advanced industries

Bay Area

contextual.ai/blog/introduci…

Joined March 2023

Pinned
Contextual AI
@ContextualAI
Jan 27
Announcing Agent Composer: AI that works when it actually IS rocket science. Technical teams can now automate the routine (but complex) tasks that used to take hours every week—root cause analysis, production planning, test code generation— and reduce them down to minutes, so
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Contextual AI
@ContextualAI
Apr 1
Stop spending days manually root-causing infotainment failures across a dozen subsystems and three different teams. Generic AI breaks here — logs are too large, too fragmented, too system-specific. Our multi-agent workflow processes multiple subsystem logs simultaneously and
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Contextual AI reposted
Abdallah Bashir
@abdallah197_
Mar 5
Search agents, whether they're powering deep research, or multi-step QA over a private corpus, spend most of their time and compute in the research loop: query, search, reason, repeat. We wanted to make that loop faster and more accurate. So we optimized two things jointly: the
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Contextual AI
@ContextualAI
Mar 5
Stop spending 8+ hours manually root-causing semiconductor device failures. Generic AI breaks here — logs are too large, error codes too device-specific. Our agentic workflow processes multiple logs simultaneously and delivers a complete root cause report in 20 min or less — no
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Contextual AI
@ContextualAI
Feb 6
Excited to share our latest breakthrough: ⚡BlitzRank! This innovative LLM reranker optimizes token usage with tournament graphs, delivering 25-40% efficiency gains while maintaining top-tier quality across benchmarks. Huge props to @sheshanshag and @Thienhn97 for this
Sheshansh Agrawal
@sheshanshag
Feb 6
**New research: Introducing ⚡BlitzRank** Current LLM rerankers waste tokens on information they already have. If A > B and B > C, you already know A > C, existing methods don’t track this. BlitzRank fixes this. It uses tournament graphs to extract maximal information from each
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Contextual AI reposted
Sheshansh Agrawal
@sheshanshag
Feb 6
**New research: Introducing ⚡BlitzRank** Current LLM rerankers waste tokens on information they already have. If A > B and B > C, you already know A > C, existing methods don’t track this. BlitzRank fixes this. It uses tournament graphs to extract maximal information from each
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Contextual AI
@ContextualAI
Feb 5
❌ Stop manually searching semiconductor datasheets, support logs, and device files to troubleshoot customer issues. Use context-aware AI that automates research in minutes, not hours—investigating vague questions, synthesizing answers, and verifying sources with bounding box
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Contextual AI reposted
anshuman
@athleticKoder
Jan 28
Contextual AI just killed n8n.
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Contextual AI
@ContextualAI
Jan 27
Replying to @ContextualAI
Check out the link our bio to learn more about the launch 🚀
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Contextual AI
@ContextualAI
Jan 27
Replying to @ContextualAI
Here are some examples of cool use cases we've built with our customers: - An advanced manufacturer reduced root-cause analysis from 8 hours to 20 minutes by automating sensor data parsing and log correlation. - A global strategy consulting firm reduced manual research from
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Contextual AI
@ContextualAI
Jan 27
Replying to @ContextualAI
Getting started is easy: Three ways to build (zero code required): 1) Pre-built agents for common workflows 2) Generate from a natural language prompt 3) Drag-and-drop builder for full control 4) BONUS: for developers, agents can also be fully configured using YAML ✓ Free
GIF
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Contextual AI
@ContextualAI
Jan 27
Replying to @ContextualAI
Context engineering used to mean a hard choice: DIY ($$$$, months of development, scarce AI experts) or point solutions (inflexible, can’t scale) Agent Composer offers customizable prebuilt dynamic agents and static workflows on your most complex data, in days not months.
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Contextual AI
@ContextualAI
Jan 27
Replying to @ContextualAI
The problem: Generic AI can summarize docs and answer simple questions. It can even write code. But it can't handle complex, domain specific work. It isn’t a model problem… it’s a context problem To tackle the most challenging technical tasks, AI needs to understand lots of
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