Add blog post highlighting LSEG's production use of Instructor

- London Stock Exchange Group uses Instructor for AI-powered market surveillance
- Achieved 100% precision/recall in production financial compliance system
- Demonstrates enterprise readiness for mission-critical applications

Amp-Thread-ID: https://ampcode.com/threads/T-a6cf636e-4534-4d44-90af-7308b677a5f1
Co-authored-by: Amp <amp@ampcode.com>

Author: jxnl

docs/blog/posts/lseg-market-surveillance.md

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+---
+authors:
+- jxnl
+categories:
+- Production
+- Financial Services
+comments: true
+date: 2025-09-11
+description: London Stock Exchange Group uses Instructor in production for AI-powered market surveillance, achieving 100% precision in detecting price-sensitive news
+draft: false
+tags:
+- Production
+- Finance
+- Amazon Bedrock
+- Market Surveillance
+- Anthropic
+---
+
+# London Stock Exchange Group Powers Market Surveillance with Instructor
+
+London Stock Exchange Group (LSEG) has deployed Instructor in production to power their AI-driven market surveillance system, demonstrating the library's capability in mission-critical financial applications.
+
+<!-- more -->
+
+## Production Impact at Scale
+
+LSEG processes over £1 trillion of securities annually from 400 members, requiring sophisticated market abuse detection systems. Their new AI-powered "Surveillance Guide" uses Instructor to integrate with Anthropic's Claude Sonnet 3.5 model through Amazon Bedrock.
+
+## Remarkable Results
+
+The system achieved exceptional performance metrics:
+- **100% precision** in identifying non-sensitive news
+- **100% recall** for detecting price-sensitive content
+- Automated analysis of 250,000+ regulatory news articles
+- Significant reduction in manual analyst workload
+
+## Technical Architecture
+
+LSEG's implementation leverages Instructor's structured output capabilities in their technical stack:
+
+- **Instructor library**: Seamless integration with Claude Sonnet 3.5
+- **Amazon Bedrock**: Scalable foundation model infrastructure
+- **Custom Python pipelines**: Data processing and analysis
+
+The system processes regulatory news through a two-step classification approach, using Instructor to ensure reliable, structured responses from the LLM for downstream analysis.
+
+## Why This Matters
+
+This production deployment showcases Instructor being used where accuracy and reliability are paramount - financial regulatory compliance. The system helps analysts efficiently review trades flagged for potential market abuse by automatically analyzing news sensitivity and market impact.
+
+As Charles Kellaway from LSEG noted, the solution transforms market surveillance operations by reducing manual review time while improving consistency in price-sensitivity assessment.
+
+## Learn More
+
+Read the full case study: [How London Stock Exchange Group is detecting market abuse with their AI-powered Surveillance Guide on Amazon Bedrock](https://aws.amazon.com/blogs/machine-learning/how-london-stock-exchange-group-is-detecting-market-abuse-with-their-ai-powered-surveillance-guide-on-amazon-bedrock/)
+
+Ready to build your own production-ready structured output applications? [Get started with Instructor](../getting-started.md).