Research & Insights.
Welcome to the Sabr Research Lab. Here we publish our latest empirical findings, technical reports, and architectural deep-dives into specialized Small Language Models and reasoning architectures.
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Showing 1-10 of 10 articles
SR-AppellateLaw
Specializing SLMs for Appellate Law with Proprietary SFT
Decoding LLM Hallucinations
A Technical Review of LLM Errors and Attribution Frameworks
Achieving 70% Accuracy in Legal Outcome Prediction
Benchmarking SAGE AI on the AnnoCaseLaw dataset.
RAL: Retrieval Augmented Logic
What are RAL and how are they useful?
SAGE AI: A Generic Decision Engine
Engineering the Architecture of Organizational Decision Making.
Enhancing LLM Reasoning with Agentic Systems
How structure helps enhance reasoning capabilities in complex environments.
Case Study: Validating Alpha with Synthetic Data
Moving beyond historical backtesting by generating synthetic market universes to quantify strategy robustness.
Case Study: High-Performance Backtesting Infrastructure
Delivering a distributed, cloud-native framework to accelerate research loops for institutional partners.
Case Study: Engineering a Financial Data Factory
Architecting a serverless 'Zero-Touch' pipeline to handle large-scale ingestion for a quantitative client.
Case Study: Dynamic Sector Analysis for Risk Modeling
Deploying unsupervised learning engines to identify 'empirical sectors' and hidden correlations in real-time.