Rubrics are the framework that make this possible. They connect human insight, LLM evaluation, and measurable outcomes — turning expert judgment into structured, repeatable metrics that drive confidence in every dataset.
@snorkelai
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Trusted Scale: Data Quality Through Development Stages
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Our Trusted Scale philosophy designs data quality into every stage of development — balancing two priorities that often appear in tension: Rigorous quality assurance Operational efficiency
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Quality at Scale: Snorkel’s Rubric-Based Data Discipline
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The hardest part of delivering top-quality data isn’t delivering a single good sample. It’s delivering consistent quality at scale, over many samples, again and again. At Snorkel, we believe quality at scale isn’t a contradiction — it’s a discipline. Here’s how rubric-based
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Snorkel’s FinQA Reasoning Benchmark Tests AI Financial Analysis
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Snorkel’s FinQA Reasoning Benchmark is now live on @PrimeIntellect
! Test how well your models reason through real financial data — with multi-step tool use, SQL querying, and iterative logic. Explore it here -
Multi-Agent Systems in Enterprise Tool Use Architecture
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Dive into the full breakdown, experiments, and architecture in our latest blog https://
snorkel.ai/blog/multi-age
nts-in-the-context-of-enterprise-tool-use/
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#AI #AIAgents #MultiAgentSystems #EnterpriseAI #MachineLearning -
Performance Optimization and Cost Reduction for Production AI Systems
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And the most compelling thing is getting this performance while ALSO reducing costs when it’s time to take the system to production and things need to scale.
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Smaller Models Gain Accuracy Through Multi-Agent Coordination Setup
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In the switch to the multi-agent setup: Smaller models regained lost accuracy when configured as coordinated agents Long-context reasoning improved
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Multi-Agent Systems Cut Enterprise AI Costs
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What happens when simply using the best AI model starts to break the bank? We explored how multi-agent systems — multiple AI agents collaborating across tools — could benefit enterprise AI. Details
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GPT-5 Outperforms Mini and Nano in Multi-Agent Tool Tasks
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Our team tested single- vs multi-agent setups using GPT-5, GPT-5-mini, and GPT-5-nano, using 10K+ tools across 30 domains. In the single-agent setup, GPT-5-mini and GPT-5-nano performance degrades with longer context and more reasoning, while GPT-5 remains remarkably consistent.
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Snorkel AI scales ML workflows 20x faster with Prefect
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Snorkel AI’s ML Foundations team runs tens of thousands of workflows daily with @PrefectIO OSS—20x faster throughput, less tech debt, and tools engineers love using. Read more from our Principal Engineer Smit Shah!