11 stories
AI can make an Excel report look finished before the numbers are trustworthy. Use this review workflow to trace inputs, recalculate KPIs, and separate facts from guesses.
We tested five converters on the same PDF and reviewed RowSpeak's OCR-to-Excel workflow, including analysis, charts, and dashboard sharing.
Data management software company Precisely Software Inc. today introduced the Precisely Platform, a unified system designed to make enterprise data ready for artificial intelligence. Developers also get Precisely AI Studio, a library of ready-made AI agents and apps.
Inside the silent data failures, session trust limits, browser-context execution and repair boundaries that decide if an AI-built scraper survives production.
AI that invents data is worse than no AI. Here's the trust loop DodoForm uses — snippet grounding, confidence gating, and a human review queue — so you can trust what lands in your CRM.
Compare API-first and scraping architectures through reliability engineering — uptime SLAs, schema stability, data freshness, and production failure modes.
Why monitoring AI inputs is as critical as monitoring outputs — a practical guide to data-layer observability for reliable AI systems.
Learn how to ground LLM outputs with structured real-time data using RAG and API integration to reduce hallucinations and build reliable AI applications.
Data quality — not model size — drives AI accuracy. See how structured APIs outperform noisy scraped data for RAG, agents, and ecommerce AI.
[Special thank you to Ian Kivlichan for many useful pointers (E.g. the 100+ year old Nature paper “Vox populi”) and nice feedback. 🙏 ] High-quality data is the fuel for modern data deep learning model training.
Here comes the Part 3 on learning with not enough data (Previous: Part 1 and Part 2). Let’s consider two approaches for generating synthetic data for training. Augmented data.
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