AI, Machine Learning, Reinforcement Learning, and MLOps Articles

How Winder.AI Helped Duetto Evaluate Reinforcement Learning for Hotel Pricing

Published

Apr 23, 2026

Author

Dr. Phil Winder

CEO

Winder.AI helped Duetto evaluate offline reinforcement learning for dynamic hotel pricing. Over five months, the engagement progressed from behavioural cloning baselines through Implicit Q-Learning experiments on real booking data, revealing where RL outperforms simpler approaches, what data quality prerequisites exist, and how to evaluate pricing agents when ground truth is unavailable.

What a Custom AI Contract Review Pipeline Looks Like

Published

Apr 22, 2026

Author

Dr. Phil Winder

CEO

“AI contract review” is a popular keyword to compete for. Look, I’m doing it right now! A couple of years ago my colleagues and I half-built a contract review service prototype. We decided not to take it any further, but that was a mistake. It’s now very hot.

So hot you can easily find a wall of product pages. Sign up, upload your contracts, get results. The pitch is simple. For straightforward use cases, it works.

But what if your contracts don’t fit their templates? What if your review process has steps a product can’t model? What if your data can’t leave your infrastructure? What if your firm’s clause playbook differs from the vendor’s defaults?

This article walks through what a custom-built contract review pipeline actually involves.

When Off-the-Shelf Legal AI Tools Hit a Ceiling

Published

Apr 8, 2026

Author

Dr. Phil Winder

CEO

Legal AI adoption has accelerated. Litify’s 2025 State of AI in Legal Report found that 78% of legal professionals now use AI in some form, up from 23% just two years earlier. In Winder.AI’s 13 year history (and counting!) I have observed a similar trend first hand.

On the back of this trend, significant VC funding has attempted to capture a share of this market. $2.4 billion was invested in 2025. A tsunami of products promise to automate contract review, legal research, and document analysis. Many of them work for a while. Then firms hit the ceiling.

This article is about where that ceiling is and what lies beyond it.

5 Document Workflows AI Handles Better Than People

Published

Mar 23, 2026

Author

Dr. Phil Winder

CEO

Not every document workflow needs AI. If you process ten invoices a week from the same supplier in the same format, manual handling is fine. But some workflows sit at the intersection of high volume, varied formats, and expensive errors. Those are the ones where AI document processing consistently outperforms human processing on speed, accuracy, and cost.

Five specific document workflows deliver a measurable advantage when you hand them to AI.

AI Document Processing vs Traditional OCR: What Actually Changed

Published

Mar 17, 2026

Author

Dr. Phil Winder

CEO

Most organisations already have some form of document scanning. A multifunction printer with OCR. An expense tool that reads receipts. A document management system that converts scans to searchable PDFs. If you’re reading this, then you probably already know that scanning alone isn’t enough.

What Is Document Intelligence? A Complete Guide for 2026

Published

Mar 16, 2026

Author

Dr. Phil Winder

CEO

Every organisation runs on documents. Invoices, contracts, claims, applications, correspondence. They contain the data that drives decisions, triggers payments, and satisfies compliance requirements. The problem is that most of this data is trapped in unstructured formats that only humans can read.

Document intelligence changes that. It’s the AI capability that reads, understands, and extracts structured data from unstructured documents. It is rapidly replacing the manual data entry and basic scanning workflows that most businesses still rely on.

How to Migrate a Codebase from Python to Go Using an AI Coding Assistant

Published

Feb 17, 2026

Author

Dr. Phil Winder

CEO

I recently migrated a production Python codebase to Go using Claude Code as the primary coding agent. The codebase was Kodit, an MCP server and CLI tool for indexing code repositories. It had a well-structured Python backend with a FastAPI server, SQLAlchemy ORM, Pydantic models, and a search pipeline combining BM25 and vector embeddings.

AI Confidence: Evaluating AI Models with Synthetic Data

Published

Nov 19, 2025

Author

Dr. Phil Winder

CEO

Building AI-powered applications is exciting, until you need to evaluate whether your model actually works. How do you test an AI system that gives different answers every time? How do you gather enough test data to be confident in your results? This one-hour practical webinar will transform you from uncertain to confident about AI evaluation.

How Winder.AI Helped Apartment List Eliminate Data Drift and Scale MLOps Automation

Published

Nov 3, 2025

Author

Dr. Phil Winder

CEO

Winder.AI helped Apartment List modernize its machine learning operations by unifying data pipelines, automating Kubeflow workflows, and introducing enterprise-grade governance. The outcome: consistent training and inference data, faster deployment cycles, and self-service capabilities that enabled Apartment List’s data science team to scale model delivery with confidence.

Leading with AI: A Strategic Playbook for CEOs and CTOs and Building Sustainable and Secure GenAI Systems

Published

Sep 24, 2025

Author

Dr. Phil Winder

CEO

While 71% of organizations have deployed generative AI in at least one business function, fewer than 5% of AI pilots achieve meaningful revenue impact. This gap between experimentation and production success represents both the greatest challenge and opportunity for technical leaders in 2025.