Field notes from the research bench.
Long-form essays from our engineers and researchers on what actually works when AI meets production — and what quietly fails.
Latest writing
Each essay draws on more than a decade of delivery work across MLOps, Forecasting, Computer Vision, NLP, Strategy, Engineering, Generative AI, Governance, Architecture. They are written for the people who own AI systems after go-live: engineering leads, data scientists, risk teams and the executives who sponsor them.
Five MLOps mistakes we keep seeing in 2025
From feature-store sprawl to dashboards no one looks at — what we'd do differently after a decade of shipping models into production.
Why your demand forecast is biased (and what to do about it)
A practical playbook for spotting and removing systematic forecast bias — drawn from a decade of forecasting engagements.
Choosing between classical CV and deep learning
When OpenCV beats a neural net — and how to know in advance, before you have invested six months in the wrong stack.
Aspect-based sentiment without breaking the bank
A small-model recipe for accurate, fast, multilingual aspect sentiment that does not require a frontier LLM in the hot path.
Build vs buy in 2025: the new rules
How the rise of foundation models has rewritten the build-vs-buy calculus — and the rules that have stopped being true.
Reproducibility patterns we actually use
The minimum viable practices that make experiments trustworthy — drawn from systems we have been running since 2014.
RAG in the enterprise: what works in 2025
Retrieval-augmented generation has matured. Here is the architecture we now reach for by default — and the failure modes we still see weekly.
The AI Act, for practitioners who have to ship anyway
What the EU AI Act actually requires of high-risk and limited-risk AI systems — and the documentation we have been writing on every project since 2023.
The quiet comeback of small models
The 7-billion-parameter and smaller models we deploy in 2025, the gaps they fill, and why the cost story alone is not the most interesting one.
Have a problem we should write about?
Tell us what your team is wrestling with — the best essays start as client questions.