JUXT AI Radar
An introduction to the AI Radar from our CTO, Henry Garner
Keeping pace with AI development feels increasingly difficult. New tools appear weekly, claims about capabilities shift monthly, and what seemed essential last quarter might be yesterday’s news.
Over the past year, our teams have been applying AI across client projects, from coding assistants to agent frameworks, from prompt engineering to model selection. We’ve seen what works in practice, what doesn’t live up to the marketing, and where the real value lies for organisations trying to make sensible technology choices.
We’ve distilled these insights into our first AI Radar: an opinionated guide to the tools, techniques, and platforms we think are worth your attention right now. It’s structured around four rings (adopt, trial, assess, and hold) making it easier to understand what’s ready for production use versus what needs more time to mature.
This isn’t a snapshot: we’ll be updating it regularly as the landscape evolves and our understanding deepens. If you’re navigating AI adoption in your organisation, we hope it provides a useful reference point.
Henry Garner (CTO, JUXT), October 2025
Radar Overview
Our radar is organized into four main categories, each containing technologies evaluated across four adoption levels:
- Adopt: Technologies we recommend using now
- Trial: Worth exploring for new projects
- Assess: Keep under observation
- Hold: Not recommended for new projects
Categories
Techniques
AI methodologies, approaches, and practices that shape how we build intelligent systems.
Languages & Frameworks
Programming languages, libraries, and frameworks that power AI development.
Tools
Software tools and utilities that enhance AI development workflows.
Platforms
Infrastructure and platform services that support AI applications.
Contributing
This radar represents our current viewpoint and will be updated regularly. We welcome feedback and suggestions from the community, you can reach us on LinkedIn, BlueSky and via email. Each technology entry includes detailed reasoning for its placement, helping you make informed decisions for your AI projects.
