Start from a question, not a blank page
A Lens is a saved starting point for a technology question. Open one to see the topics inside it, how their coverage is moving, and how they connect in the source record.
Reach for a Lens when you know the area you care about, but not yet which companies, models, products, or standards are driving the coverage.
How a Lens works. Each Lens below is a curated set of related companies, models, and technologies. Open one and Compass assembles them into a single view: what's gaining or losing coverage across the set, how they rank against each other, and how they connect in the source record.
Every figure opens to the dated articles behind it. Compass shows the movement and the evidence; what it means is your call.
| Start with | When you want to know | What you get |
|---|---|---|
| A topic | "What's changing around this one company, product, model, or technology?" | A topic workspace, and a single-topic report |
| A Lens | "Which companies, products, technologies and themes make up the question I care about?" | A reusable multi-topic workspace |
| A State of X report | "What's happening across that whole conversation — who has the attention, who's gaining or cooling, how the field is clustering, and what the press is emphasizing?" | A sourced landscape briefing — attention, movement, concentration, clusters and evidence |
The workspace lets you explore the set. State of X gives you the read you can carry into a meeting: who holds attention, who's gaining or cooling, whether attention is concentrating or spreading out, what the press keeps connecting, and the cited evidence behind the pattern. Coverage share is not market share, and movement is not a prediction.
Where the economics of running AI intersect with chips, data centers, and power — measured connections around the cost of scale.
From coding assistants to autonomous agents — track measured signals around delegation in software engineering.
The measured movement around quantum-resistant security — post-quantum cryptography, confidential computing, and related standards.
GPUs, accelerators, and cost-per-token signals across the AI compute stack.
Where spatial computing meets consumer hardware — measured activity around devices, standards, and interface models.
Disclosure rules, standards, and mandates measured alongside cybersecurity practice.
FinOps, optimization, and efficiency signals across enterprise cloud spend.
Humanoid robots, automation, and embodied intelligence — measured links between AI systems and physical machines.
Platforms, governance, and integration signals around enterprise AI deployment.
Safety frameworks, regulation, and oversight measured across AI-related regions and domains.
Small models, NPUs, and on-device inference — measured signals around edge AI.
IDEs, CI/CD, and platforms measured across the daily work of building software.