Articles, teardowns, and market observations on how mobile apps are built, how they evolve, and what those signals mean for teams making product, technology, and compliance decisions.
Every piece links back to the underlying evidence so agencies, product teams, enterprise, and ecosystem readers can trace claims to the data.
What mobile app intelligence is, where the signals come from, and how to read them when the app is not yours.
How to compare apps you do not own, on monetisation, technology stack, SDKs, store performance and accessibility.
Accessibility, privacy and regulatory signals in shipped apps, and what the paperwork trail should look like.
How agents and MCP change app research, connecting Appnalysis to ChatGPT, Claude or Cursor and asking in context.
Practical walkthroughs for getting an answer out of Appnalysis, from a first question to exports and MCP access.
Comparing an app against its category on store performance, monetisation and technical choices, with the method shown.
Worked examples showing how agencies, product teams and policy teams turned app evidence into a decision.
App Store Optimisation read from evidence: what listings, ratings and store metadata actually tell you.
For agencies pitching, defending and expanding accounts with evidence about the apps in a client's category.
For product teams deciding what to build next, and proving the call with how comparable apps are actually built.
For enterprise teams running due diligence, vendor review and portfolio oversight across iOS and Android.
For regulators, researchers and policy teams who need repeatable, citable evidence on how the mobile market behaves.
Mobile app intelligence is structured, decision-ready insight into how iOS and Android apps are built and behave in the real world, drawn from real app packages, App Store and Google Play signals, and broader ecosystem sources. It covers features, SDKs, frameworks, monetisation, security signals, and architecture, not just downloads or revenue estimates. Appnalysis delivers mobile app intelligence as an AI agent so teams can ask questions in plain English and get answers grounded in real evidence, without navigating dashboards.
Mobile data intelligence is the discipline of turning raw store and app-package observations into evidence a team can defend. Three things decide whether it counts: provenance, so every figure says whether it was observed or estimated; refresh cadence, because a figure without a date is a rumour in a market that moves in release cycles; and citability, so anyone can check the claim against the app, the version and the observation. Appnalysis is built to those three tests, which is why answers arrive with their sources attached. See what mobile app intelligence covers.