Android app development cost for legal & professional services

There is no single figure, and quoting one would be the least useful thing this page could do — the same pairing spans several-fold depending on scope, compliance and how many surfaces you ship. What this page gives you instead is what the pairing demands: the regimes that may apply, the systems of record you will be asked to integrate with, the device matrix and the release path. The calculator below is already fixed to Android and legal & professional services — answer what is left and it returns a cost range, hours, timeline, team and running costs for your scope.

Because legal & professional services brings its own obligations before you write a feature: SOC 2 Type II, Professional confidentiality rules, GDPR may apply, you will be asked to integrate with systems like DocuSign / Dropbox Sign and iManage / NetDocuments / SharePoint, and there are typically 5 distinct roles rather than one. The platform contributes its own separate costs — the device matrix, Google Play review — and those are independent of the industry.

Because you are not shipping to one device family. Android spans thousands of models, four density buckets, five OS versions still in meaningful use, and vendor skins from Samsung, Xiaomi, Oppo and others that change how notifications, background work and permissions behave. A realistic matrix is 20–30 configurations, which is roughly 60–80 hours of QA per release cycle that an iOS-only build simply does not incur.

For Android alone, native Kotlin is usually cheaper — you are not paying a framework premium or writing bridges. Flutter and React Native only win once you need iOS too, at which point one codebase serving both costs roughly 24% more than a single native app instead of 170% more. Choose native if Android is your only target or you need deep hardware access; choose cross-platform if both mobile platforms are in scope and your UI is fairly conventional.

Yes, and clients increasingly expect it, but the professional liability changes the engineering. Every AI output needs source attribution, a human review step and an audit record of who accepted what. Retrieval over the firm’s own documents rather than open-ended generation is the pattern that works. Budget $50,000–$120,000 for a properly grounded, evaluated implementation — most of that in retrieval quality and evaluation rather than the model call.

It is a planning estimate, not a quote. The band shown is roughly plus or minus 15–20% for a well-defined scope, and wider while requirements are still moving. It is built from engineering hours per discipline, converted at our blended delivery rate, so the hours are directly comparable to a real proposal line by line — but a firm price needs a technical specification, which is the step after budgeting.