The education app development company that builds standards-native, compliant learning platforms.

We scope which rules apply first, because they differ by segment. For consumer apps that knowingly serve children under 13, COPPA requires verifiable parental consent before collecting personal information, and the 2025 amendments add a separate consent step before sharing a child's data with third parties for targeted advertising, bring biometric and government identifiers into scope, and bar indefinite retention, with full compliance due by April 22, 2026. For school deployments, FERPA protects education records, and an EdTech vendor can touch personally identifiable information only under the school official exception, operating under the school's direct control with redisclosure limits and a data processing agreement. We build to whichever applies: consent and data-minimization flows, role-scoped access, retention windows enforced in code, and parent or eligible-student access and deletion.

It matters because it decides whether your content and your learning data stay yours. SCORM 1.2 and 2004 are the long-standing packaging standards that play in almost every LMS, but they track little beyond completion and scores. xAPI records richer experiences, including offline and outside the LMS, into a learning record store. cmi5 is the modern path that pairs SCORM-style packaging and launch with xAPI tracking, so you get portability and rich analytics together. LTI 1.3 is separate: it is how you launch external tools securely inside an LMS. We typically build new courseware to cmi5 with an xAPI LRS, keep SCORM import and export for legacy content, and use LTI 1.3 for tool integration, so nothing is trapped in one platform.

We choose against latency, scale, cost, and how much control you need, not a house favorite. Agora and Zoom Video SDK are mature, globally distributed, and quick to integrate, which suits large or geographically spread classes. 100ms and LiveKit give more control and can be more cost-effective at scale, with LiveKit being open source if you want to self-host. Raw WebRTC is the most flexible and the most engineering-intensive, worth it only for very specific needs. We model your concurrency, your regions, and your budget, then recommend the SDK that fits, and we design the classroom layer so the provider can be changed later without rewriting the app.

It depends on the segment, the feature set, and the compliance surface, so we give a defensible estimate after a discovery phase. As representative ranges, a focused MVP, meaning core LMS, content authoring or import, basic assessments, and a single billing model, is a smaller, faster build, while a full platform with live virtual classrooms, AI tutoring, proctoring, K-12 rostering, and an LRS is a larger one. Our median to a working build is 90 days. On cost, Resourcifi's global delivery model typically lands about 70% below comparable onshore US agency rates, and you get senior, in-house engineers named in writing before you sign, not a rotating freelancer bench. These ranges are representative; the real number comes out of scoping your features and segment.

Yes, and these are the details that decide whether a district can actually deploy. We build rostering and single sign-on through Clever, ClassLink, OneRoster, and Google for Education, so teachers and students are provisioned without manual account creation. We design and audit to WCAG 2.2 AA, which the 2024 ADA Title II rule now expects of public schools and universities, with keyboard, screen-reader, captioning, and color-contrast support built in. And we handle the FERPA school official exception and the COPPA rules above, with a data processing agreement and role-scoped access, so the platform passes the privacy and accessibility review a district runs before it signs.

Yes, and we are specific about how. Adaptive learning paths, AI tutoring copilots, content recommendations, and automated feedback are built on clean learning data, typically with retrieval-augmented generation over your own courseware so answers stay grounded in your material. Speech-to-text and text-to-speech support language learning and accessibility. Every AI feature passes an evaluation gate before it reaches a learner, so quality is measured rather than assumed, and children's data is handled under the COPPA rules above with no repurposing for advertising. We build the data layer, the LRS, and the eval gate first, so the tutoring trains on real signal and the quality is verified before launch.