Moving Off a SaaS Wearable Platform: What the Migration Actually Looks Like

Why Teams Start Looking at Alternatives

SaaS wearable platforms like Terra, Vital, and Rook solve a real problem: they get you to production faster than building direct integrations with Apple Health, Garmin, Oura, and Whoop separately. The tradeoff shows up later.

Per-user fees that scale linearly against your growth become significant at 10,000 users and painful at 100,000. Data ownership questions surface when you realize your patient health data sits on a third-party vendor's infrastructure. Customization limits appear when you need a data field or normalization behavior the platform doesn't support. Vendor dependencies become concrete when a provider changes their OAuth flow and you're waiting on a platform update instead of fixing it yourself.

The teams who reach out about migration share one of three triggers: a pricing review that surfaced the SaaS cost at projected scale, a compliance conversation where legal flagged vendor data handling, or a product decision that required customization the platform couldn't accommodate.

None of these are catastrophic. But they share a common thread: something the team assumed would be handled by the platform turned out to require ownership.

What Open Wearables Actually Is

Open Wearables is a self-hosted, MIT-licensed platform for wearable data integration. You deploy it on your own infrastructure, connect the providers your product supports, and get a unified API that normalizes health data across devices.

The architecture covers provider connections (Apple Health, Garmin, Oura, Whoop, Polar, Suunto, Samsung Health Connect, Google Health Connect), OAuth flow management, data normalization into a unified schema, sync scheduling, and a developer dashboard for monitoring data pipelines.

Because it's self-hosted, your patient data never leaves your infrastructure. Because it's MIT-licensed, you own every line of code that touches your product. Because there are no per-user fees, your unit economics stay fixed as you scale.

We built Open Wearables at Momentum and use it in production across client products. The migration playbook described here is what we run for teams switching from SaaS platforms.

The Migration Process in Six Stages

Stage 1: Infrastructure Audit

Before writing any migration code, we map the existing setup. What providers are connected? What data types are flowing? What does the current normalized schema look like? Which features in the product depend on specific fields or processing behaviors?

This stage produces a data continuity map: every field in the existing pipeline, its source, its normalization logic, and whether Open Wearables covers it natively or requires custom handling.

The audit also surfaces the cost analysis. We pull the current SaaS invoice structure, calculate per-user costs at current and projected scale, and model the Open Wearables infrastructure cost. This becomes the business case document that justifies the migration timeline to stakeholders.

Completion criteria: data flow diagram complete, continuity map approved, cost model signed off.

Stage 2: Migration Plan

With the audit complete, we design the migration architecture. This includes the Open Wearables deployment configuration (AWS, GCP, or Azure; region selection for HIPAA or GDPR compliance), the provider connection sequence, and the SDK integration approach for the mobile app.

The plan also defines the parallel deployment window: how long both systems run simultaneously, what data validation criteria determine readiness to cut over, and what the rollback procedure is if the cutover needs to abort.

Historical data handling gets decided here. Some products need longitudinal continuity for features like HRV trend analysis or sleep baseline calculation. If yours does, the plan includes a backfill process. If your product only uses recent data, we skip the backfill and set a sync start date.

Completion criteria: deployment architecture documented, validation criteria defined, historical data decision finalized.

Stage 3: Parallel Deployment

Open Wearables goes live on your infrastructure alongside the existing platform. Both systems run simultaneously, collecting the same provider data independently.

This stage is about establishing confidence before any user-facing change. The mobile app stays connected to the original platform. Open Wearables runs in the background, processing the same provider data, generating the same outputs, sitting next to the production system without touching it.

Infrastructure gets hardened here: monitoring dashboards, sync health checks, error alerting, cost tracking, and performance baselines. By the end of this stage, Open Wearables has been running in your environment for long enough to produce a meaningful validation dataset.

Completion criteria: two weeks of parallel data collected, monitoring operational, no critical sync failures.

Stage 4: Data Validation

This is where the migration earns or loses confidence. We compare Open Wearables output against the existing platform across every field in the continuity map.

The validation process checks field coverage (are all expected data types present?), normalization equivalence (do sleep stage values map correctly between schemas?), sync reliability (what percentage of expected syncs completed?), and latency (how does processing time compare?).

Discrepancies get categorized: acceptable differences due to intentional normalization changes, gaps that require additional provider configuration, and errors that need code fixes before cutover.

Most migrations surface two or three provider-specific edge cases during validation. A Garmin activity type that maps differently. A Whoop HRV field that requires a unit conversion. These get resolved before cutover, not after.

Completion criteria: validation report signed off, all critical discrepancies resolved, acceptance criteria met.

Stage 5: SDK Swap

With validation complete, the mobile app switches to the Open Wearables SDK. This is the first user-facing change in the migration.

The SDK swap itself is a code change in the app: replacing the Terra (or Vital, or Rook) SDK calls with the Open Wearables equivalents. Provider authorization flows update to use Open Wearables OAuth endpoints. The data pipeline in the app backend switches to reading from Open Wearables.

For most apps, the SDK swap deploys as a standard app update. Users authorize their wearables through the same UI. The device connection process looks identical. The data that flows into the product comes from Open Wearables instead of the previous platform.

The old platform stays running during this stage. If the SDK swap surfaces unexpected issues, the app can fall back to the original pipeline without data loss.

Completion criteria: SDK swap deployed to production, app store update approved, error rate within acceptable bounds.

Stage 6: Cutover and Decommission

With the SDK swap validated in production, the migration completes. The old platform connection gets decommissioned: API keys revoked, webhooks removed, billing stopped.

For products with active user data on the original platform, this stage includes a final data export and archival if the continuity policy requires it. For products that ran parallel collection during migration, the historical data in Open Wearables is already complete.

Decommission timing varies. Some teams cut over immediately after SDK validation. Others run both systems for an additional two to four weeks as insurance before decommissioning. We recommend the latter for products where data continuity is clinically relevant.

Completion criteria: old platform decommissioned, infrastructure costs confirmed reduced, monitoring confirms Open Wearables handling full production load.

What Gets Complicated

Historical Data

If your product uses longitudinal health metrics, you cannot just start fresh on Open Wearables and pretend history doesn't exist. A sleep coaching feature that tracks 90-day trends needs 90 days of history in the new system to function correctly on day one after cutover.

Most SaaS platforms allow data export. The format varies. Terra exports are structured and reasonably clean. Some custom integration exports require transformation before import. The backfill process is scoped during the migration plan stage once we know what the data looks like.

Provider Coverage

Open Wearables natively supports the major providers. If your product connects devices not yet in the Open Wearables provider library, those require custom integration work. The audit surfaces this early. Custom provider integrations connect to the same unified API as native providers, so the product code doesn't change when a new device is added later.

Normalized Schema Differences

Terra, Vital, and Rook each have their own data schemas. Open Wearables has its own. Fields that appear equivalent sometimes normalize differently. Heart rate zones calculated by Garmin versus Open Wearables. Sleep stage boundaries that differ by one minute between systems. These differences are expected and manageable, but they need to be identified and handled explicitly, not discovered post-cutover by users reporting wrong numbers.

Cost Reference: SaaS vs. Self-Hosted at Scale

Cost comparison at different user volumes (approximate, varies by provider and plan):

Infrastructure cost for Open Wearables is cloud hosting only: compute, storage, and network egress. No per-user fees, no usage tiers, no provider surcharges.

The migration investment is a one-time cost. The infrastructure savings are ongoing. For most Series A+ products with 10,000 or more active users, the migration pays for itself in under six months.

What Momentum Handles vs. What You Handle

In a typical migration engagement:

Momentum handles: infrastructure audit, continuity mapping, Open Wearables deployment and configuration, SDK integration, parallel deployment setup, validation tooling, data validation execution, SDK swap in your app (or pairing with your mobile team), cutover coordination, and monitoring setup.

Your team handles: staging and production environment access, app store submission for the SDK update, final approval at each stage gate, and any product-side configuration that requires knowledge of your data models.

You do not need wearable data expertise on your team to run this migration. That's the point of the engagement. Your engineers need to understand your app architecture and be available for handoffs. We handle the wearable-specific complexity.

Starting Point

Migration is not the only option. If you're on a SaaS wearable platform and working with Momentum on health scores, AI features, or other product development, we build on top of what you have. The architecture we deliver is migration-ready by default: if the economics shift later and you want to move to self-hosted infrastructure, the transition is a scoped project. You're not forced to migrate to work with us.

When you do decide to migrate, the first conversation is the audit. We look at your current setup, data flows, provider coverage, and cost structure. From that, we produce the continuity map and migration plan.

The audit takes one week. It produces a document you own regardless of what comes next: a complete picture of your current wearable infrastructure, identified risks, and a migration scope. If you decide to run the migration internally or with another team, the audit is still useful.

If you're evaluating a move away from your current platform and want to understand the scope and cost, talk to the wearables team at Momentum.