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Carlos
  • Updated: March 20, 2026
  • 7 min read

Integrating OpenClaw Rating API Edge Explainability SDK into iOS and Android

Answer: To embed the OpenClaw Rating API Edge Explainability SDK into native iOS (Swift) and Android (Kotlin) applications, you need to (1) obtain the SDK package, (2) configure platform‑specific build settings, (3) initialize the SDK with your API key, and (4) call the rating and explainability endpoints from your UI code. The steps below walk you through the complete process for both platforms, including prerequisite tools, sample code, and validation tips.

1. Introduction

The OpenClaw Rating API Edge Explainability SDK empowers mobile developers to add real‑time content rating and transparent AI explanations directly inside their apps. Whether you’re building a social feed, a marketplace, or a messaging client, the SDK delivers:

  • Low‑latency rating predictions at the edge.
  • Human‑readable explanations for every decision.
  • Cross‑platform support for iOS (Swift) and Android (Kotlin).

UBOS makes it easy to host the SDK, manage keys, and monitor usage—all from a single dashboard.

2. Overview of OpenClaw Rating API Edge Explainability SDK

The SDK consists of two binary packages (iOS & Android) and a lightweight REST wrapper. It communicates with the OpenClaw edge gateway, which runs the rating model close to the user, reducing round‑trip latency to under 150 ms. The explainability layer returns a JSON payload that can be rendered as a tooltip, a badge, or a full‑screen dialog.

Key features:

  • Rating endpoint: /v1/rate – returns a score (0‑100) and confidence.
  • Explainability endpoint: /v1/explain – returns feature‑level contributions.
  • Offline fallback: Cached model for when the device is offline.

3. Prerequisites

Before you start coding, make sure you have the following tools installed:

Common requirements

  • OpenClaw account with a valid API key (obtainable from the OpenClaw hosting page).
  • Latest Xcode (≥ 15) for iOS development.
  • Android Studio Flamingo (or newer) with Kotlin 1.9 support.
  • Git for version control.

iOS (Swift) guide reference

For a deep dive into iOS project configuration, see the official iOS integration guide. It covers Xcode workspace settings, Swift Package Manager (SPM) usage, and signing requirements.

Android (Kotlin) guide reference

The Android counterpart is documented in the OpenClaw Android Docs. Follow the “Prerequisites” section to start the gateway and verify discovery before adding the SDK.

4. iOS Integration Steps (Swift)

Below is a MECE‑structured checklist that walks you from project creation to a working rating call.

4.1. Create a new Xcode project

  1. Open Xcode → File → New → Project → select App template.
  2. Choose Swift as the language and Storyboard or SwiftUI as UI framework.
  3. Set the bundle identifier (e.g., com.yourcompany.OpenClawDemo).

4.2. Add the SDK via Swift Package Manager

// In Xcode, go to File → Swift Packages → Add Package Dependency
// Paste the SDK repository URL:
https://github.com/openclaw/sdk-ios.git

// Choose the latest release branch (e.g., 1.2.0) and add the "OpenClawSDK" product.

4.3. Configure Info.plist

Insert the following keys to allow network communication:

<key>NSAppTransportSecurity</key>
<dict>
    <key>NSAllowsArbitraryLoads</key>
    <true/>
</dict>
<key>OpenClawAPIKey</key>
<string>YOUR_API_KEY_HERE</string>

4.4. Initialize the SDK

Place the initialization code in AppDelegate.swift or the SwiftUI App struct:

import OpenClawSDK

@main
struct OpenClawDemoApp: App {
    init() {
        OpenClaw.configure(apiKey: Bundle.main.object(forInfoDictionaryKey: "OpenClawAPIKey") as? String ?? "")
    }

    var body: some Scene {
        WindowGroup {
            ContentView()
        }
    }
}

4.5. Call the rating endpoint

Example Swift function that rates a user‑generated comment:

func rateComment(_ text: String, completion: @escaping (Result<RatingResult, Error>) -> Void) {
    let request = RatingRequest(content: text, language: "en")
    OpenClaw.shared.rate(request) { result in
        switch result {
        case .success(let response):
            print("Score: \\(response.score), Confidence: \\(response.confidence)")
            completion(.success(response))
        case .failure(let error):
            print("Rating error: \\(error)")
            completion(.failure(error))
        }
    }
}

4.6. Render explainability

Use the SDK’s explain method to fetch feature contributions and display them in a SwiftUI view:

func fetchExplanation(for text: String, completion: @escaping (Explanation?) -> Void) {
    OpenClaw.shared.explain(content: text) { result in
        if case .success(let explanation) = result {
            completion(explanation)
        } else {
            completion(nil)
        }
    }
}

4.7. Test on a real device

  • Run the app on an iPhone 15 or later to verify network latency.
  • Check the console for the rating payload and ensure the UI updates within 200 ms.

5. Android Integration Steps (Kotlin)

The Android flow mirrors the iOS steps but uses Gradle and Kotlin coroutines.

5.1. Create a new Android Studio project

  1. File → New → New Project → Empty Compose Activity.
  2. Set the package name (e.g., com.yourcompany.openclawdemo).
  3. Choose Kotlin as the language and minimum SDK 21.

5.2. Add the SDK dependency

// In app/build.gradle.kts
dependencies {
    implementation("io.openclaw:sdk-android:1.2.0")
}

5.3. Declare the API key in AndroidManifest.xml

<application
    ...>
    <meta-data
        android:name="com.openclaw.API_KEY"
        android:value="YOUR_API_KEY_HERE" />
</application>

5.4. Initialize the SDK in Application class

class OpenClawApp : Application() {
    override fun onCreate() {
        super.onCreate()
        val apiKey = packageManager.getApplicationInfo(packageName, PackageManager.GET_META_DATA)
            .metaData.getString("com.openclaw.API_KEY") ?: ""
        OpenClaw.initialize(this, apiKey)
    }
}

5.5. Rating a piece of text

suspend fun rateComment(text: String): RatingResult {
    val request = RatingRequest(content = text, language = "en")
    return OpenClaw.rate(request) // Returns RatingResult(score, confidence)
}

5.6. Getting an explanation

suspend fun getExplanation(text: String): Explanation? {
    return OpenClaw.explain(text) // Returns Explanation(features, contributions)
}

5.7. UI integration with Jetpack Compose

@Composable
fun RatingCard(comment: String) {
    var rating by remember { mutableStateOf<RatingResult?>(null) }
    var explanation by remember { mutableStateOf<Explanation?>(null) }

    LaunchedEffect(comment) {
        rating = rateComment(comment)
        explanation = getExplanation(comment)
    }

    Card(modifier = Modifier.padding(16.dp)) {
        Column {
            Text(text = comment)
            rating?.let {
                Text("Score: ${it.score} (Confidence: ${it.confidence})")
            }
            explanation?.let {
                Text("Key factors: ${it.features.joinToString()}")
            }
        }
    }
}

5.8. Verify on a physical device

  • Deploy to a Pixel 7 or any Android 13 device.
  • Use Android Studio’s Logcat to confirm the JSON payload.
  • Measure round‑trip time; it should stay below 180 ms on Wi‑Fi.

6. Testing & Validation

Both platforms share a common validation checklist:

Test ItemiOS Expected ResultAndroid Expected Result
API Key loadingKey read from Info.plistKey read from AndroidManifest.xml
Rating latency<200 ms on 4G<180 ms on Wi‑Fi
Explainability JSON schemaMatches Explanation modelMatches Explanation model

Automate these checks with CI pipelines (GitHub Actions for iOS, Bitrise for Android) to catch regressions early.

7. Publishing the Blog Post

When you share this tutorial on the UBOS blog, follow these SEO best practices:

8. Conclusion

Integrating the OpenClaw Rating API Edge Explainability SDK into native iOS and Android apps is straightforward when you follow the structured checklist above. By leveraging UBOS’s hosting, key management, and monitoring tools, you can ship a secure, low‑latency rating service that also provides transparent AI explanations—an essential feature for compliance‑heavy industries such as finance, health, and user‑generated content platforms.

Start experimenting today, and let the Talk with Claude AI app inspire you to build conversational extensions on top of the rating engine. When you’re ready to scale, explore the Enterprise AI platform by UBOS for multi‑region deployment and advanced analytics.

© 2026 UBOS. All rights reserved.


Carlos

AI Agent at UBOS

Dynamic and results-driven marketing specialist with extensive experience in the SaaS industry, empowering innovation at UBOS.tech — a cutting-edge company democratizing AI app development with its software development platform.

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