End-to-end Product Development of a Personal Communication and Behavior Coaching Solution

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Hike in user retention rates
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Fewer manual testing errors
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Playstore downloads

Our Client

  • GetMee is a brainy personal communication and behavior coaching app.
  • The mobile application leverages AI, machine learning, and deep learning algorithms to actively analyze user’s behavior and personality traits.
  • It offers learning plans and actionable feedback on communication and user behavior for continuous improvement and growth.

Problem Statement

Handling the end-to-end development of the AI-backed communication coaching app involved a set of challenges that required a thoughtful approach to multiple areas:
  • User-Friendly Design Challenges:

    Designing a user interface from scratch requires expert management strategies and out-of-the-box thinking. The client aimed to build a visually appealing and easy-to-use interface with wireframes, icons, and color codes that align with the app’s usage.

  • Inefficient Speech Processing:

    Gathering and processing speech data efficiently demands a robust system. Recognizing emotions directly from speech stood as a challenge. Hence, we aimed to develop an efficient speech-to-text and emotion-detection engine.

  • NLP Concerns:

    Creating Natural Language Processing (NLP) models for sentiment analysis and emotion extraction from text was another problem statement.

  • Integration Issues:

    The client faced difficulties in designing and integrating AI-ML models into both Android and IOS apps. Deploying these apps to Playstore and AppStore comes with its own set of challenges, ensuring regulatory compliance.

  • Testing Concerns:

    Clearly stating test cases and giving feedback to developers are crucial parts of making sure our app works well.

Our Solution

Our AI engineering team along with the client’s internal management planned a series of steps, seamlessly integrating data modeling and training processes.

GetMee App Development Pipeline





GetMee App Development Life Cycle

  • Our team of AI experts took charge of the entire product development journey. The step-by-step process involved a series of phases, some of which were executed sequentially or in parallel.


  • The onboarded experts navigated through each phase of the lifecycle, ensuring that every step contributed to the evolution of GetMee. From the inception of the model to the deployment of a feature-rich application on multiple platforms, expert supervision was ensured throughout the process.

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Business Impact

The successful partnership between our team and the client has demonstrated a significant impact on GetMee, leading to its successful market launch.
  • End-To-End App Development: From designing a user-friendly interface to addressing speech processing complexities and NLP concerns, our solutions have facilitated a seamless and efficient app development lifecycle.

  • Smooth Functionality Across Platforms: The careful selection and integration of AI-ML models for both Android and IOS applications have ensured a consistent and reliable UX. The deployed applications on Playstore and AppStore smashed integration challenges, providing users with a smooth app experience.

  • Ensured Reliability: The dedicated focus on clear test cases and effective feedback loops during the testing phase has resulted in the development of a reliable and trustworthy application. Users can trust in the accuracy of speech-to-text and emotion recognition, backed by a thoroughly tested system with minimum bugs and errors.

  • Successful Deployment: GetMee’s deployment across Android and IOS applications, along with integration through API to cloud servers, ensured a broad reach and accessibility. Users can seamlessly engage with the app on their preferred platforms, enhancing overall convenience and user adoption.


In conclusion, the strategic solutions implemented in response to various challenges have not only led to the successful development of GetMee but also positioned it as an intelligent, reliable, and user-centric communication and behavior coaching app. The app’s efficient functionality, lack of bugs, and diverse deployment options contribute to an overall positive user experience.

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