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Our client, a tech company based in Europe, specializes in digital communication solutions. Operating in a competitive global market, they strive to enhance digital interactions for individuals and businesses.
Detailed information about the client cannot be disclosed under the provisions of the NDA.
The client reached out with a sophisticated video conferencing platform already in place, rich with AI-powered functionalities aimed at transforming online communications. Their platform had features like real-time call transcription, sentiment analysis during dialogues, in-depth conversation analytics, and more.
These features enhance communication by offering deeper insights into conversations, gauging emotional tones, and providing concise meeting summaries. By analyzing real-time activity, users can identify and address any engagement gaps, ensuring smooth and productive interactions throughout.
Despite having a robust web version of their platform, the client faced hurdles in addressing the mobile-centric audience. The lack of a dedicated mobile video conferencing solution constrained their growth in this segment.
The primary issues highlighted by the client were:
Given these requirements, the client approached Innowise to craft a mobile application that mirrored the web platform’s strengths but with the added agility and features tailored for mobile users.
Our video conferencing app development company embarked on designing a customized mobile application tailored for AI-powered video conferencing. Over 4 months, we have developed the mobile version and integrated real-time transcription, gesture recognition, meeting summaries, scheduling customization, call synchronization, and mobile-optimized meeting notes accessibility.
Addressing the requirements posed by the client, our development team created a custom calendar widget instead of relying on off-the-shelf solutions. Several factors influenced this decision:
The application provides an interactive call experience tailored to the preferences and needs of each participant. Beyond the conventional offerings of video and sound, the app is notable for its AI-driven gesture and mood recognition. During calls, the system detects and interprets specific gestures and face expressions made by users. For instance, waving at the camera or giving a thumbs-up can be instantly recognized by the application, which then can translate these gestures into chat emojis, providing a visual cue to all participants about an individual’s reactions.
Our team implemented a preference-based adaptive video system. Depending on the user’s preferences and network conditions, the video quality dynamically adjusts. This ensures that, irrespective of bandwidth limitations, users have smooth call experience.
All incoming calls are recorded and stored on the system’s back-end. This data not only serves as a record but is also analyzed by AI to provide insights into the dynamics of the call. Whether it’s understanding the mood of the conversation through AI-analyzed transcriptions or recognizing the level of participant engagement, the system provides valuable feedback to users post-call.
With the importance of post-meeting analysis in mind, our solution incorporated call recording features. Not only can users record their sessions but they can also review them with varied playback speeds. AI further amplifies this experience by breaking down the call into distinct segments based on topics.
For those who prefer a concise overview, the AI system generates a summary, highlighting the pivotal points of discussion, decisions made, and action items agreed upon. This feature is particularly advantageous for those who might have missed the meeting or need a quick refresher.
The app provides trend analysis over time. By accumulating data from consecutive meetings, users can track recurring themes, frequently discussed topics, or persistent issues. This is instrumental for long-term projects where tracking progress and identifying consistent pain points guide strategic decisions.
Another feature is speaker identification. The AI system can discern different voices and tag them, simplifying the process of tracking speakers’ contributions during a meeting for better clarity. This is particularly useful in larger meetings with multiple participants.
Moreover, to assist in the preparation for future meetings, the app offers predictive analysis. By examining past meetings, it can suggest potential topics or questions that might arise, helping participants to be better prepared.
All these analytical tools, once confined to desktop platforms, have been presented in the mobile application, ensuring that users can tap into insights anytime, without compromising on intuitiveness.
Following the mobile video conferencing app launch, we expect strong adoption from the existing user base. The mobile-first approach will allow users to join meetings from anywhere, making participation more accessible than ever. Quick-invite links will streamline the process of adding new participants.
We anticipate a noticeable increase in new user registrations. This will reflect the app’s market appeal and solidify its position. In turn, we expect enhanced visibility and interest, leading to further investment opportunities.
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