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Leapfrog AI: LLM powered Chat Agent for Supply Chain Design
A chat assistant that helps users interact with supply chain data using everyday language—no SQL or coding needed. It makes it easy to find answers, run scenarios, and export results, all through simple conversation.
Customizable and secure search and chat agent
Aiming for companies and use-cases that either can't risk compromize data security or need special adaptation, we've developed a modular platform to fill the gap between traditional SaaS solutions and custom development.
Based on the learnings from numerous projects over the past two years, we have developed a safe and isolated RAG solution for companies with needs beyond vanilla SaaS solutions.
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Highlight detection and automatic video editing for online game streamers
Modulai has built a object-detection based system for detecting highlights and memorable events in online gaming streams for automatic editing of dense highlight reels.
Modulai has built a object-detection based system for detecting highlights and memorable events in online gaming streams for automatic editing of dense highlight reels.
Read moreAI-generated imagery for Bonnier News
In collaboration with Bonnier News, we explored the use of generative AI for replacing stock photos in ad production.
Empowering Journalism with AI: Unlocking Podcast Insights
Modulai collaborated with Svenska Dagbladet to harness AI technology for transcribing and analyzing Swedish podcasts.
Chat-based data visualization solution for Mediatool
The solution provides a seamless experience in extracting and summarizing data through natural language queries in a chat interface that retrives needed information and visualizes it directly in the interface.
Mediatool initiated a project utilizing OpenAI’s chat models through few-shot learning to generate complex JSON structures for automatic data retrieval and visualization, based on input and feasibility study by Modulai. This allows customers to chat with an AI assistant in a user-friendly way to retrieve data for decision-making in seconds. Chat interface removes technological barriers for customers who can now use natural language to communicate with the platform.
AI powered shopping assistant for e-commerce
Based on discussions and feedback from multiple e-commerse platforms, we've developed an easily integratable shopping assistant that lets site visitors ask natural language questions about the product catalouge and get recent, relevant and actionable resposes in real-time.
In the highly competitive e-commerce industry, customer service plays a crucial role in sustaining and growing the business. Customers nowadays expect instantaneous, accurate, and personalized responses to their queries. Traditional customer service methods are no longer sufficient to meet the growing demands and expectations of the online shopping community. To bridge this gap, an AI-powered shopping assistant bot capable of understanding and navigating the vast product catalog and providing instant, relevant answers is a necessity.
Shot speed prediction using object tracking for Passion Football
The ICONS app by Passion Football lets football players of all levels develop their skills and challenge others. We developed a solution that uses the smartphone camera to track and accurately estimate a players shot speed.
With the app, users can access a variety of exercises that measure essential football skills. These exercises are designed to be both fun and interactive, while also providing analytical insights to the player and suggesting exercises that target and improve their weak areas.
On-device, real time car fuel lid detection
We developed a CPU-optimized object detection model for on-device detection of fuel lids on cars.
The model was integrated into the central control system of the fueling rig, taking the role of the main detection mechanism, firstly to make sure the car is in the right position, and secondly to guide the fueling arm to the fuel door lid in real-time.When optimizing the model for CPU inference, we explored TensorFlow Lite and OpenVINO. In the end, we used OpenVINO which is a framework for optimizing deep neural nets on Intel CPU’s.
Social feed and video recommender for Frever
Engineers at Frever and Modulai teamed up in close collaboration to create an end-to-end machine-learning-based feed recommender system. A multi-model system architecture was developed and populates the feeds of every user. Information about the content of the video as well as indicators of the users' preferences is taken into account to ensure the best possible experience and relevance.
Frever’s unique video-creation and social content sharing app enables their users’ creativity. Users create personalized avatars and express themselves through music videos, stories, and vlogs.
