Our cases
- Industry
- Areas of AI
- Capabilities
Customizable and safe document search and chat solution
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.
Read moreEmpowering Journalism with AI: Unlocking Podcast Insights
Modulai collaborated with Svenska Dagbladet to harness AI technology for transcribing and analyzing Swedish podcasts.
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.
Customer feedback clustering using state of the art NLP
Using recent advancements in Natural Language Processing (NLP), the Modulai team developed a model for clustering customer feedback into topics, making it possible to monitor sentiment across these and detect potential negative responses in real-time so that companies can take immediate action.
The client is a Stockholm-based startup founded in 2015 that helps businesses grow by the voice of their happy customers, providing a cloud-based solution for customer referrals, responses, recommendations, rewards, reviews, retargeting, and retention. Staying alert to customer opinion is key since reviews and testimonials are an important part of many companies marketing strategies.
Product recommendations for Ahlsell’s website and app
We helped out with kickstarting the in-house AI capabilities at Ahlsell by collaborating on the development of a recommender system for their website and smartphone app.
In close collaboration with Ahlsell’s data scientists, the team developed an end-to-end pipeline handling data ingestion, data processing, and model predictions. The recommendation system consists of a collaborative filtering model as well as a content-based model.
