AI Solutions
- A framework for trustworthy AI in the insurance environment
In the insurance industry, the push for trustworthy AI is becoming increasingly significant, driven by regulatory bodies and consumer expectations for transparency and fairness in automated decisions. To align with EU guidelines and specific insurance industry regulations from EIOPA and BaFin, insurance companies are advised to adopt frameworks that ensure… Read more: A framework for trustworthy AI in the insurance environment - Democratizing AI with Dataiku, leveraging AutoML features to enable analysts to build and deploy models with no coding knowledge
Prologis has significantly enhanced its operational processes by integrating Dataiku, a platform that democratizes AI, enabling analysts without coding expertise to develop and deploy models. This transformation began with moving their data management to a cloud-based system using Snowflake, which increased analytics modernization. With Dataiku, Prologis has expanded its AI… Read more: Democratizing AI with Dataiku, leveraging AutoML features to enable analysts to build and deploy models with no coding knowledge - Automation Boosts Efficiency in Employee Onboarding
JIFFY.ai significantly enhanced the onboarding process for a global professional services firm by automating 80% of the activities, which streamlined the procedure for both HR teams and new hires. This automation reduced the onboarding time from three hours to just 17 minutes and allowed the HR team to shift their… Read more: Automation Boosts Efficiency in Employee Onboarding - Time series analysis for shipping outdoor equipment through data warehousing
Our client, a major manufacturer and distributor of outdoor equipment, required a centralized platform for all its data to enhance advanced analytics of customer and business data. Niologic implemented a data warehouse based on Google BigQuery and developed a time series analysis for shipping, along with a machine learning algorithm… Read more: Time series analysis for shipping outdoor equipment through data warehousing - Automating Information Extraction with Named Entity Recognition and LLMs
Our project focused on automating the information extraction process from various data sources such as textual documents and database tables, utilizing Named Entity Recognition (NER) and advanced Language Models (LLMs). The main goal was to create an automated solution that could efficiently extract relevant information using NER and enrich metadata… Read more: Automating Information Extraction with Named Entity Recognition and LLMs