gIQ leverages Large Language Models (LLMs) and biologically-inspired associative knowledge graphs for the fast and accurate identification of connections, correlations, and patterns in data, enabling better decision-making.
Harness automated workflows to process and enrich large unstructured datasets, extracting additional information and providing deeper understanding and context beyond raw data.
Execute LLM-driven workflows
Extract relevant information from unstructured data
Categorize, summarize and classify with built-in and custom prompts
Prepare enriched datasets for further analysis
Define and run LLM-driven workflows
Extract information from unstructured data
Categorize, summarize and classify with built-in and custom prompts
Prepare enriched datasets for further analysis
Leverage associative knowledge graphs to explore data relationships, identify complex patterns and execute advanced data analytics tasks.
Perform advanced analytics with graph AutoML tools
Explore hidden relationships reflected in the knowledge graph structure
Make predictions, detect anomalies, identify clusters
Find frequent patterns and association rules
At the core of gIQ stands a team of dedicated, driven and passionate professionals. We bring a wealth of experience as visionary leaders, AI enthusiasts and seasoned entrepreneurs who have already steered multiple companies to success.
gIQ emerged from our collective vision, inspired by the challenges we faced in diverse customer engagements.
Drawing upon a rich tapestry of experiences, deep insights, and groundbreaking scientific research we have crafted a solution that addresses the real-world complexities of data analytics.
gIQ embodies our commitment to transforming challenges into opportunities for innovation and progress.
Hetmana Żółkiewskiego 17A
31-539 Kraków, Poland
g.IQ sp. z o.o. ul. Hetmana Żółkiewskiego 17A, 31-539 Kraków, entered in the register of entrepreneurs kept by the District Court for Kraków Śródmieście in Kraków XI Commercial Division of the National Court Register under KRS (National Court Register) number: 0001100802, NIP (VAT identification number): 6751796936; REGON: 528213218.