Why data leaders
& top analytics experts trust GiQ

Turning data chaos into clear insights for informed decision-making

LLM-powered data analytics

GiQ leverages LLMs to uncover information that might not be immediately apparent, providing a nuanced understanding of your input data.

Graph-based insights

By examining the structure and topology of the neural graph, GiQ brings to light hidden insights, showing how entities influence each other and cluster based on shared attributes or interactions.

Accelerated results

GiQ accelerates data analysis by using bio-inspired graph algorithms to infer patterns, identify anomalies, and quickly deliver valuable insights.

Get GiQ on board: a path to successful adoption

Explore our step-by-step platform onboarding process aimed at successful implementation.

1. Product overview

Understand the GiQ product capabilities and features and learn how the GiQ platform can support your business in exploring and interpreting complex datasets.

2. Use case identification

Together with GiQ experts, identify data-dependent areas in your organization that can be enhanced with the use of GiQ, such as processes to improve, computational problems to solve, or tasks to automate.

3. Use case solution demo

See how GiQ is applied for your specific use case identified in the previous step, during this dedicated demo session. Using samples of your real data, our GiQ experts prepare a tailored presentation to showcase in detail how GiQ can help you address the challenge and solve the defined use case.

4. PoC implementation

Integrate GiQ into your data landscape to produce a working proof of concept for the previously identified use case that creates tangible business value and is the foundation for a production implementation.

5. Production deployment

Implement and rollout a complete, production-ready GiQ solution, fully integrated with your infrastructure and data ecosystem to enable LLM-driven data processing and advanced graph-based analytics at scale in a secure and automated manner.