Intelligent/Cognitive Systems consume data that are too complex for current databases to handle. GRAKN.AI is a hyper-relational database that allows you to perform knowledge engineering to manage this complexity. Effectively, Grakn provides a Knowledge Base (aka. Knowledge Graph) as the core foundation of intelligent systems.
Grakn provides an intelligent query language, Graql: Grakn’s reasoning (through OLTP) and analytics (through OLAP) query language, which is a much higher-level abstraction over traditional query languages. This allows intelligent systems to benefit from an intuitive language the provides an expressive schema for knowledge modelling, reasoning transactions for real-time inference, distributed algorithms for large-scale analytics, and optimisation of query execution. Grakn also provides the logical integrity of SQL, the scale of relationships of Graph databases, and the horizontal scalability of NoSQL.
In this community, we discuss the underlying technology and applications of the Grakn hyper-relational database. We will also discuss the techniques of a new software engineering principle, Knowledge-Driven Development, that Grakn now enables. The group is for engineers to demonstrate their solutions and share the lessons they learnt, as well as business leaders to learn applications of Grakn in their business.
## Introduction to Knowledge Graphs with Grakn and Graql
Grakn is a distributed knowledge graph: a logical database to organise large and complex networks of data as one body of knowledge. Grakn provides the knowledge engineering tools for developers to easily leverage the power of Knowledge Representation and Reasoning when building complex systems. Ultimately, Grakn serves as the knowledge-base foundation for cognitive and intelligent systems.
Graql is Grakn's query language. It provides an expressive knowledge schema language through an enhanced entity-relationship model, transactional queries that perform deductive reasoning in real-time, and analytical queries with native distributed Pregel and MapReduce algorithms. Graql provides a strong abstraction over low-level data constructs and complex relationships.
## Haikal Pribadi, Founder and CEO of Grakn Labs
Haikal is the Founder and CEO of Grakn Labs, a company working on build knowledge graphs for intelligent systems. His interest in the field began at the Monash Intelligent Systems Lab, where he worked on robotics systems that were adopted by NASA JPL and continued into his postgraduate studies at the University of Cambridge. He then became the youngest Algorithm Expert behind Quintiq’s Optimisation Technology that powers some of the world’s most challenging optimisation problems. He now works on Grakn, a distributed knowledge graph for intelligent systems. Grakn was recently awarded Product of the Year 2017 by the University of Cambridge Computer Lab.
## Grakn Labs is a team of people driven by a purpose: to solve the world's most complex problems, through knowledge engineering. We are the inventors of the Grakn knowledge-graph and the Graql query language. Our technology helps organisations in various industries, including Life Sciences, Defence & Security, Financial Services and Robotics, to build intelligent systems that we believe will change the world. From financial analytics to drug discovery, cyber threat detection to robotics disaster recovery, our technology empowers engineers around the world to tackle a higher order of complexity in knowledge, and solve the world's most complex problems.
## Join the global conference of technologies built using Grakn
Grakn Cosmos 2020: The Universe of Orderly Systems
6-7th of February 2020