Gorilla Logic

Gorilla Logic is a software engineering firm that provides digital product and platform engineering services. The company offers product development, platform consolidation, application modernization, and sustained engineering support. Services are described as being accelerated by AI-enabled workflows and modular AI agents. The organisation states it works with global brands, private equity teams, and high-growth companies, indicating operations at an international or global scale.

Services and Capabilities

• AI-enabled product engineering: development of software products with integrated AI components and delivery workflows.
• Platform engineering, DevOps and SRE: design and operation of cloud platforms, infrastructure automation, continuous integration/continuous delivery pipelines, and site reliability practices.
• Intelligent quality engineering: automated testing, quality assurance pipelines, and test automation integrated into the development lifecycle.
• Application modernization and platform consolidation: migration and refactoring of legacy systems, consolidation of platforms, and re-platforming to modern architectures.
• Data and machine learning solutions: implementation of machine learning models for use cases such as dynamic pricing and diagnostic analytics.
• Sustained engineering and operational support: ongoing engineering teams or pods that provide maintenance, incident response, and operational improvements.

Industry Focus

• Automotive: delivered AI-powered diagnostics and operational analytics for a global automotive company, including work that reduced mean time to recovery for incidents.
• Travel and hospitality: implemented machine learning solutions for dynamic pricing and revenue management for a travel company.
• Media and live events: provided scalable DevOps and platform support to ensure reliable streaming and operations for a large multi-week sporting event.

Technology and Delivery Approach

• Delivery workflows and modular agents: use of a portfolio of delivery-tested workflows and modular AI agents to standardise recurring activities and accelerate implementation.
• Embedded delivery teams: dedicated pods and embedded engineering teams that integrate with client organisations to provide hands-on engineering, tooling, and operational patterns.
• Automation and integration: emphasis on automation across software development lifecycles, including CI/CD, automated testing, and infrastructure as code for platform operations.
• Data and analytics: application of diagnostics, monitoring, and machine learning models to operational and business problems such as incident reduction and pricing optimisation.
• Platform and application modernization: iterative workstreams for refactoring, consolidating platforms, and sustaining engineering to support long-term operations.