GOStack Automates iGaming Production with Generative AI on AWS

Intro

A leading global provider of technology for the iGaming industry aimed to significantly increase its annual game production to meet growing international demand. While their core platform was scalable, the operational workflows required to launch new games, particularly trademark clearance and multilingual translation, were manual, slow and expensive. These processes created a significant bottleneck, limiting the company's ability to grow and respond to market opportunities.

The Challenge

The client's goal was to increase annual game production by up to 7x, but their existing operational workflows could not keep pace. Critical pre-launch processes, including legal trademark clearance and the translation of in-game content for multiple languages, were highly manual and dependent on external vendors. This created a linear scaling model where producing more games meant proportionally higher costs and longer delays.

The core challenge was to automate these knowledge-intensive, compliance-critical workflows at scale. The solution needed to be faster and more cost-effective than the existing manual processes without compromising the high standards of quality and auditability required in the heavily regulated iGaming industry.

Our Solution

GOStack designed and implemented a production-grade Generative AI solution on AWS that automated three core operational workflows, transforming the client's production pipeline.

AI-Powered Trademark Clearance

To accelerate the slow and manual process of trademark validation, GOStack built a hybrid system. It combines deterministic similarity scoring for objective risk detection with Generative AI-powered reasoning for contextual legal assessment. The system includes configurable risk thresholds and a human-in-the-loop validation step, ensuring full compliance while dramatically reducing the time required for pre-screening.

Domain-Specific Translation Engine

Replacing legacy translation memory systems and reducing reliance on external agencies, GOStack developed a scalable, AI-powered translation workflow. The engine enforces a domain-specific glossary to ensure consistent terminology across all languages and formats all content to meet strict regulatory requirements. This allows for near-instantaneous localization of game rules and in-game text.

Agentic RAG Support Assistant

To improve internal support efficiency, an AI assistant was built using an agentic Retrieval-Augmented Generation (RAG) model. The assistant retrieves information from relevant internal documentation before generating responses, allowing it to handle multi-step operational queries and produce grounded, traceable answers suitable for compliance-sensitive environments.

AWS-Powered Architecture

The entire solution is built on a secure and scalable serverless architecture using AWS-native services. Amazon Bedrock provides foundation model inference for reasoning, translation and RAG workflows. Amazon OpenSearch Service is used for hybrid semantic and metadata-based retrieval. AWS Lambda orchestrates the data ingestion and AI workflows, with Amazon S3 providing secure, version-controlled document storage. The architecture is deployed in a multi-AZ configuration for high availability and uses managed services to scale automatically with demand.

Results and Benefits

The implementation delivered measurable improvements across speed, cost efficiency and scalability, enabling the client to meet its ambitious production goals.

• Processing Time Reduced by >80%: Trademark pre-screening became 80-90% faster and game localization dropped from days to minutes.

• Operational Costs Reduced by ~50%: Dependency on external trademark and translation services was cut by over 50%, reducing overall workflow costs by 40-50%.

• Enabled 7x Production Scalability: The automated workflows enabled a 7x increase in game production capacity without a proportional increase in headcount.

• Internal Throughput Increased by 3-5x: The new system dramatically increased the processing throughput for all core production workflows.