At Inspired Entertainment, our core technology is processing the secure financial transactions that power the global online betting industry. Our centralized platform, the Remote Gaming Server (RGS), handles real-time wallet operations across multiple strictly regulated jurisdictions, supported by 11 data centers and over 200 deployments worldwide.

Growth in this space requires continuously integrating our platform with major betting operators like DraftKings, Entain, and the Flutter Group. The challenge is that every operator maintains entirely custom, proprietary APIs for their wallet transactions—requiring complex integrations just to handle standard operations like authenticating users, checking balances, and processing debits and credits.

• The bottleneck: Even if all major betting companies use JSON over HTTP, the data structures and protocols are highly customized and proprietary. Historically, to connect our server to a new operator, we had to manually interpret the API doc, map it to our RGS API, and build a custom “adapter”—a Java Spring Boot translation microservice. This required a standard scrum team of five and took 6 to 8 weeks, consuming roughly 40 dev days and 12 QA days per integration just on boilerplate code.

• The impact: This manual bottleneck artificially capped our business at completing about 12 integrations per year, which limited revenue growth. Furthermore, our highly skilled developers were stuck doing repetitive, “rinse and repeat” translation work instead of building core platform features.

Instead of continuing to manually map API documentation to Java code, we partnered with Google Cloud and the Barefoot Coders to build an AI-orchestrated integration pipeline. We utilized Gemini CLI to ingest operator wallet APIs and automate the creation of the Java Spring Boot integration modules. Now, a process that took weeks of manual coding is orchestrated by a single developer in days.

Our infrastructure relies heavily on Google Cloud to handle the strict regulatory and performance demands of real-money gaming.

Our new adapter workflow completely bypasses the manual mapping phase. The developer feeds the API documentation (PDFs/Markdown) and specific prompts directly into the Gemini CLI. The AI acts as the primary author, mapping the proprietary JSON payloads to Inspired’s normalized RGS endpoints.

Use hard numbers to prove the success of the project.

• Efficiency: Adapter build times plummeted from 6-8 weeks down to 1 week, with a clear roadmap to reduce this to 1 day once integration and regression testing are fully automated. Manual engineering time dropped from 40 Dev days to just 5 AI-orchestrated Dev days.

• Scalability: We reduced the team required per integration from five down to two (1 Dev, 1 QA). Instead of reducing headcount, we leveraged this efficiency to double our capacity, aiming to scale from 12 integrations a year to 24+, directly accelerating revenue growth.

• Application modernization: Beyond the adapters, a senior architect used Gemini CLI to tackle an abandoned legacy modernization project. In just one week as a background task, they successfully upgraded the core RGS from Java 8 to Java 25, transitioned from Tomcat 9 to 10, and moved from Spring 4 to Spring Boot 3.22, producing a clean, human-readable changelog in the process.

• Security: We leverage Gemini CLI to accelerate the process of updating dependencies, reducing effort when remediating Software Composition Analysis(SCA) findings decreasing our exposure to known vulnerabilities.

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