Futureproofing Tines: Designing AI infrastructure for scale

Tines, a company known for its focus on security and automation, has adapted its platform to incorporate reasoning capabilities within its workflows by leveraging AI models, enabling tasks such as alert summarization and data enrichment. Initially, AI features were developed on AWS Bedrock to ensure data security and compliance, but as customer demand evolved, Tines introduced a flexible framework that supports multiple AI providers, including OpenAI, Mistral, and self-hosted options, without complicating the codebase. This was achieved through a generator-client split that standardizes interaction with various providers, allowing developers to focus on feature development rather than infrastructure specifics. Additionally, Tines implemented a method for enforcing structured data output across different AI models by incorporating JSON schema enforcement, ensuring consistent functionality even with diverse provider capabilities. The company’s iterative development cycle, driven by customer feedback, has allowed for rapid adaptation and the integration of new AI standards, ensuring that its platform remains versatile and capable of supporting both cloud-hosted and self-hosted AI deployments.