Facgure Builds AI Integration Platform with Amazon Bedrock, Reduces AI Adoption Time from 6 Months to 1 Week

Facgure had already helped regional customers manage data at scale through business intelligence and data lakehouse solutions. But even with well-organized data, enterprises lacked a secure and scalable path to applying AI in production. They needed a way to generate insights and deliver AI-driven services without building or training models from scratch. They also had to protect sensitive information throughout the process.

Rather than layer new tools on top of fragmented systems, Facgure sought to offer a secure, unified platform that made AI adoption more practical and accessible. Drawing on its core expertise, the company built a generative AI platform on AWS that helps organizations deploy secure, branded tools using their own data. The result was its flagship product Rover AI, a scalable solution designed to accelerate adoption. The platform removes the need for complex infrastructure and keeps sensitive information out of external systems.

Facgure developed Rover AI on AWS to help organizations deploy secure, branded generative AI tools faster. The company launched the platform within six months, up to 50 percent faster than projected—accelerating time-to-market. As a result, Rover AI now supports adoption across Thailand and other Southeast Asian markets.

To support Rover AI's core generative capabilities, Facgure used Amazon Bedrock, a fully managed service that provides access to pretrained foundation models without the need to manage infrastructure. The company selected Claude, an Anthropic model known for strong language comprehension, to support Thai language interactions and culturally relevant responses. Facgure also integrated Titan, an AWS-built model for summarization, semantic search, and embedding generation. These models power secure, context-aware processing of proprietary data through Rover AI features such as Rover Compass (AI-Powered Enterprise Data Analytics), Rover Console (AI Integration Management Console), and IntelliQ (Web-based AI Chatbot).

To balance performance and cost, Facgure used Amazon Elastic Compute Cloud (Amazon EC2) to run backend components including the management console, AI Flow workflow engine, and AI Agents. AWS Lambda handles event-driven functions like Application Programming Interact (API) requests and chatbot interactions. Facgure uses this hybrid approach to scale resources on demand and optimize operational efficiency.

Facgure also implemented Amazon Elastic Container Service (Amazon ECS) to manage container-based services that support platform integrations. These include LINE Official Account and Facebook Messenger, two popular messaging apps that help customers interact with Rover AI through familiar digital channels. The company also deployed Elastic Load Balancing (ELB) to distribute traffic across services and maintain high availability. This architecture helped reduce AI deployment time for enterprise customers from 6 months to 1 week. ELB further supported secure deployment under each customer's brand, while keeping data private and operations consistent.

The company also turned to Amazon QuickSight, a cloud-native business intelligence service, to power Rover Insight, the dashboard for omni-channel analytics. With this, customers could visualize AI-driven analytics across multiple data sources and communication channels. This oversight helped organizations make faster, more informed decisions.

Facgure estimates that enterprise customers using the AWS-developed Rover AI platform achieved up to a 70 percent reduction in operational costs.

As adoption grows, Facgure plans to expand into new Southeast Asian markets, helping more organizations deliver generative AI tools under their own name. To support this growth, Facgure will continue to enhance capabilities in storage, analytics, workflow automation, and data lake infrastructure.

"With Rover AI, we set out to make generative AI secure, practical, and accessible. Many of our customers work with sensitive data or operate in complex environments. They need solutions they can trust, that run on their terms, and that deploy quickly. By building on AWS, we've created a platform that integrates AI into their workflows and data lakehouse while maintaining control, flexibility, and data privacy," said Theerayooth Kosin, CEO, Facgure.