What challenges did Facgure face before AI implementation?

Enterprises wanted to deploy generative AI securely with their own data. Off-the-shelf AI tools did not fit branded deployments, privacy constraints, or local compliance needs. Facgure needed to balance performance and cost while scaling adoption across Southeast Asia.

What was the impact of the AI solution?

Launched Rover AI within six months. Reduced enterprise AI development and deployment time from 6 months to 1 week. Reported up to 70% reduction in operational costs for customers. Enabled secure branded deployments across Thailand and other Southeast Asian markets.

Source

ProductionEvidence: Medium65/100

Facgure builds Rover AI on Amazon Bedrock to cut secure enterprise genAI deployment from 6 months to 1 week

Use case typeGenerative AI transformationUpdated Jul 15, 2026

Facgure is a Thailand-based digital solutions provider and AI consultancy that built Rover AI, a generative AI platform for enterprises to securely deploy branded tools using their own data. The platform runs on AWS and combines Amazon Bedrock, Amazon EC2, AWS Lambda, Amazon ECS, Elastic Load Balancing, and Amazon QuickSight to support secure, scalable customer deployments and analytics.

Organization: Facgure
Industry: Professional Services
Location: Thailand
Published: July 2026

Reported outcomes

AI development and deployment time: 6 months to 1 week

Time & speed

Operational costs: Up to 70% lower

Strategic outcomes

New product / capabilityLaunched Rover AI within six monthsMarket & geographic expansionEnabled adoption across Thailand and Southeast AsiaCustomer experience & trustKept sensitive information out of external systems

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

AI development and deployment time: 6 months to 1 week decrease

AWS Solutions Case StudyJul 15, 2026Customer storyExplicit claimMedium evidence strength

reduces AI Adoption Time from 6 Months to 1 Week

Normalized claim

Operational costs: 70% decrease

AWS Solutions Case StudyJul 15, 2026Customer storyExplicit claimMedium evidence strength

up to a 70 percent reduction in operational costs

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Facgure
Provider: AWS
Maturity: Production
Linked source: AWS Solutions Case Study

Reported up to 70% reduction in operational costs for customers

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 2 of 2

1Generative AI transformation
2Workflow orchestration

Enterprises wanted to deploy generative AI securely with their own data.
Off-the-shelf AI tools did not fit branded deployments, privacy constraints, or local compliance needs.
Facgure needed to balance performance and cost while scaling adoption across Southeast Asia.

Built Rover AI on AWS to provide a secure, customizable generative AI platform.
Used Amazon Bedrock with Claude and Titan for core generative and retrieval capabilities.
Used Amazon EC2, AWS Lambda, Amazon ECS, and Elastic Load Balancing for scalable hybrid compute and service orchestration.
Used Amazon QuickSight for analytics dashboards.

Technologies

Amazon Bedrock Amazon EC2 AWS Lambda Amazon Elastic Container Service Elastic Load Balancing Amazon QuickSight Anthropic Claude 3 Amazon Titan

Launched Rover AI within six months.
Reduced enterprise AI development and deployment time from 6 months to 1 week.
Reported up to 70% reduction in operational costs for customers.
Enabled secure branded deployments across Thailand and other Southeast Asian markets.

Architecture

Facgure built Rover AI on AWS using Amazon Bedrock for foundation models, Amazon EC2 for backend workflow and AI agent components, AWS Lambda for event-driven functions, Amazon ECS for containerized integrations, Elastic Load Balancing for high availability, and Amazon QuickSight for analytics dashboards.

Sources & evidence1

Evidence: Medium65/100Evidence strength