About Us
Building practical software for supply chain collaboration
Lineverge is a Singapore and Hong Kong based software company behind Automail. We work with business teams to build tailored solutions for collecting, consolidating, and analyzing supply chain data across complex partner networks.
Our focus is practical engineering, close collaboration, and software that fits real operational processes rather than forcing businesses into rigid systems.
Our Philosophy
Core Values
We aim to give our clients a leading edge by providing the finest IT solution to help them solve the most complex supply chain problems. Our goal is our clients' success.Craftsmanship
We are committed to continuous improvement. By staying at the forefront of emerging technologies, we ensure that we deliver high-quality, innovative solutions that empower our clients to solve the most complex challenges in their supply chain management.
Flexibility
We understand that each company has its unique challenges and business needs. We do not force a one-size-fit-all solution upon our clients but are rather flexible in our service to ensure that all needs and challenges are addressed with our solutions.
Trust & Teamwork
We build relationships based on openness and trust, and we embed those values into our development process. We work with our clients as a team and we ensure that we are completely transparent with our work.
Speed
We know that speed is crucial for companies to stay ahead of competition. We use Agile deployment approach to deliver solutions to our clients as quickly as possible. We then provide hypercare service to fine tune those solutions to fully address the business needs.
Our People
Meet the Team
Our Tech Stack
Engineering Built Around the Problem
We use different architectures and technologies where they make practical sense. Our focus is on maintainability, flexibility, performance, and the ability to adapt quickly to changing business requirements.Automail Architecture
Automail uses a deliberately monolithic application architecture, organized into modular components. This gives us a stable common foundation while allowing business logic, workflows, interfaces, and integrations to be extended quickly where a project requires something specific.
Serverless Autoform
Autoform is an AWS-hosted SaaS application with a static frontend, serverless backend, and document-oriented data storage. AWS Step Functions orchestrate multi-step workflows, allowing the service to scale independently while remaining lightweight for external supply chain partners.
Data Processing & ML
We maintain our own data-processing and machine-learning algorithms for recurring transformation, matching, classification, and loading tasks. They are designed around the supply chain datasets we work with and optimized for processing large volumes efficiently.
Document Intelligence
Our document-processing pipelines use multiple LLM stages to extract, interpret, normalize, and clean information before it enters Automail. The process can combine model reasoning with deterministic validation and document-specific business rules rather than relying on a single extraction prompt.
Contextual AI
Automail includes an integrated chat using large-context models such as GPT-5.6 Sol or Gemini 3.8 Flash. The integration is aware of the structure and capabilities of each Automail instance and can work directly with application data and tools without requiring a separate RAG infrastructure.
Continuous Refactoring
Every major Automail version includes architectural cleanup and refactoring alongside new functionality. We continuously apply established software design patterns where they improve separation of concerns, reuse, testing, and long-term maintainability.
Supply Chain Document Processing
Document-specific processing is already used across a broad range of common supply chain records. Each document type can have its own extraction logic, validation rules, and downstream workflow.
Engineer-Owned Codebase
Our application architecture and production code are designed, written, reviewed, and maintained by our engineering team. We use AI development tools selectively for bounded tasks where they improve efficiency, such as small extensions, repetitive transformations, or test support. They supplement the engineering process rather than replacing ownership of the codebase or our security and review practices.
Designed to Evolve
New capabilities are introduced without treating existing deployments as disposable. Architecture, migrations, and backward compatibility are considered as the platform evolves.