Engineering Practical, Scalable AI Systems

We transform large models into deployable, high-performance AI systems that power next-generation SaaS applications.

What is AgriLinq?

AgriLinq is an applied AI engineering company focused on transforming large models into deployable and scalable systems.

We build the technical foundation that enables future AI products to be rapidly developed, validated, and brought to market.

Our Research Directions

AI Application Research

Exploring deep adaptation, fine-tuning, and control methods for large models in real-world scenarios to build reliable, high-precision AI capabilities.

AI SaaS Architecture

Designing modular, multi-tenant AI systems including API Gateways, model orchestration, and scalable inference pipelines for rapid multi-product incubation.

High-Concurrency Systems

Building high-performance inference architectures capable of handling massive requests, ensuring low latency and high reliability in high-traffic environments.

AI Product Engineering

Transforming AI technologies into reusable, mass-producible modules to shorten the distance from technical prototypes to commercial products.

Why Choose AgriLinq?

Engineering-First Deployment

Building deployable, maintainable AI systems with an engineering mindset, ensuring technology is not just a concept but truly supports products and services.

Scalable Architecture

Designed from the bottom up for high concurrency and horizontal scalability, capable of growing rapidly from prototype to enterprise-grade traffic.

Efficient & Cost-Effective AI Computing

Using model orchestration, caching, and inference optimization strategies to effectively reduce computing costs while maintaining performance.

Multi-Product Incubation

Creating reusable AI technology modules to accelerate the development and deployment of multiple products from prototype to PMF.

AgriLinq's Technology Development Strategy

Phase 1

Establish Core AI Engineering Foundation

Building AI inference architecture, multi-tenant systems, and deployable core engineering capabilities to form the technical foundation supporting all future products.

Focus: Inference / Multi-tenant / Deployability

Phase 2

Deepen AI Application & System Optimization

Expanding model fine-tuning, Prompt Engineering, cost optimization, and high-concurrency architecture research to enhance system reliability and scalability.

Focus: Fine-tuning / Optimization / High-Concurrency

Phase 3

Incubate Internal Product Prototypes

Using the technical platform as a base to explore AI applications in various fields, rapidly producing multiple product prototypes for initial market validation.

Focus: Prototyping / Exploration / Use-case Discovery

Phase 4

Market Validation & PMF Identification

Selecting directions with market potential, conducting user testing and iterations to identify products that meet market needs and have growth space.

Focus: PMF / User Feedback / Fast Iteration

Phase 5

Spin-off & Independent Growth

Products achieving PMF will be spun off into new independent companies for operation and fundraising, while the parent company continues to provide technical support and starts the next round of incubation.

Focus: Spin-off / Investment-ready / Multi-product