AI ENGINEERING SERVICES
Turn your AI model into a product people can use
BiX turns research AI and computer vision models into secure, testable web and cloud products, from inference APIs and user workflows to deployment and handover.
FROM RESEARCH TO USE
A working model is only the beginning
Research code proves an idea. A product must accept real inputs, produce repeatable outputs, protect data, support users, survive deployment, and remain understandable after handover. BiX connects those engineering steps in one delivery team.
WHAT WE BUILD
The engineering between a model and a product
Model-to-service engineering
Refactor research code into controlled inference services with containers, APIs, input validation, configuration management, and reproducible execution.
Computer vision systems
Build practical workflows around classification, detection, segmentation, tracking, image enhancement, and quantitative image analysis.
Web product development
Create role-aware applications for data upload, analysis jobs, visual review, result comparison, reporting, and administration.
Cloud delivery
Package and deploy isolated services with release pipelines, access controls, logging, monitoring, backup planning, and operational handover.
Evaluation and traceability
Connect datasets, model versions, configurations, metrics, test cases, and releases so teams can reproduce results and investigate failures.
Evidence-ready documentation
Deliver requirements, architecture, test records, version manifests, deployment guides, and regulated-product extensions when the project needs them.
WHO WE WORK WITH
Teams with valuable AI that has not yet become usable software
- University and institutional research teams preparing a demonstrator or technology transfer
- Early-stage AI companies moving from a notebook to a customer-ready MVP
- Industrial teams applying computer vision to inspection, measurement, or workflow automation
- R&D consortia that need a stable, testable software deliverable
ENGAGEMENT FLOW
Decide what matters, then build the shortest credible path
- 01Discover
Review the use case, model, data rights, target users, performance evidence, and operating constraints.
- 02Blueprint
Freeze the MVP boundary, architecture, acceptance criteria, delivery plan, and ownership model.
- 03Build and verify
Implement the AI service and product workflow, then test critical functions and failure paths.
- 04Launch and transfer
Deploy the approved release with operating documents, source or artifact handover, and maintenance options.
CLEAR RESPONSIBILITIES
Good productization starts with a clean handoff
You bring the problem and evidence.
- Business or research objective
- Model, sample data, and lawful usage rights
- Domain criteria and a decision-maker
- Target users and acceptance priorities
We build the product around it.
- Product requirements and architecture
- Inference, web, data, and cloud software
- Verification and release evidence
- Deployment, handover, and maintenance plan
SCIENTIFIC LEADERSHIP
Computer vision depth, product engineering discipline
BiX is founded by Jang-Hwan Choi, Ph.D., an AI and computer vision researcher with experience spanning academic research, technology transfer, and applied software development. Our team combines that technical depth with the practical work required to deploy and maintain an AI product.
START WITH THE MODEL YOU HAVE
Let us map the shortest path from research code to a usable product
Share the current model, available data, intended users, and target timeline. We will identify the first buildable scope and the evidence needed to deliver it.