AI software development is the process of designing and building applications powered by artificial intelligence — from generative AI and chatbots to machine learning and automation. CIT Software builds production-ready AI solutions as a Vietnam-based offshore partner, and hands over the full source code so the system is entirely yours.
What we build with AI
We help companies move AI from experiment to production. That includes generative-AI features inside your product, AI agents and assistants that handle real tasks, retrieval-augmented generation (RAG) chatbots that answer from your own documents, machine-learning models for prediction and classification, computer vision, document processing, and automation that removes repetitive manual work. The aim is not AI for its own sake, but AI that solves a specific business problem and pays for itself.
Our AI development services
CIT covers the full path from idea to a deployed, maintainable AI system:
- Generative AI & LLM apps — assistants, content and workflow tools built on models like GPT, Claude and open-source LLMs.
- RAG chatbots & knowledge assistants — chatbots that answer accurately from your own data and documents.
- AI agents & automation — systems that take actions across your tools, not just chat.
- Machine learning & predictive models — forecasting, recommendations, scoring and classification.
- Computer vision & document AI — image recognition, OCR and automated document handling.
- AI integration — adding AI features into your existing app via our custom software development team.
Start with an AI proof of concept
AI projects carry more uncertainty than standard software, so the smartest first step is usually a proof of concept: a small, focused build that tests feasibility, accuracy and value on your real data before committing to a full rollout. It keeps risk and budget under control and gives you evidence — not promises — to decide what to scale. From a successful PoC we move to a production system with the reliability, monitoring and guardrails a live product needs.
How we build AI solutions
Our process is transparent and evidence-led. We start with discovery to define the use case, data and success metrics; run a proof of concept to validate feasibility; then engineer the production system — data pipelines, model integration, prompts or fine-tuning, and the surrounding application; test for accuracy, safety and performance; and finally deploy, monitor and hand over the source code. Because AI models and data change over time, we can also support ongoing evaluation and improvement after launch.
Responsible, practical AI
Useful AI has to be trustworthy. We build with attention to data privacy, accuracy and clear boundaries on what the system will and won’t do, so outputs stay reliable and on-brand. Rather than chasing hype, we focus on measurable outcomes — hours saved, faster response times, higher conversion — and design each system so your team can understand, monitor and control it. You keep ownership of the code, the prompts and the data throughout.
Why build AI with an offshore team in Vietnam?
Building AI with a Vietnam-based team gives companies in the US, Singapore and internationally access to strong AI and data engineering at a fraction of local cost, with English-speaking project management and full ownership of the resulting system. It is a growing reason companies choose to outsource software development to Vietnam — the same competitive economics that apply to web and mobile now apply to AI, without giving up control of your models or data.
AI use cases by industry
The best AI projects start from a concrete problem, and those problems look different in each sector. In fintech, teams use AI for fraud detection, document verification and customer support automation. In healthcare, it powers clinical documentation, triage assistants and medical-image analysis. Retailers use it for recommendations, demand forecasting and support chatbots; logistics companies for route optimisation and delivery prediction; and professional-services firms for knowledge assistants that answer from internal documents. We start from the outcome you want — hours saved, faster response, higher conversion — and choose the AI approach that delivers it, rather than fitting a trendy technology to an undefined goal.
How we measure AI value
AI only earns its place when it moves a number that matters. Before building, we agree on the metric — support tickets deflected, processing time cut, accuracy achieved, revenue influenced — and design the system to be measured against it. During the proof of concept we test that metric on your real data, so the decision to scale rests on evidence, not enthusiasm. After launch we keep evaluating outputs, because models and data drift over time; ongoing measurement is how an AI feature stays reliable and keeps paying back its cost.
The AI technologies we work with
We build on leading foundation models such as GPT and Claude, and on open-source LLMs when data privacy or cost calls for a self-hosted approach. For retrieval and knowledge assistants we use vector databases and RAG pipelines; for predictive work we use established machine-learning and data-engineering tools; and we wrap it all in a robust application with the monitoring and guardrails production requires. Because you receive the source code, prompts and configuration, you are never locked to a single model or vendor — the system can evolve as the AI landscape does.
Frequently asked questions
How much does AI development cost?
It depends on the use case, data readiness and whether you need a proof of concept, a production system, or both. We usually start with a scoped PoC to prove value, then quote the production build per project.
Do we own the AI system and source code?
Yes. CIT builds to your specification and hands over the complete source code, prompts and configuration on delivery, so you fully own the system, the data and the roadmap.
Can you add AI to our existing product?
Yes. We frequently integrate AI features — assistants, RAG chatbots, automation — into existing web and mobile apps, connecting to your current systems and data.
How do you handle data privacy and accuracy?
We follow secure data-handling practices, keep your data under your control, and design each system with guardrails and evaluation so outputs stay accurate and safe for production use.
Build vs buy: where custom AI wins
Not every AI need requires a custom build — sometimes an existing tool is enough. Custom AI earns its cost when the value lives in your own data and workflow: a knowledge assistant trained on your documents, automation wired into your specific processes, or a model that reflects your business rules and stays under your control. Off-the-shelf AI products are quick to adopt but generic, priced per seat, and limited by what the vendor allows. When AI is central to your product or a genuine efficiency lever, a custom system you own — code, prompts and data included — protects both your advantage and your independence. In discovery we are honest about which path fits, so you invest where it actually pays back.
Build your AI solution with CIT
Tell us the problem you want AI to solve and we will propose an approach, a proof of concept and a quote — production AI built by a Vietnam offshore team, with full source-code handover. Contact CIT Software to get started
