AI Development Services

AI development services are the engineering work needed to design, build, integrate and maintain AI-powered software. That includes choosing the right models, preparing data, building generative AI applications, AI agents, chatbots or machine learning models, connecting them to your existing systems, and monitoring them in production. For the broader picture, including strategy and business use cases, see our AI services and solutions.

An AI development company turns a business problem into working AI software. A good one will help you pick a use case worth solving, assess your data, build and test a proof of concept, develop the production application with its integrations and security, and support it after launch. It should also tell you when a simpler, non-AI solution is the better choice.

Most AI projects follow six stages: discovery and feasibility, data engineering, prototyping and model selection, full development with training or fine-tuning, integration and deployment, and ongoing MLOps. Each stage ends with something you can review, such as a scope document, test results or a working release, so decisions are based on evidence.

Cost depends on scope rather than on "AI" itself. The biggest drivers are: using an existing model through an API versus training a custom one, the state of your data, the number of integrations, security and compliance requirements, and expected usage, which drives ongoing model and hosting costs. A proof of concept is the lowest-cost way to start; we give a written estimate after a short discovery call.

A focused proof of concept often takes a few weeks. A production-ready first version typically takes a few months, and larger platforms with many integrations or custom model training take longer. Data readiness, integration complexity and approval cycles have the most influence on the timeline.

For most business applications, starting with an existing large language model plus retrieval-augmented generation (RAG) over your data is faster and cheaper. Fine-tuning or training a custom model makes sense when you need a specific style or format, very high accuracy on a narrow task, lower per-request cost at scale, or full control over where the model runs. We benchmark both options on your task before recommending one.

Yes. Much of our AI development work is adding AI features to existing web apps, mobile apps, CRMs, ERPs and internal tools through secure APIs, without rebuilding the product, including AI copilots embedded in your own software. See our dedicated AI integration services and legacy application modernisation.

We design for least-privilege data access, encrypt data in transit and at rest, use providers and settings that do not train on your data, defend against prompt injection, log AI actions and add human review where decisions are consequential. We align the engineering with frameworks such as the NIST AI RMF, ISO/IEC 42001, GDPR and the EU AI Act where they apply to your project.

You do. Source code, prompts, evaluation datasets, fine-tuned model weights, infrastructure configuration and documentation created for your project are handed over to you. Third-party models accessed through an API remain subject to their provider's terms.

CodeBase Coders provides end-to-end AI development services: AI consulting and proof of concept, generative AI and AI agent development, AI chatbots and voice agents, machine learning, AI integration and MLOps, delivered by one full-stack team. You can also hire a dedicated development team for ongoing AI work. Contact us to discuss your project.