AI Services and Solutions

AI services and solutions cover everything needed to put artificial intelligence to work in a business: consulting to find the right use cases, development of custom AI models and applications, integration of AI into existing software, and the ongoing monitoring and maintenance that keeps AI accurate. Typical solutions include chatbots, AI agents, document processing, recommendation engines, predictive analytics and computer vision.

The cost of AI development depends mostly on scope and data. The main factors are:

• whether you use an existing model through an API or need a custom-trained model;
• how much data cleaning, labelling and integration work is required;
• the number of systems the AI must connect to;
• security, compliance and deployment requirements (cloud vs. private hosting);
• ongoing usage costs such as LLM tokens and hosting.

A focused proof of concept costs far less than a full production platform, which is why we usually recommend starting there. After a short discovery call we provide a written estimate for your specific project.

As a rough guide, a proof of concept often takes a few weeks, a production-ready first version a few months, and larger platforms with many integrations longer. The timeline depends on data readiness, the number of integrations, approval processes and how much custom model training is needed. We confirm a timeline after discovery.

Most businesses do not need to replace their systems to use AI. We connect AI to your CRM, ERP, helpdesk, website or custom software through secure APIs and middleware, so AI features appear inside the tools your team already uses. Learn more about our AI integration services.

Traditional machine learning predicts or classifies, for example scoring a transaction for fraud or forecasting demand. Generative AI creates new content such as text, summaries, answers, images or code, usually with large language models. Many real solutions combine both: an ML model decides, and a generative model explains or drafts the next step.

AI as a Service means using AI capabilities, such as language models, speech, vision or ML platforms, through cloud APIs instead of building everything from scratch. It lowers upfront cost and speeds up delivery. We often build on AIaaS platforms like OpenAI, Anthropic, Google Vertex AI, AWS Bedrock and Azure OpenAI, and add the custom logic, data connections and guardrails your use case needs.

It can be, when the system is designed for it. We limit which data the AI can access, use providers and settings that do not train on your data, offer private or regional deployments where required, and add access control, logging and defences against prompt injection. We also align the design with the data-protection regulations that apply to your business.

Not always. Generative AI solutions such as chatbots and knowledge assistants can work with your existing documents from day one. Custom predictive models do need enough historical data of reasonable quality. Our data analytics and AI readiness assessment tells you which approach your current data supports.

CodeBase Coders helps you go from idea to working AI: we identify high-value use cases, build proofs of concept, develop custom AI, generative AI, AI agents and chatbots, integrate them with your existing systems and support them after launch. For strategy and readiness, see our AI consulting services; for chatbots, our AI chatbot development services; for autonomous agents, our AI agent development; for the engineering side, our AI development services. Contact us to discuss your AI project, or explore more on the CodeBaseAI page.