Artificial intelligence development is building software that learns from data, understands language or images, and takes actions. It includes machine learning models, LLM apps, AI agents, chatbots and computer vision. Most business AI today is built on foundation models like GPT, Claude or Gemini, connected to your own data and tools.

Most projects cost between $8,000 and $80,000+. A proof of concept or AI MVP sits at the low end, chatbots and RAG systems in the middle, and custom platforms with trained models at the top. Data quality, integrations and compliance needs move the price most. We give a fixed-scope estimate within an hour of your call.

A focused AI feature or chatbot usually takes 4 to 8 weeks. AI agents, voice agents and multi-system integrations take 8 to 12 weeks, and custom ML platforms can run 3 to 6 months. We always ship a working proof of concept early so you see progress in the first few weeks.

AI agent development is building AI that plans and completes multi-step tasks on its own, like researching a lead, updating your CRM and sending a follow-up. Unlike a chatbot that only replies, an agent uses tools and APIs to take action. Good agents also have limits and human approval steps built in.

A chatbot answers questions in a conversation. An AI agent does work: it can call APIs, read and write data, and chain several steps together to finish a task. Many clients start with a chatbot and later add agent features once they trust the answers.

Generative AI for code development means using LLMs to write, review, test and explain code. Our engineers use AI coding tools to move faster, and we also build custom coding assistants trained on a company's own codebase and standards. Every AI-written line still goes through human review before it ships.

Not always. Chatbots, RAG systems and most AI agents work with the documents and data you already have, because they use pre-trained foundation models. Custom prediction models, like churn or demand forecasting, do need clean historical data. We check your data in week one and recommend the right approach.

Yes, and it's one of our most common projects. We connect GPT, Claude or Gemini to your current product through APIs and add features like smart search, chat assistants, auto-generated content or workflow automation. In most cases there's no need to rebuild anything.

Buy an off-the-shelf tool if you only need basic, generic features. Customize when the AI must know your data, tone and workflows, which is the right choice for most businesses. Build fully custom when you need strict data control, unusual logic or AI that is your core product.

Yes. We sign an NDA before the first call, use encrypted storage and role-based access, and keep your data out of public model training. For regulated industries we follow HIPAA, GDPR or SOC 2 practices. You keep full ownership of your code, data, prompts and models.

Look for a partner that shows live AI agents in production, names its tech stack, explains how it handles errors and permissions, and gives fixed-scope pricing. Check Clutch or Google reviews and ask to speak with a past client. AngleBrackets shares real case studies like ToryOS and LinkedIn AI on request.

We keep monitoring accuracy, cost and usage, retrain or update prompts when results drift, and add new features as your needs grow. AI isn't a one-time build, so most clients stay on a monthly support plan after launch.