Services · AI

    Enterprise AI development services, from pilot to production

    AMT (Advanced Millennium Technologies) builds AI systems that run on real data, for real users, at a cost the business accepts. We design and engineer AI agents, generative AI applications, RAG systems, chatbots, voice AI and MCP servers. We have built AI since 2013, starting with IBM Watson, and deliver under ISO 9001:2015 and ISO 27001:2022.

    Schedule Technical Discovery

    Your first conversation will be with a senior technical partner, not a salesperson.

    What enterprise AI development actually involves

    Most of the work in an AI project is not the model. It is getting the right data to the model, controlling what the system is allowed to do, proving its answers are right, and keeping cost and latency in check once real users arrive. That is what AMT builds. The model is one component. The system around it decides whether the project ships.

    Our AI development services

    Our AI development services
    ServiceBuild this whenPage
    AI agent developmentSoftware needs to plan and act across your tools, not just answerAI agent development
    Generative AI developmentYou need text, summaries or content generated inside a workflowGenerative AI development
    RAG developmentAnswers must come from your own documents and dataRAG development
    Conversational AI and chatbotsCustomers or staff need answers and transactions in chatConversational AI and chatbot development
    Voice AI developmentThe conversation happens on the phone or by voiceVoice AI development
    MCP server developmentAI models need structured, controlled access to your systemsMCP server development
    AI product engineeringAI is a feature of a product you sell to many customersAI product engineering

    Is your AI idea ready to build? Five questions

    Answer yes or no. Three or more yes answers means you are ready for a discovery sprint. Fewer means start by fixing the no answers.

    1. Is there a measurable outcome? A ticket deflection rate, a processing time, a cost per case. "Use AI" is not an outcome.
    2. Does the data exist and can we reach it? If the answers live in documents nobody can export, that is the first project.
    3. Do you know what the system must never do? Actions it cannot take, data it cannot show, users it cannot serve.
    4. Is there an owner on your side? Someone who can make decisions and give access within days.
    5. Do you know what a wrong answer costs? That decides how much testing, review and human approval the system needs.

    Proof: AI systems AMT has shipped

    Proof: AI systems AMT has shipped
    ProjectWhat it doesCase study
    Telecom chatbot, Middle EastEnglish and Arabic bot on WhatsApp and Messenger, resolving over 50% of chats, about 100,000 conversations a month, live since 2019Read
    Support chatbot productMoved from keyword rules to OpenAI intent detection, then RAG with LangChain and Chroma DBRead
    SaaS chatbot builderMCP server that builds chat flows from a prompt using OpenAI and Anthropic modelsRead
    Microfinance bank, CambodiaTransactional chatbot on the core banking system, in English and KhmerRead
    Home energy, UKAI model that turns a postcode into a retrofit plan, trained on 20 million propertiesRead

    How AMT delivers AI projects

    1. Discovery sprint, two to three weeks. Ends in a written scope, architecture note, main risks and an estimate range.
    2. Architecture agreed. Data access, permissions, model choice, evaluation and cost at expected volume, written down before build.
    3. Build in increments. Each increment is tested against real questions with known good answers.
    4. Production ready. Monitoring, rollback, access controls and runbooks in place before launch.
    5. Handover or run. Your team runs it, or AMT does under a support agreement.

    These are the five delivery gates described on How we work. Our engineers use AI coding tools under one rule: no blind AI-generated code.

    Models and tools we work with

    Models and tools we work with
    AreaWhat we use
    Language modelsOpenAI (including GPT-4o), Anthropic, Gemma 2, Llama 3.1, IBM Watson
    OrchestrationLangChain, MCP (Model Context Protocol)
    Vector databasesChroma DB
    Classic machine learningPython, Random Forest, multi-output classifiers
    LanguagesPython (FastAPI), Node.js, NestJS

    We pick the model per task. Open models such as Gemma 2 and Llama 3.1 are an option when cost or data location matters.

    What drives the cost of an AI project

    We quote after technical discovery. These are the things that move the number.

    What drives the cost of an AI project
    DriverLower effortHigher effort
    DataClean, exportable, one sourceScattered, unstructured, many owners
    ActionsAnswers onlyReads and writes to business systems
    Risk of a wrong answerLow, a person checksHigh, money, health or legal impact
    UsersInternal teamPublic customers at volume
    Languages and channelsOne of eachSeveral of each

    FAQ

    What do enterprise AI development services include?

    Discovery, architecture, data integration, model selection, building the application around the model, evaluation, security and permissions, deployment, and support. At AMT that covers AI agents, generative AI, RAG, chatbots, voice AI, MCP servers and AI features inside products.

    Is AMT an AI development company in India?

    Yes. AMT has 150+ engineers in Bengaluru and Kochi and works with clients in the United States, Europe, the Middle East and Asia. We have built AI systems since 2013, starting with IBM Watson.

    How much does AI development cost?

    It depends on the data, what the system is allowed to do, the cost of a wrong answer, and the number of users and channels. We quote after a technical discovery call, and most projects start with a two to three week discovery sprint.

    Which AI models do you use?

    Whichever fits the task. Our projects use OpenAI models including GPT-4o, Anthropic models, open models such as Gemma 2 and Llama 3.1, and IBM Watson.

    Our AI pilot works in a demo but not in production. Can you help?

    Yes. That is the most common situation we see. Start with AI pilot to production, see how forward deployed engineering closes the gap, or read why pilots stall in our insights.

    Do you follow the EU AI Act?

    We design systems so you can meet the rules that apply to your use case, and we cover which rules apply when in our AI and GenAI insights.

    Tell us what the AI should do, what data it needs, and what is stopping it today.

    Already have a pilot that stalled? →