AI in your product

    Custom chatbots

    Support bots and internal assistants trained on your data, linked to your CRM, and deployable on cloud or your own servers when required.

    Beyond a FAQ page with a text box

    Chatbots fail when they cannot see live order status, invent return policies, or leave users stuck with no path to a person. We build assistants that read from your real systems: orders, tickets, bookings, inventory, not static FAQ pages alone.

    For a marketplace we tied conversations to specific products and orders so buyers and sellers were not repeating information already in the system. For an operations platform we built an internal assistant that answers stock and margin questions from live data, not outdated spreadsheets.

    When the bot should act, not just reply

    The assistant can look up a record, create a ticket, or send a notification when that is what the user needs. We set permissions so a customer-facing bot cannot trigger admin actions. When the bot is unsure, the full conversation goes to your team so customers do not repeat themselves.

    When data must stay on your servers

    Banks, government contractors, and healthcare clients sometimes cannot send customer data to third-party AI services. We can run open models on your infrastructure with the same document search and tool connections as cloud setups. We will tell you upfront where capability differs so you can decide.

    Tools we typically use

    We adapt to your stack when needed. These are common on projects like this.

    OpenAI / Claude / Gemini
    Ollama / LLaMA / Mistral
    React / Next.js
    Node.js / Python
    WebSockets
    CRM APIs (HubSpot, Salesforce, Zoho)

    Common questions

    How is this different from Intercom or Zendesk AI?
    Off-the-shelf tools work well for generic support. We build when you need deep integration with custom ERP/CRM logic, proprietary data sources, or deployment constraints those platforms do not support.
    Can the chatbot work in Hindi or other languages?
    Yes. Model choice affects quality per language. We test with your actual user queries in each language before launch.
    What does ongoing maintenance look like?
    You will want to review misfires monthly and update the knowledge base when products or policies change. We can hand that over to your team or stay on retainer for tuning.

    Start a project

    Have a Business Idea or Problem to Solve?

    Let's discuss what you're trying to build, automate, or improve and determine the right technical approach.

    NDA availableNo hard sellReply within 2 business hours

    How we work

    5 steps
    01

    Understand

    We start by understanding your business, users, workflows, and technical requirements.

    02

    Define

    We establish the scope, deliverables, architecture, milestones, and responsibilities before development begins.

    03

    Build

    Our team develops the product using a modern, maintainable technology stack.

    04

    Test & Launch

    We test the application, resolve issues, and prepare the product for production.

    05

    Handover

    You receive the source code, documentation, and agreed project deliverables.