A curving sequence of softly lit glass capsules floating in the dark like the turns of a conversation

Expert AI Chatbot Development

Build Intelligent Conversational AI That DelightsYour Customers

Create smart chatbots powered by GPT, LLaMA, and other LLMs. From customer service to sales assistants, we build AI chatbots that understand context and deliver value.

Overview

What areAI Chatbots?

AI Chatbots are intelligent conversational interfaces that use natural language processing and machine learning to understand and respond to user queries. Our chatbot solutions provide 24/7 customer support, automate routine inquiries, qualify leads, and enhance user engagement. We build custom chatbots for websites, mobile apps, messaging platforms, and voice assistants that deliver personalized, human-like conversations at scale.

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Service Models

Engagementmodels

Choose the engagement model that best fits your project needs and budget

  • Part-Time

    20 hrs/week

    4 of 6 included

    • Flexible hours: included
    • Direct team integration: included
    • Multiple developers: not included
    • You manage daily tasks: included
    • Dedicated tech lead: not included
    • Cost-effective scaling: included
  • Full-Time

    40 hrs/week

    4 of 6 included

    • Flexible hours: included
    • Direct team integration: included
    • Multiple developers: not included
    • You manage daily tasks: included
    • Dedicated tech lead: not included
    • Cost-effective scaling: included
  • Most complete

    Extended Team

    Multiple roles

    6 of 6 included

    • Flexible hours: included
    • Direct team integration: included
    • Multiple developers: included
    • You manage daily tasks: included
    • Dedicated tech lead: included
    • Cost-effective scaling: included

Benefits

Why teams choose Jishu Labs forconversational AI

Experience the advantages of working with world-class software engineers

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  • Scoped in writing

    What we are building, what we are deliberately not building, and how we will know it works — agreed before the first commit rather than discovered in the third month.

  • Built to be handed over

    Code, documentation and the reasoning behind decisions are written for whoever inherits them. Handover is designed in from the start, not assembled at the end.

  • Production from day one

    Tests, CI and observability are part of the first sprint. Nothing ships that cannot be deployed, monitored and rolled back.

  • You own all of it

    Source, infrastructure and accounts are yours throughout. No proprietary layer, no dependency on us to keep it running.

  • Direct access

    You talk to the people writing the code. Questions get answered by whoever made the decision, not relayed through an account layer.

  • Scope that can change

    Priorities move. The engagement is structured so that is a conversation about sequence, not a change order.

Onboarding

How We Builda Chatbot

From the questions your customers actually ask to a released assistant you can measure.

  1. Question inventory

    We start from real conversations - support tickets, chat logs, search queries - to establish what people actually ask and how often.

  2. Scope and refusal design

    We agree what the assistant answers and, just as importantly, what it declines and hands to a person.

  3. Grounding your content

    We index your documentation and product data so answers come from your sources and can be traced back to them.

  4. Evaluation harness

    We build a graded set of real questions and run it on every change, so quality is measured rather than sensed.

  5. Channel integration

    We connect the assistant to the channels your customers use, and to the systems it needs to read or act on.

  6. Release and monitor

    We release behind the measures we agreed - containment, escalation, accuracy - and watch them from day one.

Tech Stack

The stack behind ourconversational AI

What we build conversational AI on, and why

  • Frontend Development

    • React & Next.js
    • Vue & Angular
    • TypeScript
    • Tailwind CSS
    • Redux & State Management
  • Backend Development

    • Node.js & Python
    • Java & .NET
    • Go & Rust
    • GraphQL & REST APIs
    • Microservices Architecture
  • Mobile Development

    • React Native
    • Flutter
    • iOS (Swift)
    • Android (Kotlin)
    • Cross-platform Solutions
  • Cloud & DevOps

    • AWS & Azure & GCP
    • Docker & Kubernetes
    • CI/CD Pipelines
    • Terraform & Infrastructure as Code
    • Monitoring & Logging
  • Data & AI

    • PostgreSQL & MongoDB
    • Machine Learning
    • Data Engineering
    • AI/LLM Integration
    • ETL Pipelines
  • Quality Assurance

    • Test Automation
    • Jest & Cypress
    • Performance Testing
    • Security Testing
    • QA Best Practices

Roles

Who Workson It

The people a project like this usually needs, and what each of them owns.

  • Conversation designer

    Designs the flows, tone and refusal behaviour, and decides where a person takes over.

  • AI engineer

    Builds the retrieval, prompting and evaluation harness behind the answers.

  • Backend engineer

    Builds the integrations that let the assistant read from and act on your systems.

  • QA engineer

    Maintains the graded question set and the automated checks that run on every change.

FAQ

Frequently AskedQuestions

Start a Project

Tell us what you are building. You get a senior team for custom software and AI — web, mobile, data, and cloud — from the first idea through to production.