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For teams with an existing .NET product

Integrate AI into existing .NET products. End-to-End.

I design and integrate production-ready AI features using LLMs, RAG, MCP, copilots and agentic workflows directly into existing .NET applications.

Discuss a Project (opens in a new tab) Explore Services
  • LLMs
  • RAG
  • MCP
  • Copilots
  • Agentic Workflows
  • .NET

From prototype to product

Building an AI prototype is easy. The real challenge starts afterwards.

A working chatbot, agent or RAG demo is only the beginning. Inside a real product, AI has to work with everything that is already there:

Prototype

  • Chat demo
  • Sample data
  • Runs locally

Inside a real product

  • Existing APIs
  • Databases
  • Authentication
  • Permissions
  • Business logic
  • User interface
  • Testing
  • Monitoring
  • Deployment

I combine AI engineering with .NET development and take the feature from the initial idea to production-ready integration.

Services

What I Build

Five areas of focus with one shared goal: the AI feature should end up as part of your product, not as an experiment running next to it.

  • 01

    RAG & Knowledge Assistants

    Make company knowledge from documents and existing data sources accessible through LLMs, including retrieval, context and sources.

    • Retrieval
    • Embeddings
    • Citations
  • 02

    AI Copilots

    Integrate AI assistants directly into existing .NET products instead of building isolated chatbots beside the actual application.

    • Product context
    • UI integration
    • Actions
  • 03

    Agentic Workflows

    Automate multi-step processes using AI agents, tools, APIs and existing business systems.

    • Agents
    • Tool calling
    • Human-in-the-loop
  • 04

    MCP & Tool Integration

    Connect LLMs and agents to internal tools, data and functionality through MCP and APIs.

    • MCP servers
    • APIs
    • Access control
  • 05

    End-to-End AI Integration

    From the AI layer to the actual .NET feature: backend, APIs, data, UI, testing and deployment.

    1. AI Layer
    2. Backend
    3. APIs
    4. Data
    5. UI
    6. Testing
    7. Deployment

AI + .NET

Two worlds. One production-ready feature.

AI Engineering

  • LLMs
  • RAG
  • MCP
  • Copilots
  • AI Agents
  • Agentic Workflows

.NET Engineering

  • C#
  • ASP.NET Core
  • Blazor
  • EF Core
  • REST APIs
  • SQL
  • Azure
Production-Ready AI Feature

I don't just build the AI layer. I can integrate the functionality into the existing .NET architecture, business logic, APIs, data and user interface.

Use Cases

Where AI Can Add Value to Existing .NET Products

Typical Use Cases

Illustrative scenarios, not client references.

  • Internal Knowledge Assistant

    Search internal documents and knowledge sources and answer questions with the relevant company context.

    1. Documents
    2. RAG
    3. LLM
    4. Answer + Sources

  • AI Customer Support

    Answer recurring product and support questions based on existing documentation and take load off the support team.

    1. Support request
    2. Documentation
    3. LLM
    4. Answer or handoff

  • In-Product Copilot

    Integrate a context-aware copilot directly into an existing .NET or Blazor application.

    1. Existing Application
    2. User Context
    3. Copilot
    4. Product Actions

  • Agentic Process Automation

    Automate multi-step workflows in which an agent orchestrates different tools, APIs and systems.

    1. Email
    2. Extract Information
    3. Check Internal System
    4. Create / Update Record
    5. Generate Response
    6. Human Approval

Process

From Idea to Production-Ready Feature

A clear path in four steps, with one point of contact from the first analysis to deployment.

  1. 01 – Use Case & Analysis

    We clarify the business problem and look at your existing .NET product, the available data and possible integration points.

    • Goal
    • Data
    • Interfaces

  2. 02 – Architecture & Design

    I define the AI architecture, model approach, RAG strategy, tools, MCP integration and clear system boundaries.

    • Models
    • RAG
    • MCP

  3. 03 – Implementation & Integration

    I implement the AI functionality and integrate it with the backend, APIs, database and UI of your .NET application.

    • C#
    • APIs
    • UI

  4. 04 – Production

    Testing, error handling, security considerations, observability and deployment, so the feature holds up in day-to-day use.

    • Testing
    • Observability
    • Deployment
Portrait of Haris Abbasi, founder of Abbasi AI Engineering

Haris Abbasi

AI + .NET Software Engineer Düsseldorf, Germany

About

Behind Abbasi AI Engineering

I'm Haris Abbasi, a software engineer with more than 6 years of experience in software development and a strong focus on C# and .NET.

Today, I specialize in connecting modern AI technologies with existing .NET products, from the initial use case to the integrated feature.

My full-stack .NET background allows me to look beyond the AI layer and work across backend, APIs, databases, UI, testing and deployment.

I hold a Master's degree in Computer Science and combine established software engineering with modern LLM, RAG and agent technologies.

Software Engineering
6+ Years
Computer Science
Master
Full-Stack
C# / .NET
Specialization
AI + .NET
Download CV PDF, German

Experience Across Software Engineering and Client Projects

A short overview. The details are in the CV.

Client projects as a freelance developer

  • TEXSIB GmbH

    2024 – 2025

    Full-stack web development

  • DSS GmbH

    2024 – 2025

    Full-stack web development

Professional positions

  • QUMsult GmbH

    2025 – 2026

    Full-Stack Software Developer (.NET / Blazor)

  • The MicroZone

    2021 – 2023

    Mobile QA Engineer with C# development

  • ICCC

    2018 – 2020

    Full Stack C# / .NET Developer

Technology

Tools I work with

The technology follows the use case, not the other way around.

AI

  • LLMs
  • RAG
  • MCP
  • AI Agents
  • Agentic Workflows

Backend

  • C#
  • .NET
  • ASP.NET Core
  • REST APIs
  • EF Core

Frontend

  • Blazor
  • HTML
  • CSS
  • JavaScript

Data

  • SQL
  • SQL Server
  • PostgreSQL

Cloud & Delivery

  • Azure
  • Git
  • CI/CD
  • DevOps

Contact

Already have a .NET product and want to integrate AI where it actually adds value?

Whether you already have a concrete use case or are exploring an idea, let's discuss how AI could fit into your existing product.

Book a 30-Min Call (opens in a new tab) Send an Email

Or reach out via WhatsApp (opens in a new tab) LinkedIn (opens in a new tab) hello@haris-abbasi.com