# Systenics AI | Enterprise AI Solutions Experts

> Transform your business with cutting-edge AI solutions. Expert AI consulting and enterprise AI systems for intelligent automation and innovation..

Systenics Solutions AI is a bespoke agency focused on building innovative AI based solutions for our global clients powered by the Microsoft Azure AI and Open AI enterprise platforms.

Our expertise spans across AI strategy, business intelligence, AI integration, and custom AI solution development. We provide comprehensive AI consulting services to help enterprises leverage artificial intelligence for competitive advantage.

## Main Pages

- [Homepage](https://systenics.ai/): Main landing page with company overview, services, products, and capabilities
- [Blog](https://systenics.ai/blog): Collection of articles on AI, AI integration, enterprise solutions, and technology insights
- [Privacy Policy](https://systenics.ai/privacy-policy): Privacy policy and data handling information

## Blog Posts

- [Three Common Nginx Errors Solved: 413, 504, and Static File Handling (Docker Edition)](https://systenics.ai/blog/2025-11-06-three-common-nginx-errors-solved-413-504-and-static-file-handling-docker-edition): Fix Nginx errors like 413 Request Entity Too Large, 504 Gateway Timeout, and static file issues in Docker using simple nginx-proxy configuration tweaks.
- [PDF to Markdown Conversion Tools: Beyond the Hype - A Deep Dive into MarkItDown, Docling, and Mistral Document AI](https://systenics.ai/blog/2025-07-28-pdf-to-markdown-conversion-tools): Explore MarkItDown, Docling, and Mistral Document AI performance when converting complex PDFs into structured Markdown. This comparison highlights each tool’s strengths and limitations, from basic text scraping to AI-powered table recognition.
- [What Is Context Engineering? Boost Your AI with Better Context](https://systenics.ai/blog/2025-07-12-what-is-context-engineering-boost-your-ai-with-better-context): Learn what Context Engineering is, how it differs from Prompt Engineering, and see real-world examples like AI coding assistants. A simple guide for beginners to understand how AI truly becomes smart.
- [Why Your Semantic Kernel Agents Are Sharing Plugins and How to Fix It](https://systenics.ai/blog/2025-05-09-why-you-semantic-kernel-agents-sharing-plugins): Learn why using a single Semantic Kernel for multiple agents causes plugins to leak between them, uncover the root cause, and explore simple solutions to ensure each agent’s plugins remain properly isolated.
- [Integrating Dapr with DotNet Semantic Kernel Process Framework on Aspire](https://systenics.ai/blog/2025-04-26-integrating-dapr-with-dotnet-semantic-kernel-process-framework-on-aspire): Learn how to integrate Dapr sidecars into your .NET Aspire projects with Microsoft’s Semantic Kernel Process Framework to run AI-powered workflows at cloud scale. This step-by-step guide covers installation, configuration and sample code to get resilient, actor-based processes running anywhere.
- [Understanding Selection and Termination Strategy functions in .NET Semantic Kernel Agent Framework](https://systenics.ai/blog/2025-04-22-understanding-selection-and-termination-strategy-functions-in-dotnet-semantic-kernel-agent-framework): Explore how Selection and Termination Strategy Functions in the Semantic Kernel Agent Framework for .NET manage multi-agent conversations by choosing the next speaker and deciding when to end the chat.
- [Automate Workflows with Microsoft Semantic Kernel Process Framework in .NET](https://systenics.ai/blog/2025-04-18-automate-workflows-with-microsoft-semantic-kernel-process-framework): Build intelligent, event-driven workflows using Microsoft’s Semantic Kernel Process Framework to automate content creation, onboarding, and complex tasks with AI and custom logic.
- [Building Multi‑Agent AI Workflows with Semantic Kernel Agent Framework in .NET](https://systenics.ai/blog/2025-04-17-building-multiagent-ai-workflows-with-semantic-kernel-in-dotnet): Explore how multi-agent systems enable AI agents to collaborate seamlessly, enhancing efficiency and scalability. Learn to implement this approach using Microsoft's Semantic Kernel, orchestrating specialized agents to automate tasks like email drafting and approval.
- [Why Your AI Agent Isn't Calling Your Tools: Fixing Function Invocation Issues in Semantic Kernel](https://systenics.ai/blog/2025-04-11-fixing-function-invocation-issues-in-semantic-kernel): This blog covers why your Semantic Kernel AI agent may ignore plugins and how to fix it with a simple configuration change.
- [Building a Model Context Protocol Server with .NET and Semantic Kernel Integration](https://systenics.ai/blog/2025-04-10-building-a-model-context-protocol-server-with-net-and-semantic-kernel-integration): Learn how to implement a Model Context Protocol (MCP) server using C# and integrate it with Semantic Kernel to enhance AI assistants with external data and tools through a standardized protocol.
- [Building AI Agent using Semantic Kernel Agent Framework](https://systenics.ai/blog/2025-04-09-building-ai-agent-using-semantic-kernel-agent-framework): Explore the creation of intelligent AI agents with the Semantic Kernel Agent Framework
- [Model Context Protocol (MCP): The New Standard for AI Integration](https://systenics.ai/blog/2025-04-07-model-context-protocol-mcp-the-new-standard-for-ai-integration): MCP enables LLMs to access real-time data and execute dynamic actions with ease, reducing redundancy and maintenance overhead through standardized client-server interactions.
- [Boosting Developer Productivity with ChatGPT/Gemini/Claude Integration in Visual Studio](https://systenics.ai/blog/2025-04-01-boosting-developer-productivity-with-chatgpt-integration-in-visual-studio): Boost your coding efficiency with ChatGPT/Gemini/Claude integration in Visual Studio! Learn how the free ChatGPTExtension eliminates tab switching, automates code fixes, and streamlines your workflow right inside your IDE. Maximize productivity and simplify your development process today!
- [From Prompt Engineering to RAG: Optimizing Product Category Classification Systems - Part 2](https://systenics.ai/blog/2025-03-31-from-prompt-engineering-to-rag-optimizing-product-category-classification-systems-part-2): How we enhanced our product classification system by incorporating Retrieval-Augmented Generation (RAG) to provide dataset-specific context, resulting in improved performance and reliability.
- [From Prompt Engineering to RAG: Optimizing Product Category Classification Systems - Part 1](https://systenics.ai/blog/2025-03-10-from-prompt-engineering-to-rag-optimizing-product-category-classification-systems-part-1): How we enhanced our product classification system by incorporating Retrieval-Augmented Generation (RAG) to provide dataset-specific context, resulting in improved performance and reliability.
- [Understanding Response Format Limitations: Why Llama, Phi & Mistral Models Struggle in Azure AI Studio](https://systenics.ai/blog/2025-03-08-understanding-response-format-limitations): A comprehensive exploration of Response Format compatibility issues when working with Llama, Phi, and Mistral model families in Microsoft Azure AI Studio with Semantic Kernel, and how to effectively navigate these limitations.
- [Using OpenAI vs Azure OpenAI with Semantic Kernel. What's the difference?](https://systenics.ai/blog/2024-12-11-openai-vs-azure-openai-what-should-you-choose-with-semantic-kernel): Understanding the differences between OpenAI and Azure OpenAI and how to use them with Semantic Kernel
- [Building a Recommendation System Using Text Embeddings and python](https://systenics.ai/blog/2024-11-29-building-a-simple-recommendation-system-using-embeddings): Learn how to create a simple recommendation system for e-commerce using vector embeddings and Gradio.
- [Should you use GPT-4o-mini for multimodal tasks?](https://systenics.ai/blog/2024-11-19-should-you-use-gpt-4o-mini-for-multimodal-tasks): A deep dive into the real costs and limitations of gpt-4o-mini for image processing tasks.
- [Using the Waitfor and WaitforCompletion in .NET Aspire 9](https://systenics.ai/blog/2024-11-12-using-waitfor-and-waitforcompletion-in-dotnet-aspire-9): Learn how to use the new WaitFor and WaitForCompletion methods in .NET Aspire 9 to manage dependencies in your distributed applications.
- [Improved function calling with the Semantic Kernel](https://systenics.ai/blog/2024-11-05-improved-function-calling-with-semantic-kernel): A new way to call functions using the latest Semantic Kernel SDK
- [Using Structured Outputs with Semantic Kernel](https://systenics.ai/blog/2024-10-25-using-structured-outputs-with-semantic-kernel): A Simple Guide to Structured Outputs with Semantic Kernel. Converting text responses into typed data with JSON schema and C# model classes.
- [Setting up the Azure OpenAI API versions in Semantic Kernel](https://systenics.ai/blog/2024-10-21-setting-up-api-version-for-azure-openai-in-semantic-kernel): Managing Azure OpenAI API versions in Semantic Kernel, including both new and legacy approaches.
- [JSON Mode and Structured Outputs Mode using OpenAI Models](https://systenics.ai/blog/2024-10-13-json-mode-and-structured-outputs-mode-using-openai-models): Understanding JSON Mode and Structured Outputs in OpenAI Models
- [Implementing a Simple BPE Tokenizer in .NET](https://systenics.ai/blog/2024-10-07-implementing-a-simple-bpe-tokenizer-in-dotnet): Writing a basic Byte Pair Encoding (BPE) tokenizer using C# and .NET
- [Understanding Tokenization in Large Language Models](https://systenics.ai/blog/2024-09-30-understanding-tokenizers-in-large-language-models): An in-depth exploration of tokenization, tokens, and their crucial role in modern LLMs
- [Building a Simple text Classifier with Semantic Kernel](https://systenics.ai/blog/2024-07-26-building-a-simple-nlp-classifier-with-semantic-kernel): Using Semantic kernel to showcase how NLP tasks like text classification can be done with just a bit of prompt engineering in both python and .NET
- [Working with Semantic Kernel in Python](https://systenics.ai/blog/2024-07-15-working-with-semantic-kernel-in-python): An introduction to the Python version of the Semantic Kernel SDK
- [Building AI Apps with .Net Aspire and Semantic Kernel](https://systenics.ai/blog/2024-07-03-building-apps-with-aspire-and-semantic-kernel): Using aspire orchestration to develop AI-powered apps locally with .NET and Semantic Kernel
- [Getting Started with .NET Aspire](https://systenics.ai/blog/2024-06-20-getting-started-with-dotnet-aspire):  An introduction to .NET Aspire, its integrated services, and the Aspire dashboard.
- [Building a .NET Food Health Analyzer with Azure OpenAI and Semantic Kernel](https://systenics.ai/blog/2024-06-03-building-a-food-health-checker-with-openai-and-semantic-kernel): In-depth look at a .NET-based Food Health Analyzer app using Azure OpenAI and Semantic Kernel for intelligent ingredient and health analysis.
- [Packaged Food Health Checker with Semantic kernel](https://systenics.ai/blog/2024-05-27-packaged-powered-food-health-check-with-semantic-kernel): An overview for a simple AI powered app for checking packaged food healthiness
- [The new prompt filter in Semantic Kernel](https://systenics.ai/blog/2024-05-14-the-new-prompt-filter-in-semantic-kernel): Working with the new prompt filter IPromptRenderFilter in semantic kernel
- [Yaml prompts with semantic kernel](https://systenics.ai/blog/2024-05-02-yaml-prompts-with-semantic-kernel): Working with yaml prompt templates in semantic kernel
- [Manual function calling with Semantic Kernel and OpenAI](https://systenics.ai/blog/2024-03-27-manual-function-calling-with-semantic-kernel): Using the manual mode for function calling in Semantic Kernel
- [Function calling using Semantic Kernel](https://systenics.ai/blog/2024-03-18-function-calling-with-semantic-kernel): Using the gpt-4 function calling capabilities with semantic kernel
- [Introduction to OpenAI's function calling](https://systenics.ai/blog/2024-03-11-openai-function-calling): Introduction to function calling with OpenAI
- [Using Semantic Kernel with local embeddings](https://systenics.ai/blog/2024-03-04-using-local-embedding-semantic-kernel): Using a local embedding service with Semantic Kernel
- [Quick Setup for a local embedding Server using python](https://systenics.ai/blog/2024-02-26-local-embedding-server-using-python): Setting up a local embedding service using Python for development
- [Vision in Semantic Kernel](https://systenics.ai/blog/2024-02-19-vision-with-semantic-kernel): Using gpt-4 with vision in Semantic Kernel
- [Multiple streaming responses with Azure OpenAI and Semantic Kernel](https://systenics.ai/blog/2024-02-12-multiple-streaming-responses-with-azure-openai-and-semantic-kernel): Working with Azure multiple streaming responses in Semantic Kernel
- [Working with Azure OpenAI on Semantic Kernel](https://systenics.ai/blog/2024-02-05-azure-openai-with-semantic-kernel): Getting familiar with using OpenAI connector in Semantic Kernel
- [Getting Started with Semantic Kernel plugins](https://systenics.ai/blog/2024-01-29-plugins-with-semantic-kernel): Building GPT plugins in dotnet using Semantic kernel
- [Prompt engineering with Semantic Kernel](https://systenics.ai/blog/2024-01-22-prompt-engineering-with-semantic-kernel): Using prompts effectively with Semantic Kernel
- [What is Prompt Engineering](https://systenics.ai/blog/2024-01-15-what-is-prompt-engineering): Designing effective prompts for emerging AI-powered applications.
- [Understanding Embeddings](https://systenics.ai/blog/2023-01-08-understaning-embeddings): Introduction to embeddings and their uses
- [Setting up a Qdrant client for .NET](https://systenics.ai/blog/2024-01-01-setting-up-qdrant-with-qdrant-dotnet): Setting up a local qdrant server using the qdrant-dotnet library
- [Introduction to RAG systems](https://systenics.ai/blog/2023-12-25-intro-to-rag-systems): Brief introduction to RAG and their working
- [Getting Started with Semantic Kernel using .NET](https://systenics.ai/blog/2023-12-18-getting-started-with-semantic-kernel-dotnet): Getting familiar with Semantic Kernel and its functionality
- [What is Semantic Kernel](https://systenics.ai/blog/2023-12-11-what-is-semantic-kernel): Introduction to Semantic Kernel the lightweight AI apps orchestrator using dotnet
- [Introduction to Qdrant](https://systenics.ai/blog/2023-12-09-introduction-to-qdrant): Getting familiar with qdrant and its functionality.
- [Introduction to Vector Databases](https://systenics.ai/blog/2023-12-05-introduction-to-vector-database): Introduction to Vector Databases, the next-gen DBMS powering AI applications.
- [Understanding LLMs and their workings](https://systenics.ai/blog/2023-12-04-understanding-llm-and-their-workings): Understanding LLMs and their workings from the basics.

## Products

- [CSV Normalize](https://csvnormalize.com): AI-powered CSV Normalizer transforms unorganized CSV data into a clear, standardized format
- [Bank Statements CSV](https://bankstatementscsv.com): Convert PDF bank statements to CSV accurately in seconds with AI-powered extraction
- [Card Statement CSV](https://cardstatementcsv.com): Turn PDF credit card statements into neat CSV files with AI extraction

## Optional

- [Sitemap](https://systenics.ai/sitemap.xml): Complete sitemap of all pages
- [RSS Feed](https://systenics.ai/rss.xml): RSS feed for blog posts
- [AuctionWorx](https://www.systenics.com/auctionworx): Related service from Systenics
- [Careers](https://www.systenics.com/jobs/): Job opportunities at Systenics