ChatCompletionService

Overview

A reusable ChatCompletionService built on Microsoft Semantic Kernel — providing standardized AI completion, prompt management, multi-provider routing, and plugin orchestration for enterprise AI applications.

The Challenge

Teams integrating AI into multiple products faced inconsistent implementations — different prompt patterns, no standardized model routing, and duplicated AI integration code across projects.

Our Solution

We engineered a centralized ChatCompletionService using Semantic Kernel that abstracts AI provider complexity. It provides a unified interface for chat completions, system prompt management, plugin registration, and intelligent model routing.

Architecture

Application Layer → ChatCompletionService → Semantic Kernel Kernel → Plugin Registry → Model Router (OpenAI / Azure / Gemini) → Response Stream → Application Callback

Key Features

• Unified chat completion interface across AI providers
• System prompt engineering and management
• Semantic Kernel plugin registration and orchestration
• Multi-provider model routing with fallback
• Streaming and non-streaming response modes
• Token usage tracking and cost monitoring hooks
• Configurable temperature and model parameters

Business Impact

• Reduced AI integration time for new projects by 70%
• Standardized prompt engineering practices across teams
• Enabled rapid switching between AI providers without code changes
• Created reusable foundation for all Acubent AI products

Results

• Successfully deployed across ChatSphere and Butler Bot
• Consistent API surface regardless of underlying AI provider
• Plugin architecture enabling rapid feature extension
• Production-stable with comprehensive error handling

Future Scope

• Open-source release for community adoption
• NuGet package distribution
• Built-in RAG pipeline plugins
• Admin UI for prompt and model management