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Semantic Kernel Agent

Microsoft

89·Strong

Overall Trust Score

Microsoft's enterprise-grade SDK for integrating LLMs with conventional programming languages. Provides agent capabilities through plugins, planners, and memory systems with first-class support for .NET, Python, and Java.

microsoft
azure
open-source
Version: 1.x
Last Evaluated: November 9, 2025
Official Website →

Trust Vector

Performance & Reliability

87
task completion accuracy
88
Methodology
Based on enterprise testing and model performance
Evidence
Semantic Kernel Documentation
Enterprise-grade reliability with extensive testing
Date: 2024-10-15
Confidence: highLast verified: 2025-11-09
tool use reliability
91
Methodology
Tool integration testing
Evidence
Plugins System
Robust plugin system with native and semantic functions
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
multi step planning
86
Methodology
Complex task testing
Evidence
Planner System
Multiple planner types for sequential and action planning
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
memory persistence
89
Methodology
Memory system evaluation
Evidence
Memory Stores
Multiple memory store backends (Azure, PostgreSQL, SQLite, Chroma)
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
error recovery
85
Methodology
Error handling testing
Evidence
Error Handling
Enterprise-grade error handling and retry policies
Date: 2024-09-15
Confidence: highLast verified: 2025-11-09
latency
Value: Low (1-5s typical)
Methodology
Performance monitoring
Evidence
Performance Optimization
Optimized for production with async operations
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09

Security

89
tool sandboxing
85
Methodology
Security architecture review
Evidence
Plugin Security
Plugin execution controls and security boundaries
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
access control
90
Methodology
Access control assessment
Evidence
Enterprise Integration
Integration with Azure AD and enterprise IAM systems
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
prompt injection defense
87
Methodology
Injection attack testing
Evidence
Prompt Engineering
Template system provides separation of instructions and data
Date: 2024-09-20
Confidence: mediumLast verified: 2025-11-09
data isolation
92
Methodology
Data architecture review
Evidence
Memory Isolation
Strong isolation via memory collections and namespaces
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
enterprise security
93
Methodology
Enterprise security assessment
Evidence
Azure Integration
First-class Azure security integration and compliance
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09

Privacy & Compliance

90
data retention
92
Methodology
Privacy architecture review
Evidence
Azure Compliance
Full control over data retention, Azure compliance options
Date: 2024-09-01
Confidence: highLast verified: 2025-11-09
gdpr compliance
93
Methodology
Compliance documentation review
Evidence
Microsoft Compliance
GDPR compliant when used with Azure OpenAI
Date: 2024-08-15
Confidence: highLast verified: 2025-11-09
third party data sharing
88
Methodology
Data flow analysis
Evidence
Azure OpenAI
Azure OpenAI provides data residency and no training on customer data
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
local deployment option
88
Methodology
Deployment options assessment
Evidence
Multi-Model Support
Supports local models via Ollama and ONNX runtime
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09

Trust & Transparency

90
documentation quality
95
Methodology
Documentation completeness review
Evidence
Microsoft Learn
Exceptional Microsoft Learn documentation with tutorials and samples
Date: 2024-10-20
Confidence: highLast verified: 2025-11-09
execution traceability
88
Methodology
Logging capabilities assessment
Evidence
Diagnostics
Built-in logging, telemetry, and Azure Monitor integration
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
decision explainability
85
Methodology
Explainability features assessment
Evidence
Planner Observability
Planner execution steps visible for debugging
Date: 2024-10-01
Confidence: mediumLast verified: 2025-11-09
open source code
93
Methodology
Open source assessment
Evidence
GitHub Repository
MIT licensed, 20k+ stars, Microsoft official project
Date: 2024-10-20
Confidence: highLast verified: 2025-11-09
enterprise support
92
Methodology
Support options assessment
Evidence
Microsoft Support
Official Microsoft support available for enterprise customers
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09

Operational Excellence

91
ease of integration
90
Methodology
Integration complexity assessment
Evidence
Multi-Language SDKs
First-class support for .NET, Python, and Java
Date: 2024-10-15
Confidence: highLast verified: 2025-11-09
scalability
93
Methodology
Scalability testing
Evidence
Azure Integration
Designed for enterprise scale with Azure services
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
cost predictability
88
Methodology
Pricing model analysis
Evidence
Open Source + Azure
Free SDK, predictable Azure OpenAI pricing
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
monitoring capabilities
94
Methodology
Monitoring features assessment
Evidence
Azure Monitor Integration
Excellent monitoring via Azure Monitor and Application Insights
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
production readiness
92
Methodology
Production readiness assessment
Evidence
Enterprise Adoption
Production-ready with major enterprise deployments
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09

✨ Strengths

  • •Enterprise-grade security and compliance features
  • •Excellent multi-language support (.NET, Python, Java)
  • •First-class Azure integration with managed services
  • •Outstanding documentation and Microsoft support
  • •Robust plugin and memory systems
  • •Production-ready with strong monitoring capabilities

⚠️ Limitations

  • •More complex than simpler agent frameworks
  • •Best performance requires Azure services (cost consideration)
  • •Less opinionated design requires more architectural decisions
  • •Smaller community compared to some other frameworks
  • •Some features still evolving (agents capability)
  • •Learning curve for developers new to semantic programming

📊 Metadata

license: MIT
supported models:
0: Azure OpenAI
1: OpenAI
2: Anthropic
3: Hugging Face
4: Local models
programming languages:
0: .NET (C#, F#)
1: Python
2: Java
deployment type: Self-hosted or Azure
tool support:
0: Plugins
1: Native functions
2: Semantic functions
github stars: 25800+
first release: 2023
ga version: 1.45 (.NET) and 1.27 (Python) - April 2025
transition: Microsoft Agent Framework is the successor (Semantic Kernel v2.0)

Use Case Ratings

customer support

90

Enterprise-grade reliability ideal for customer support

code generation

88

Strong plugin system works well for code generation tasks

research assistant

87

Memory and planning capabilities good for research tasks

data analysis

85

Good for data analysis with custom plugins

content creation

86

Semantic functions useful for content generation workflows

education

88

Memory system excellent for personalized tutoring

healthcare

92

Outstanding for healthcare with Azure compliance and security

financial analysis

94

Excellent for finance with enterprise security and compliance

legal compliance

89

Strong security and memory features good for legal work

creative writing

82

Works well but not specifically optimized for creative tasks