AgentGenome for Semantic Kernel Developers
Profile Semantic Kernel Agents. Beyond Microsoft Lock-In.
Enterprise orchestration that works outside Azure
2,000+ developers • Portable across 12+ LLMs • No credit card required
Why Semantic Kernel Developers Need AgentGenome
Semantic Kernel brings enterprise-grade AI orchestration. AgentGenome ensures your agents aren't locked to Azure—profile once, deploy on any cloud or LLM.
Microsoft Ecosystem Lock-In
Semantic Kernel works best with Azure OpenAI. Every integration deepens Microsoft dependency. What's your exit strategy?
Enterprise Compliance Needs Documentation
SOC 2, HIPAA, and enterprise audits need behavioral documentation. Can you prove your agent behaves consistently?
Plugin Behaviors Are Opaque
Your Semantic Kernel plugins work, but how? Without profiling, plugin interactions are a black box.
Multi-Cloud Strategy Is Becoming Standard
Enterprises want cloud flexibility. Can your agents work on Azure, AWS, and GCP identically?
"Sound familiar?"
AgentGenome Solves Every Problem
Add 3 lines of code. Capture your agent's behavioral DNA. Deploy anywhere.
import semantic_kernel as sk
from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion
from agentgenome import profile
kernel = sk.Kernel()
kernel.add_service(OpenAIChatCompletion("gpt-4"))
@profile(genome_id="enterprise-agent")
async def process(goal: str):
result = await kernel.invoke_prompt(goal)
return str(result)
# Enterprise orchestration patterns capturedWhat You Get
- Behavioral profiling without code changes
- 35% average token savings
- Real-time drift detection
- Substrate-independent genome export
- Multi-provider deployment ready
Profile Once. Deploy Anywhere.
Port beyond Azure. Capture your Semantic Kernel agent's behaviors and deploy on AWS, GCP, or direct LLM APIs—same enterprise orchestration, no Microsoft lock-in.
Your Semantic Kernel Agents Deserve Freedom
You've invested months optimizing Semantic Kernel prompts. What happens when costs rise, performance drops, or a better model launches?
✗Without AgentGenome
- •Start over. Rebuild every prompt from scratch.
- •Lose months of behavioral optimization.
- •4-6 weeks of engineering per migration.
- •$47K+ average migration cost.
- •40%+ behavioral drift during migration.
With AgentGenome
- ✓Export your behavioral genome in one click.
- ✓Import to LangChain, AutoGen, LlamaIndex, or any provider.
- ✓Keep your optimizations. Zero rework.
- ✓95%+ behavioral consistency guaranteed.
- ✓Hours, not weeks. Included in Pro tier.
# Export Semantic Kernel genome
from agentgenome import genome
# Capture Azure-based behaviors
genome.export('enterprise-agent.genome')
# Deploy on AWS Bedrock
genome.import_to('enterprise-agent.genome', provider='bedrock')
# Or direct Anthropic API
genome.import_to('enterprise-agent.genome', provider='anthropic')Deploy your Semantic Kernel genome on any supported provider:
Profile once. Deploy anywhere. Never locked in.
Build Semantic Kernel applications Once.
Deploy on Any LLM.
Port beyond Azure. Capture your Semantic Kernel agent's behaviors and deploy on AWS, GCP, or direct LLM APIs—same enterprise orchestration, no Microsoft lock-in.
Your Agent Genome
Behavioral DNA captured in universal format
Profile Your Semantic Kernel applications
Add 3 lines of code. Capture behavioral DNA automatically.
import semantic_kernel as sk
from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion
from agentgenome import profile
kernel = sk.Kernel()
kernel.add_service(OpenAIChatCompletion("gpt-4"))
@profile(genome_id="enterprise-agent")
async def process(goal: str):
result = await kernel.invoke_prompt(goal)
return str(result)
# Enterprise orchestration patterns capturedYour applications become substrate-independent
Profile today, deploy on any LLM tomorrow. Your optimizations travel with you.
Real Results with AgentGenome
How SecureEnterprises Achieved Multi-Cloud AI Portability
The Challenge
SecureEnterprises built their threat detection agent on Semantic Kernel + Azure OpenAI. But government contracts required multi-cloud deployment options. Azure-only wasn't acceptable.
The Solution
AgentGenome profiled the agent's orchestration patterns, plugin interactions, and decision logic. These genomes were deployed on Azure, AWS Bedrock, and direct Anthropic API.
"Multi-cloud wasn't optional for our contracts. AgentGenome made it possible without rebuilding."
— Robert Kim, Chief Security Officer, SecureEnterprises
Without vs With AgentGenome
| Aspect | Without AgentGenome | With AgentGenome |
|---|---|---|
| Debugging Time | 4+ hours per incident | 52 minutes average (-78%) |
| Token Efficiency | Unknown waste | 35% average savings |
| Behavioral Visibility | Black box | Full trait analysis |
| Drift Detection | Discover in production | Catch before deployment |
| Agent Portability | 🔒 Locked to Semantic Kernel | 🔓 Deploy on any LLM |
| Migration Time | 4-6 weeks per provider | Hours with genome export |
| Migration Cost | $47K+ engineering | Included in Pro tier |
| Multi-Provider Strategy | Rebuild for each | One genome, all providers |
| Future-Proofing | Start over when models change | Take your genome with you |
| Vendor Negotiation | No leverage (locked in) | Full leverage (can leave) |
The Cost of Waiting
💸 Financial Lock-In
- Semantic Kernel pricing has increased multiple times since launch
- Without portable profiles, you pay whatever they charge
- Migration estimate without AgentGenome: $47K and 8 weeks
⚠️ Strategic Lock-In
- Better alternatives might exist—but can you actually switch?
- Your competitors are profiling for portability right now
- When you need to migrate, will you be ready?
🔒 The Vendor Lock-In Tax
- 4-6 weeks of engineering to migrate unprofiled agents
- 40%+ behavioral drift during manual migration
- Zero leverage in pricing negotiations
📉 Competitive Disadvantage
- Competitors with portable profiles ship 80% faster
- They negotiate contracts with leverage—you don't
- They test new models in hours; you take months
"Every day without profiling locks you deeper into Semantic Kernel."
When Semantic Kernel raises prices or a better model launches, will you be ready to leave?
What You'll Achieve with AgentGenome
Real metrics from Semantic Kernel users who profiled their agents
Before AgentGenome
- • Debugging: 4+ hours per incident
- • Migration: 4-6 weeks per provider
- • Token waste: Unknown
- • Drift detection: In production
- • Vendor leverage: None
After AgentGenome
- • Debugging: 52 minutes average
- • Migration: Hours with genome export
- • Token savings: 35% average
- • Drift detection: Before deployment
- • Vendor leverage: Full (can leave anytime)
Already Locked Into Semantic Kernel?
Here's how to escape with your behavioral DNA intact
Profile Your Current Agent
Add 3 lines of code to capture your Semantic Kernel agent's behavioral DNA. No changes to your existing logic.
Export Your Genome
One command exports your substrate-independent genome. It works on any LLM provider, not just Semantic Kernel.
Deploy Anywhere
Import your genome to Claude, Gemini, Llama, or any provider. 95%+ behavioral consistency, zero rework.
Zero-Downtime Migration Promise
AgentGenome's migration assistant guides you through the process. Profile your current agent while it's running, export the genome, and deploy to a new provider—all without touching your production system until you're ready.
Start Free. Unlock Portability with Pro.
Most Semantic Kernel developers choose Pro for multi-provider genome sync. Start free and upgrade when you need portability.
| Portability Features | Free | Pro | Enterprise |
|---|---|---|---|
| Genome Export | JSON only | JSON + YAML | All formats |
| Multi-Provider Sync | — | ✓ | ✓ + Custom |
| Migration Assistant | — | ✓ | ✓ + SLA |
| Custom Substrate Adapters | — | — | ✓ |
Frequently Asked Questions
Everything you need to know about AgentGenome for Semantic Kernel