5-Lens Empirical Quadrants, Pareto Frontier & 17-Facet AI Catalog
Replaces subjective analyst pay-to-play quadrants with reproducible telemetry across LLMs, CPU/Edge SLMs, 3D/Multimodal, Time-Series Foundation Models (Chronos-Bolt, TimesFM 2.0, Moirai-MoE, TimeGPT, PatchTST, Toto), Agent SDKs/Orchestrators, 7-Stage RAG, DSPy, Embeddings, MCP + A2A, Security, Tracing vs Evaluation, Memory Policies vs Vector/SQL Substrates, and Durable Execution.
All 17 Facets (18) agent_development_orchestration ai_security_and_guardrails automation_ipaas_dag_durable embeddings_and_rerankers evaluation_and_regression_testing llm_frontier_cloud llm_open_weights_cloud memory_behavior_policies multimodal_vision_audio_3d observability_tracing_monitoring programmatic_prompt_workflow_optimization protocols_mcp_and_a2a rag_context_pipeline slm_cpu_edge_quantized teleon_team_simulation_provenance timeseries_foundation_models vector_and_transactional_storage
5 Orthogonal Ranking Lenses
- Lens 1 (Empirical 2x2 Quadrant): X = Verified Execution Reliability vs Y = Architectural Composability and Governance Fit.
- Lens 2 (Constraint-Weighted Wave): Custom workload weights plus Tversky hard vetoes (
spdx_license, blast class, CPU-only). - Lens 3 (Exact Pareto Frontier): Non-dominated set across Quality, Latency, Cost, Cliff Retention, and Lock-in Freedom (orange nodes).
- Lens 4 (Jagged-Frontier Cliff Index): Perturbed neighbor retention ratio.
- Lens 5 (Team Marginal Value / WAR): Paired holdout lift net of coordination token tax.
| Component & Publisher | Primary Facet | Quadrant & Frontier | Lens Scores | Cliff & WAR | License |
|---|---|---|---|---|---|
| PydanticAI Pydantic ( agent_sdk) |
agent_development_orchestration |
EMPIRICAL_LEADER PARETO | Exec: 96, Fit: 93, Wave: 93.12 | Cliff: 89%, WAR: +0.28 | MIT |
| LangGraph LangChain ( orchestration_framework) |
agent_development_orchestration |
EMPIRICAL_LEADER PARETO | Exec: 91, Fit: 91, Wave: 91.66 | Cliff: 84%, WAR: +0.24 | MIT |
| Google Agent Development Kit (ADK) Google ( agent_sdk) |
agent_development_orchestration |
EMPIRICAL_LEADER | Exec: 92, Fit: 91, Wave: 91.62 | Cliff: 86%, WAR: +0.23 | Apache-2.0 |
| Semantic Kernel Microsoft ( agent_sdk) |
agent_development_orchestration |
EMPIRICAL_LEADER | Exec: 92, Fit: 92, Wave: 90.84 | Cliff: 87%, WAR: +0.19 | MIT |
| Microsoft Agent Framework Microsoft ( orchestration_framework) |
agent_development_orchestration |
EMPIRICAL_LEADER | Exec: 90, Fit: 90, Wave: 90.46 | Cliff: 84%, WAR: +0.2 | MIT |
| Mastra TypeScript Agent Framework Mastra ( orchestration_framework) |
agent_development_orchestration |
EMPIRICAL_LEADER | Exec: 91, Fit: 91, Wave: 90.42 | Cliff: 86%, WAR: +0.21 | Apache-2.0 |
| LlamaIndex Workflows LlamaIndex ( orchestration_framework) |
agent_development_orchestration |
EMPIRICAL_LEADER | Exec: 90, Fit: 90, Wave: 90.14 | Cliff: 84%, WAR: +0.21 | MIT |
| AWS Strands Agents AWS ( agent_sdk) |
agent_development_orchestration |
EMPIRICAL_LEADER | Exec: 91, Fit: 91, Wave: 90.1 | Cliff: 86%, WAR: +0.2 | Apache-2.0 |
| OpenAI Agents SDK OpenAI ( agent_sdk) |
agent_development_orchestration |
EMPIRICAL_LEADER | Exec: 92, Fit: 91, Wave: 89.98 | Cliff: 84%, WAR: +0.21 | MIT |
| Hugging Face smolagents Hugging Face ( agent_sdk) |
agent_development_orchestration |
EMPIRICAL_LEADER | Exec: 90, Fit: 90, Wave: 89.82 | Cliff: 84%, WAR: +0.22 | Apache-2.0 |
| Agno Agno ( agent_sdk) |
agent_development_orchestration |
EMPIRICAL_LEADER | Exec: 93, Fit: 84, Wave: 87.98 | Cliff: 86%, WAR: +0.21 | MPL-2.0 |
| LangChain Agents LangChain ( agent_sdk) |
agent_development_orchestration |
OPERATIONAL_WORKHORSE | Exec: 84, Fit: 78, Wave: 86.72 | Cliff: 73%, WAR: +0.14 | MIT |
| AWS Bedrock Agents AWS ( managed_agent_service) |
agent_development_orchestration |
EMPIRICAL_LEADER | Exec: 92, Fit: 92, Wave: 84.86 | Cliff: 87%, WAR: +0.18 | Proprietary |
| Azure AI Foundry Agent Service Microsoft Azure ( managed_agent_service) |
agent_development_orchestration |
EMPIRICAL_LEADER | Exec: 91, Fit: 91, Wave: 84.71 | Cliff: 86%, WAR: +0.18 | Proprietary |
| Teleon SDK v1.8.0 Dual-Resolution Muscle Memory & MCP Kit Teleon ( sdk_package) |
agent_development_orchestration |
OPERATIONAL_WORKHORSE | Exec: 84, Fit: 81, Wave: 82.08 | Cliff: 84%, WAR: +0.18 | Apache-2.0 |
| Microsoft AutoGen Microsoft ( orchestration_framework) |
agent_development_orchestration |
SCOPED_SPECIALIST | Exec: 79, Fit: 72, Wave: 80.96 | Cliff: 53%, WAR: +0.09 | MIT |
| CAMEL CAMEL-AI ( orchestration_framework) |
agent_development_orchestration |
SCOPED_SPECIALIST | Exec: 77, Fit: 72, Wave: 79.84 | Cliff: 53%, WAR: +0.1 | Apache-2.0 |
| CrewAI CrewAI ( orchestration_framework) |
agent_development_orchestration |
SCOPED_SPECIALIST | Exec: 74, Fit: 58, Wave: 77.54 | Cliff: 48%, WAR: +0.06 | MIT |