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 (11) 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 |
|---|---|---|---|---|---|
| Bytecode Alliance Wasmtime (Component Model) Bytecode Alliance ( inference_runtime) |
teleon_team_simulation_provenance |
EMPIRICAL_LEADER PARETO | Exec: 99, Fit: 96, Wave: 96.7 | Cliff: 96%, WAR: +0.33 | Apache-2.0 |
| SLSA Build Provenance v1.1 OpenSSF ( protocol_spec) |
teleon_team_simulation_provenance |
EMPIRICAL_LEADER | Exec: 98, Fit: 96, Wave: 96.46 | Cliff: 96%, WAR: +0.29 | Apache-2.0 |
| SPIFFE / SPIRE Workload Identity CNCF ( protocol_spec) |
teleon_team_simulation_provenance |
EMPIRICAL_LEADER | Exec: 97, Fit: 95, Wave: 95.72 | Cliff: 95%, WAR: +0.29 | Apache-2.0 |
| Software Heritage SWHID v1 Software Heritage / ISO 18670 ( protocol_spec) |
teleon_team_simulation_provenance |
EMPIRICAL_LEADER PARETO | Exec: 99, Fit: 96, Wave: 95.6 | Cliff: 99%, WAR: +0.34 | GPL-3.0 |
| C2PA Content Credentials C2PA Coalition ( protocol_spec) |
teleon_team_simulation_provenance |
EMPIRICAL_LEADER | Exec: 95, Fit: 94, Wave: 94.28 | Cliff: 95%, WAR: +0.24 | Apache-2.0 |
| E2B Firecracker Code Sandboxes E2B ( team_simulation_substrate) |
teleon_team_simulation_provenance |
EMPIRICAL_LEADER | Exec: 95, Fit: 94, Wave: 94.24 | Cliff: 93%, WAR: +0.28 | Apache-2.0 |
| Daytona Isolated Dev Environments Daytona ( team_simulation_substrate) |
teleon_team_simulation_provenance |
EMPIRICAL_LEADER | Exec: 93, Fit: 93, Wave: 93.12 | Cliff: 93%, WAR: +0.25 | Apache-2.0 |
| Mesa Agent-Based Modeling Project Mesa ( team_simulation_substrate) |
teleon_team_simulation_provenance |
EMPIRICAL_LEADER | Exec: 94, Fit: 94, Wave: 92.72 | Cliff: 93%, WAR: +0.23 | Apache-2.0 |
| Google DeepMind Concordia Google DeepMind ( team_simulation_substrate) |
teleon_team_simulation_provenance |
EMPIRICAL_LEADER | Exec: 86, Fit: 89, Wave: 89.13 | Cliff: 82%, WAR: +0.22 | Apache-2.0 |
| DyLAN (Dynamic LLM-Agent Network) THUNLP ( team_simulation_substrate) |
teleon_team_simulation_provenance |
OPERATIONAL_WORKHORSE | Exec: 83, Fit: 80, Wave: 87.14 | Cliff: 82%, WAR: +0.2 | MIT |
| GPTSwarm GPTSwarm Authors ( team_simulation_substrate) |
teleon_team_simulation_provenance |
OPERATIONAL_WORKHORSE | Exec: 82, Fit: 79, Wave: 86.5 | Cliff: 78%, WAR: +0.19 | MIT |