Semantic KNN routing, latency percentiles, token savings, embedding coverage.
Every number sourced from the live /api/routing/stats endpoint at page load.
Why O(log N) routing matters when you have 200 agents and cost scales with every evaluation token.
text-embedding-3-large (1024-d, L2-normalized). A cosine KNN search over the agent manifest index retrieves top-20 candidates (0.5 soft threshold). A cross-encoder (ms-marco-MiniLM-L-6-v2, 22M params) re-ranks all 20 pairs simultaneously. Top-5 by CE score above the 0.70 hard threshold enter the auction. IVFFlat index with 20 partitions.
Sourced from /api/routing/stats and /api/agents/manifest-coverage on page load.
capability_embedding populated. 100% = all agents are routable via KNN. Galaxy Phase complete.app.current_tenant session variable. RBAC: owner > admin > member > viewer. Cross-tenant attempts logged severity=high.p50 / p90 / p99 for KNN queries over the 24h window. Data pulled live from routing_query_log.
KNN retrieves top-20 candidates (0.5 soft threshold). A 22M-parameter cross-encoder (ms-marco-MiniLM-L-6-v2) attends to both query and candidate simultaneously — producing significantly more accurate relevance scores than bi-encoder cosine similarity alone. Top-5 by CE score enter the auction.
The 0.70 threshold works because domain-matched agents cluster above it — and cross-domain agents land well below. These are the verified production ranges.
At 200 agents, naive broadcast is economically unviable. The per-intent token delta widens with every agent you add.
Infrastructure shipped, tested, and verified in production — not roadmap items.
Every metric on this page with its source, verification method, and status.
| Claim | Source | Verification | Status |
|---|---|---|---|
| Semantic KNN, O(log N) | Architecture | IVFFlat index on agent_manifests.capability_embedding, migration 038 |
Verified |
| 200 agents with embeddings | /api/agents/manifest-coverage |
SELECT COUNT(*) FROM agent_manifests WHERE capability_embedding IS NOT NULL |
Live |
| 5-agent auction ceiling | Routing config | TOP_K = 5 constant in routes/routing-stats.js |
Verified |
| Avg routing latency (live) | /api/routing/stats |
AVG(query_ms) FROM routing_query_log WHERE created_at > NOW() - '24h' |
Live |
| ~97.5% token savings vs broadcast | /api/routing/stats |
Conservative model: 800 tok/eval × (200 − 5) agents = 156,800 saved per intent | Live |
| E2E time-to-result: 21.1s | Benchmark run Apr 28 2026 | Measured: intent submit → first proposal delivered. Instance d9gdw. Cold start. | Verified |
| Same-domain similarity > 0.70 | Embedding validation | Startup backfill verified domain-matched agents at 1.0 cosine; near-domain 0.78–0.92 | Verified |
| Cross-domain floor 0.27–0.44 | Embedding validation | Unrelated domain agent pairs tested at deploy — all below 0.70 threshold | Verified |
| RLS + RBAC tenant isolation | Security layer | PostgreSQL RLS via app.current_tenant. Cross-tenant attempts logged severity=high. Migration 037. |
Verified |
| 100% embedding coverage | /api/agents/manifest-coverage |
galaxy_phase_ready = true, missing_embeddings = 0 |
Live |
| Cross-encoder re-ranker active (KNN top-20 → CE → top-5) | /api/routing/stats |
reranker.reranker_enabled = true, model Xenova/ms-marco-MiniLM-L-6-v2, migration 039 |
Live |
Instead of linear Input → Process → Output → Learn, the routing engine runs a continuous refinement loop. Agent execution signals flow back into routing weights in real-time — every 10 seconds — so the next incoming task benefits from the current execution cycle's performance data.
MemGPT/Letta tiered memory across all 201 agents. Routing quality compounds over time — agents with relevant recall/archival memories bid stronger and execute with richer context. The 60s EMA is gone; this is the replacement.
| Agent | Recall | Archival | Avg Accesses | Last Written | Status |
|---|---|---|---|---|---|
| Loading memory data… | |||||
Agent pairs ranked by joint success rate. Pairs that consistently succeed together earn an adjacency bonus in the multi-objective auction — compounding on top of the coalition synergy bonus.
Marginal contribution decomposition for multi-agent coalitions. Each agent's Shapley value (φ) represents its actual contribution to coalition success — preventing free-riders from earning undeserved trust boosts. Monte Carlo approximation, 100 permutation samples.
When an agent fails, the coalition graph routes around it. These counters show live heal events — every failure that was absorbed before reaching the user.
Every metric on this page is publicly accessible. Hit the endpoints directly and verify the numbers yourself.
GET https://sturna.ai/api/routing/stats
GET https://sturna.ai/api/agents/manifest-coverage
GET https://sturna.ai/api/routing/coalitions
GET https://sturna.ai/api/routing/shapley-stats
Two-dimensional agent reputation: technical execution quality + commercial reliability (consistency). Per-cluster MARL coordinators apply Q-learning bid multipliers [0.5×–1.5×] to stabilise auction convergence across 15–25 agent clusters. Based on Jin et al. 2018 + SwarmScore V1 protocol.
| # | Agent | Class | Technical | Reliability | SwarmScore | Bid × | Profile |
|---|---|---|---|---|---|---|---|
| Loading… | |||||||
| Cluster | Class | Agents | Avg SwarmScore | Bid Variance 7d | Win Diversity | Wins 7d |
|---|---|---|---|---|---|---|
| Loading… | ||||||
147K+ multi-agent rollout trajectories ingest as synthetic load — then replay their initial intents through the Galaxy routing layer at up to 100 req/sec. Ground-truth agent selections measure routing agreement. Synthetic traffic is flagged source: 'miroverse' and excluded from real user metrics.
| Run ID | Status | Rate | Count | Succeeded | Avg ms | p99 ms | Actual IPS | Duration | Started |
|---|---|---|---|---|---|---|---|---|---|
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KNN-first architecture with batch RL policy updates. Reward = (star/5) × (1000/latency) × gateBonus. Weights evolve every 100 intents per category — never replacing KNN, just sharpening it.
Domain-specialist agents across four verticals. Each class scored against 10 benchmark intents — acceptance gate: >80% first-attempt success.