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Pipeline Command Center

AI/ML → Agentic AI → RAG+KG — operated by AI Co-Workers

3,200 Inferences/hr
94.2% Model Accuracy
17 Active Agents
1.8% Hallucination
1,937 Decisions Logged
96
health
◆ Stage 1 — AI / ML
ARIA watching
🗗
Feature Store
rows18,400
null %0.0%
refresh15 min
features
ML Training Pipeline
frameworkXGB+BERT
last run2h 14m
cadencenightly
trained model
📦
ML Model Registry
models4
latest acc94.2%
rollbackv-1, v-2
load model
Inference API
p99 latency42 ms
rpm3,200
error rate0.0%
classifier scores
❖ Stage 2 — Agentic AI
MAX on-call
A2A Message Bus
throughput480 msg/s
loss rate0.000%
transportmTLS
task dispatch
🏛
Agent Orchestrator
agents17
active tasks591
protocolA2A/mTLS
plan task
📋
Task Planner
queue depth591
avg time4.2 min
HITL gate0.70
log decision
📄
Decision Log
records1,937
immutable✓ NIST AU-9
deletes0 (blocked)
retrieve context
expand KG
◆ Stage 3 — RAG + Knowledge Graph
SAGE monitoring
💾
RAG Chunk Store
chunks1,536
freshness1.2 hrs
SLA4 hr max
chunk vectors
📊
Vector Index
enginepgvector HNSW
dims512
p99 search8 ms
top-k chunks
🔗
KG Entity Store
entities2,191
edges6,803
types9
subgraph context
🌟
Grounded Response Engine
strategyRRF fusion
hallucination1.8%
citationsalways

○ AI Co-Workers On Duty

🤖
ARIA
Data Analyst • AI/ML Layer
WATCHING
AI/ML Accuracy holding at 94.2%. Feature null rate nominal. Next retraining in 6h 42m.
🤗
MAX
DevOps Engineer • Agentic Layer
ON-CALL
AGENTIC Task queue at 591 — elevated but within SLA. A2A bus stable at 480 msg/s.
🤖
SAGE
AI Developer • RAG+KG Layer
ACTIVE
RAG+KG Hallucination rate 1.8% — below 2% target. KG expanded +23 nodes this hour.
Live Activity
00:00ARIAModel accuracy stable at 94.2% — no drift detected
00:00MAXAgent Orchestrator processed 48 tasks, avg 3.8 min each
00:00SAGEKG ingested 23 new entities from DIC document batch
00:00MAXA2A message bus heartbeat OK — 17/17 agents responsive
00:00ARIAFeature Store refreshed — 18,400 rows, 0 nulls on input cols
00:00SAGEVector index HNSW rebuild complete — p99 latency 8ms

⚡ AI Co-Worker Pipeline Briefing

Prepared by ARIA, MAX & SAGE — CUI // SP-CTI

AI/ML Layer — ARIA
🤖
ARIA — Data Analyst
The AI/ML pipeline is operating within all nominal parameters. Overnight retraining completed in 2 hours 14 minutes — 8% faster than baseline, attributed to reduced feature variance in the innovation signals domain. The threat-classifier-v3 model is the performance leader at 94.2% accuracy on the held-out eval set. I am monitoring one early-warning signal: BERT signal-ranker accuracy dipped 0.4% on threat intel features compared to last week. This is within noise but I recommend scheduling a targeted fine-tune pass against the 65 newly ingested RAG chunks by end of week.
Accuracy 94.2% Inference p99 42ms 3,200 rpm BERT signal drift ▲0.4%
Agentic AI Layer — MAX
🤗
MAX — DevOps Engineer
The A2A message bus and 17-agent fleet are healthy. Task queue depth is elevated at 591 tasks but remains within the 750-task SLA ceiling — no escalation required. The Security and Compliance agents are processing a batch of 48 NIST-800-53 gap tasks from the overnight kanban cycle; this accounts for 82% of the queue elevation. Zero message loss events in 72 hours. mTLS certificate rotation is current. One watch item: the Knowledge agent's response time spiked to 380ms at 03:40 UTC — isolated, no recurrence. Decision audit log continues to grow cleanly; 1,937 immutable records, zero delete attempts blocked.
17/17 agents active 591 tasks queued 0 message loss 1,937 decisions logged
RAG + Knowledge Graph Layer — SAGE
🤖
SAGE — AI Developer
The RAG+KG layer is performing at its best metrics since launch. Hallucination rate is down to 1.8% on the held-out eval set — we crossed the 2% target three days ago after the RRF fusion weight tuning. The pgvector HNSW index rebuild completed overnight; p99 retrieval latency is now 8ms, down from 14ms. Knowledge Graph expanded by 23 new entities this hour from the DIC pipeline batch — we are now at 2,191 entities and 6,803 edges. The Grounded Response Engine abstained on 7 queries today due to confidence below 0.60 threshold — correct behavior. All 7 were escalated to the human review queue per the HITL protocol.
Hallucination 1.8% p99 latency 8ms 2,191 KG entities 7 HITL escalations
⚠ Recommended Actions (3) 1. ARIA: Schedule targeted BERT fine-tune on threat intel features by 2026-06-20 • 2. MAX: Monitor Knowledge agent response time — page if recurrence >300ms • 3. SAGE: Review 7 HITL escalations in /chat — 3 flagged as constitution boundary cases
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