Sovereign AI Mesh

🤖 Active Models

3 deploying

⚡ GPU Utilization

67%

KEDA managed

💸 Monthly Spend

$82K

▼ 40% savings

🚀 Deploy Cycle

14 days

▼ from 120 days

📡 Requests/sec

284

P99: 420ms

Platform Components

API Gateway (Kong)

Healthy

Model Mesh (vLLM)

Healthy

GPU Autoscaler (KEDA)

Healthy

Eval Pipeline

Healthy

Cost Attribution

Healthy

Audit Logger

Healthy

GPU Fleet Health

A100 Cluster (8)

78%

V100 Cluster (4)

45%

T4 Spot (12)

91%

Live Request Feed

[09:14:22] POST /v1/completions → azure-gpt4o → 284ms, 1200 tokens

[09:14:21] POST /v1/embeddings → text-embedding-3-large → 42ms

[09:14:20] GET /v1/models → registry sync

[09:14:19] POST /v1/completions → vllm-llama-3 → 189ms, 880 tokens

[09:14:18] POST /v1/completions → anthropic-claude → 412ms SLOW

Model Registry

Model	Provider	Version	Cost/1K tokens	Requests/day	Latency P99	Status
GPT-4o	Azure OpenAI	2024-11	$0.015	48,200	420ms	Production
LLaMA-3.1-70B	Self-hosted vLLM	Q4	$0.002	22,100	189ms	Production
text-embedding-3-large	Azure OpenAI	2024-09	$0.00013	180,400	42ms	Production
GPT-4o-mini	Azure OpenAI	2024-07	$0.00015	31,000	180ms	Production
Claude 3.5 Sonnet	Anthropic	20241022	$0.003	8,400	380ms	Staging
Whisper Large v3	Self-hosted	v3	$0.0001	2,100	210ms	Review

AI CI/CD Pipeline

Build #1482 — LLaMA-3.1-70B Fine-tune

Running

✓ Data Prep

2m 14s

✓ Fine-tune

48m 02s

⟳ Eval Gate

Running…

Cost Gate

Pending

Promote

Pending

Eval Gate — Golden Dataset

Running eval against 2,000 golden examples…

[1/5] Faithfulness: 0.924 ✓ (threshold: 0.900)

[2/5] Relevancy: 0.951 ✓

[3/5] Coherence: 0.938 ✓

[4/5] Running hallucination check…

[5/5] Cost-per-query estimate pending…

Pipeline History

#1481GPT-4o-mini updatePassed2h ago

#1480Embedding model v2Passed5h ago

#1479LLaMA LoRA experimentFailed1d ago

#1478Claude 3.5 SonnetStaging2d ago

GPU Resource Monitor

Total GPUs

8+4+12

Avg Utilization

67%

KEDA scaling

Spot Savings

60%

vs on-demand

KEDA Events

Today

Node	Type	GPU Util %	Memory Used	Temperature	Model	Status
gpu-a100-001	A100 80GB	82%	62/80 GB	71°C	LLaMA-3.1-70B	Active
gpu-a100-002	A100 80GB	74%	58/80 GB	68°C	LLaMA-3.1-70B	Active
gpu-v100-001	V100 32GB	45%	14/32 GB	52°C	Whisper v3	Active
gpu-t4-spot-001	T4 16GB (spot)	91%	14/16 GB	78°C	Embeddings	Hot
gpu-t4-spot-002	T4 16GB (spot)	88%	13/16 GB	74°C	Embeddings	Active

API Gateway (Kong)

Active Routes

Req/sec

284

Peak: 820

P99 Latency

420ms

▼ 18%

Error Rate

0.1%

Route	Upstream Model	Req/min	Avg Latency	Rate Limit	Status
`/v1/completions`	azure-gpt4o → vllm-llama (fallback)	3,840	284ms	600/min	Active
`/v1/embeddings`	text-embedding-3-large	8,200	42ms	2000/min	Active
`/v1/chat/completions`	azure-gpt4o	1,200	380ms	300/min	Active
`/v1/audio/transcriptions`	whisper-large-v3	84	210ms	50/min	Active
`/v1/fine-tunes`	Internal pipeline	2	–	5/hr	Admin only

Token Cost Attribution

Total Platform Spend

$82K

Budget: $120K (31% under)

GPU Savings vs On-demand

40%

≈ $54K saved

Tokens Processed

2.8B

Across all models

Team / BU	Top Model	Tokens (B)	Spend	Budget	Variance
Fraud Detection	GPT-4o	0.82B	$24,600	$30,000	▼ $5,400
Customer AI	LLaMA-3.1-70B	0.61B	$1,220	$5,000	▼ $3,780
Compliance	GPT-4o	0.44B	$13,200	$15,000	▼ $1,800
Risk Analytics	GPT-4o-mini	0.59B	$8,900	$8,000	▲ $900
Research	Claude 3.5	0.34B	$12,400	$15,000	▼ $2,600
Embeddings (shared)	text-embedding-3	1.0B	$21,680	$25,000	▼ $3,320

Business Units — AI Adoption Scorecard

Business Unit	AI Maturity	Active Models	Prod Deployments	ROI vs Baseline	Governance
Fraud & Risk	Advanced	4	7	+$14.2M	Compliant
Customer Experience	Scaling	2	3	+$3.8M	Compliant
Compliance	Scaling	3	4	+$2.1M	Compliant
Operations	Growing	1	2	+$0.8M	Review
Research	Exploring	2	1	Baseline	Onboarding

Governance Dashboard

Policy Violations

▼ from 18 last month

PII Incidents

6 months clean

Models Approved

3 pending review

Audit Coverage

100%

Incident	BU	Severity	Status	Date
Unauthorized model usage (shadow AI)	Operations	Medium	Investigating	Jun 20
Cost overrun: Risk Analytics BU	Risk Analytics	Low	Monitoring	Jun 18
Eval gate failure — experimental model	Research	Low	Resolved	Jun 15

Roadmap Tracker

Deploy Cycle

14 days

▼ from 120 days

Current Phase

Phase 3

of 4

Overall Progress

74%

On schedule

Platform Roadmap

Phase 1 — Foundation

Complete

API Gateway, Model Registry, Kubernetes cluster setup. Deploy cycle: 120d → 45d.

Phase 2 — Automation

Complete

AI CI/CD pipeline, eval gates, KEDA GPU autoscaling. Deploy cycle: 45d → 21d.

Phase 3 — Optimization

In Progress — 78%

Cost attribution, governance dashboard, spot fleet expansion. Deploy cycle: 21d → 14d.

Phase 4 — Sovereign Mesh

Q4 2026

Multi-region deployment, regulatory compliance toolkit, self-service BU onboarding. Target: 14d → 7d.

Executive Summary — Board Report

💰 GPU Cost Savings

40%

$54K/mo savings

🚀 Deploy Cycle

14 days

From 120 days (91% ▼)

💸 Annual AI ROI

$21M

Across all BUs

🤖 Models in Production

▲ from 2 (start)

🛡 Governance

100%

Audit coverage

Cost Trend vs Baseline

Q4 2025

$137K

Q1 2026

$109K

Q2 2026

$82K

Q3 Target

$66K

Key Business Outcomes

Phase 1 Complete

PoC cemetery eliminated. Governance framework operational.

Phase 2 Complete

120-day → 21-day deploy cycles. 8 models in production.

Phase 3 (Current)

$21M annual ROI across BUs. 40% GPU cost reduction achieved.

Phase 4 (Q4 2026)

Target: 7-day deploy cycle. Full sovereign AI mesh.