Acme Corp TEAM PLAN
LIVE DEMO
← Home
💰 Cost Intelligence
Real-time AI spend tracking across all providers, models, teams and features
Daily spend30 DAYS
Cost by model
Cost by team
Budget statusMTD
Active alerts3 NEW
Top expensive requestsTOP 10
TimeEndpointModelTokens inTokens outCostLatencyTeam
🔢 Token Analytics
Efficiency analysis — identify waste in system prompts, context windows and caching opportunities
Total tokensMTD
182M
− steady usage
Efficiency score
74/100
⇧ +6 pts this week
Cache hit rate
21%
Target: 40%+
Wasted tokens
38M
⇧ $1,240/mo excess
Token usage breakdown — daily
System prompt analysisACTION NEEDED
Token efficiency by endpoint
Optimization recommendationsSAVE $1,240/mo
⚖ Model Comparison
Live pricing across all 23 models — find the optimal model for your exact usage profile
Usage profile
Prompt tokens (per call)
Completion tokens (per call)
Requests per month
All models — sorted by monthly cost
ModelProviderTierInput $/MOutput $/MCache $/MPer callMonthlyvs cheapestContext
Cost scatter — quality vs price
Provider breakdown
⚡ Performance & Latency
p50/p95/p99 latency, TTFT, error rates and SLA compliance across all models
p50 latency
843ms
⇧ Improved 12%
p99 latency
4.2s
⇩ Watch p99 spike
Avg TTFT
218ms
⇧ Improved 8%
Error rate
0.4%
⇧ Below SLA 1%
Latency percentiles — daily
Latency by model
Error rate over timeSLA: <1%
TTFT distribution
SLA compliance by modelAll within SLA
Modelp50p95p99Error%RequestsSLA Status
🎯 Quality & Evaluation
Prompt versioning, A/B testing, side-by-side output comparison and regression tracking
Avg quality score
8.4/10
⇧ +0.3 this week
Active A/B tests
3
▶ Running
Eval datasets
12
+2 this month
Regressions
1
⚠ Needs review
Active A/B experiments
ExperimentVariant AVariant BMetricStatusWinner
Quality scores over time
Side-by-side output comparison
CURRENT: GPT-4o • $0.0085/call • Score: 8.2/10
The quarterly earnings report shows a strong performance across all business units, with revenue growing 23% year-over-year to $4.2B. Operating margins expanded 180bps driven by efficiency initiatives...
CANDIDATE: Gemini 1.5 Flash • $0.0006/call • Score: 8.0/10
Quarterly earnings demonstrate robust growth across all divisions, with 23% YoY revenue increase reaching $4.2B. Operating margin improvement of 180bps reflects successful efficiency programs...
💡 Gemini Flash achieves 97.5% of GPT-4o quality at 7% of the cost for this summarisation task. Estimated monthly saving: $680
Eval results — latest run12 datasets • 2h ago
DatasetModelAccuracyCoherenceFactualityAvg scorevs baseline
🧠 AI Intelligence Layer
The moat — auto model router, prompt optimizer agent, and intelligent cost autopilot
Router savings
$2,840
saved this month
Routes optimized
64%
of all requests
Prompt compress
28%
avg token reduction
Quality maintained
99.1%
vs baseline
🔃 Auto model routerACTIVE
The router automatically selects the cheapest model that meets your quality threshold per request type.
Router decisions — last 7 days
🤖 Prompt optimizer agentBETA
AI-powered prompt compression — maintains semantic meaning while reducing token count by 20-35%.
📄 Smart caching recommendations
📊 Enterprise Reporting
CFO-ready dashboards, departmental chargeback and automated executive summaries
Total AI spend YTD
$38.4K
Q1 2026
Budget remaining
$21.6K
of $60K annual
Cost per request
$0.048
⇧ 14% more efficient
Monthly spend — YTD
ROI metrics
Departmental chargeback report
DepartmentMTD SpendRequestsTop modelCost/requestEfficiencyBudget %YoY
Scheduled reports
🔒 Security & Governance
API key management, audit logs, RBAC, data retention and compliance controls
Active API keys
7
3 teams
Audit events today
284
All normal
Compliance
100%
SOC2 compliant
API keys
KeyNameOrgCreatedLast usedStatus
Role-based access control
UserRoleCan viewCan exportCan configure
Audit logLast 24h
TimeUserActionResourceIP addressStatus
Data retention policy
Compliance status
🔧 Developer Experience
SDK setup, integration health, API explorer, webhook config and debug tools
SDK integrations
4
Python, TS, Go, Ruby
Webhook endpoints
3
All healthy
Failing webhooks
1
⚠ Needs fix
Quickstart — Python
# Install pip install vantage-ai[openai] # Usage — 2 line change import vantage from vantage.proxy.openai_proxy import OpenAI vantage.init("vnt_acme_xxxxxxxxxxxx") client = OpenAI(api_key="sk-...") # Identical API — Vantage wraps transparently response = client.chat.completions.create( model="gpt-4o", messages=[{"role": "user", "content": "Hello"}] ) # ✓ Cost: $0.000110 | Tokens: 12+8 | Latency: 423ms
Integration health
Webhook configuration
Endpoint URLEventsLast deliveryStatus
Live event streamLIVE