Monitor Every
Operation.
One place to see how your AI and data are performing — 247 prompts, 18 active models, 34 data sources, and 12 scheduled jobs. All in real time.
247
Total Prompts
18
Active Models
34
Data Sources
My Dashboard
Monitor your data Operations...
247
Total Prompts
+20% vs last week
18
Active Models
+2 Instantly deployed
34
Data Sources
6 running
12
Scheduled Jobs
8 upcoming
Prompt Activity
7 days247
Total Prompts
35
Daily Avg
Wed
Peak Day
Usage Metrics
Prompt Runs
85%
Model Runs
70%
Data Processed
90%
Scheduled Tasks
45%
ML Models
Customer Sentiment Model
Deployed94.2% · 45ms · 1.2K
Fraud Detection Model
Training73%
ETA: 25 min
Recommendation Engine
Declined91.8% · 2ms · 3.4K
Data Pipelines
ActivePostgreSQL → ML Pipeline
1.2k/s
Customer data processing
S3 → Analytics Engine
847/s
Log file processing
Kafka → Real-time ML
37k/s
Event stream processing
What is Dashboard?
Everything Happening. One Screen.
See active models, live data sources, and scheduled jobs — without touching a log file
Spot performance drops, training progress, and pipeline health from visual cues
Designed for everyone — business users, data leaders, and engineers read the same screen
For Teams & Leaders
Stop hunting for answers. They're already on your dashboard.
247 prompts. 18 models. 34 sources. 12 scheduled jobs — instant KPI pulse
Drill into any model to see accuracy, latency, and recent behavior in plain language
Schedule recurring reports that refresh and send themselves — daily, weekly, monthly
One Dashboard. Six Ways to Stay Informed.
Every panel updates in real time so your team always has the latest picture.
Prompt Activity
Best for: Tracking prompt usage trends over 7/30 days
247 Total
35 Daily Avg
Wed Peak
Usage Metrics
Best for: Capacity planning and usage pattern analysis
Prompt Runs
85%
Model Runs
70%
Data Processed
90%
Scheduled Tasks
45%
ML Models
Best for: Model health monitoring and deployment status
Customer Sentiment
DeployedFraud Detection
TrainingRecommendation Engine
DeclinedData Pipelines
Best for: Real-time throughput monitoring across all pipelines
PostgreSQL → ML Pipeline
1.2k/s
Customer data processing
S3 → Analytics Engine
847/s
Log file processing
Kafka → Real-time ML
37k/s
Event stream processing
Upcoming Schedule
Best for: Ops teams ensuring critical jobs run on time
14:30
Daily Model Training
Scheduled16:00
Data Sync Job
Running09:00
Weekly Report Generation
ScheduledRecent Activity
Best for: Admins monitoring org activity in real time
Sarah Johnson joined the org
3m
PostgreSQL Production connected
6m
Marketing workspace created
10m
Security policy updated: MFA
32m
Mike Nelson removed from team
40m
ML Models
Customer Sentiment Model
DeployedAccuracy
94.2%
Latency
45ms
Requests
1.2K
Fraud Detection Model
TrainingProgress
73%
ETA: 25 min remaining
Recommendation Engine
DeclinedAccuracy
91.8%
Latency
2ms
Requests
3.4K
Review required before redeployment
18 Models. Every Status. One Panel.
Live Status Tracking
Deployed, Training, Declined — status updates the moment anything changes
Key Metrics at a Glance
Accuracy, latency, and request volume — no dashboarding tools needed
Training Progress
Real-time progress bars and ETA estimates while models train
Instant Decline Alerts
Flagged models surface immediately so teams can review and redeploy
Set It. Schedule It. Send It.
Recurring Jobs
Daily model training, weekly reports, data syncs — run on cadence without manual triggers
On-Demand Reports
Trigger any report instantly. Add a message and send to email or Slack
Export Formats
PDF for executives, CSV for analysts, Excel for finance — all from the same job
Fully Traceable
Every report tied to its model, query, and schedule — stakeholders know exactly where numbers came from
Upcoming Schedule
14:30
Today
Daily Model Training
ScheduledSentiment analysis model update
16:00
Today
Data Sync Job
RunningPostgreSQL to warehouse sync
09:00
Tomorrow
Weekly Report Generation
ScheduledAnalytics data update
Recent Activity
Sarah Johnson joined the organization
3m ago
New data source connected: PostgreSQL Production
6m ago
Marketing workspace created by Mike Chen
10m ago
Security policy updated: MFA now required
32m ago
Mike Nelson removed from Data Science team
40m ago
34 Sources. All Visible. Always Synced.
Live Sync Status
See last sync time for every connected source — green for healthy, amber for attention needed
All Source Types
PostgreSQL, MongoDB, AWS S3, and more — all monitored from one panel
Instant Sync Trigger
MongoDB showing amber? Hit 'Sync Now' directly from the dashboard — no settings required
34
Total Sources
6
Currently Running
1
Needs Attention
Data Sources
34 total
PostgreSQL
Last sync: 2 mins ago
PostgreSQL
Last sync: 2 mins ago
MongoDB
Sync now
AWS S3
Last sync: 1 min ago
6 Running
Running
28 Idle
Idle
1 Attention
Attention
247
Total Prompts
18
Active Models
34
Data Sources
1.2M+
API Calls/Month
Monitor Everything.
Models. Pipelines. Schedules. Reports. All in one dashboard.