$6.99
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Synapse AI LLM Operations Dashboard Template
Synapse AI is a light single-file HTML dashboard template that monitors LLM usage, token spend, model quality, and fine-tuning jobs in one workspace.
Synapse AI is an LLM operations dashboard template for teams running language models in production. The template renders in a light pastel theme with a blue accent and organizes the work into 9 views: Dashboard, Models, Analytics, Conversations, Playground, Fine-tuning, Prompt Templates, Model Comparison, and Settings. The whole app is one HTML file, and every chart is inline SVG drawn from data arrays in the script.
The Dashboard opens with 4 KPI cards: Total API Calls at 1.2M, Active Models at 24, Team Members at 8, and Monthly Cost at $450, each with a month-over-month delta. Below them, an API Usage by Model bar chart runs across 8 months with hover tooltips, a System Alerts panel ranks events as Critical, Warning, or Info, and 4 mini cards track Average Latency at 98ms, Accuracy Score at 96.8%, Error Rate at 0.5%, and Throughput at 1.8K requests per second. A Recent Experiments table lists fine-tuning runs with status pills and accuracy figures.
What is inside Synapse AI
- 4 KPI cards: Total API Calls 1.2M, Active Models 24, Team Members 8, Monthly Cost $450, each with a monthly delta
- API Usage by Model bar chart over 8 months with per-bar hover tooltips showing call counts
- System Alerts panel with Critical, Warning, and Info severity tags and timestamps
- 4 mini stat cards: Average Latency 98ms, Accuracy Score 96.8%, Error Rate 0.5%, Throughput 1.8K req/s
- Recent Experiments table with ID, Name, Status, Created, and Accuracy columns and status pills
- Models table with Model, Type, Calls, Cost, and Status for 4 deployed models
- Token analytics: 48.2M total tokens split into input and output, average cost $0.006 per 1K tokens
- Tokens by model stacked bars and a Spend by model panel totaling $390 for the month
- Model Comparison view with a 5-axis radar chart and a metrics table covering MMLU, p50 latency, cost per 1M tokens, context window, and uptime
- Playground with a prompt textarea and run action, fine-tuning jobs table, and a Prompt Templates grid
Specifications
| Format | Single self-contained HTML file; zero dependencies, no build step |
|---|---|
| Theme | Pastel |
| Mood | Light |
| Category | AI |
| Price | $6.99, one-time |
Who Synapse AI is for
Synapse AI gives ML engineers the Models table to compare call volume and cost per model, from synapse-large at 512K calls and $210 down to vision-beta at 98K calls and $36.
Platform leads use the Analytics view to watch token consumption: 48.2M total tokens split into 31.6M input and 16.6M output, at an average cost of $0.006 per 1K tokens.
Engineering managers use the Spend by model panel to reconcile the $390 monthly total across the 4 deployed models.
Product teams use the Model Comparison radar and metrics table to weigh synapse-large against synapse-fast on quality, latency, cost per 1M tokens, context window, and uptime.
Support leads use the Conversations view to check message volume per bot, such as the support triage bot at 412 messages today.
When to reach for it
Synapse AI suits a team that tracks LLM costs by reading provider invoices at month end. The template puts calls, tokens, latency, and spend per model on one screen, so cost surprises surface in the dashboard rather than on the bill.
Synapse AI also fits teams writing an internal AI ops page without a sprint of frontend work. The Model Comparison view already pairs a 5-axis radar (Quality, Speed, Cost efficiency, Context, Safety) with a side-by-side metrics table, and the Playground view ships a working prompt box with a run action, so the skeleton of an internal console is done.
Frequently asked questions
What does Synapse AI monitor?
Synapse AI monitors LLM operations: API call volume, token consumption split into input and output, cost per model, latency, accuracy, error rate, and throughput. The template also tracks fine-tuning jobs, prompt templates, conversations per bot, and side-by-side model comparisons.
How does the Model Comparison view work?
The Model Comparison view draws a 5-axis radar chart (Quality, Speed, Cost efficiency, Context, Safety) for two models and pairs it with a metrics table. The sample data compares synapse-large at 88.4 MMLU and 940ms p50 latency against synapse-fast at 79.1 MMLU and 210ms.
Can I connect Synapse AI to real usage data?
Yes, you can connect Synapse AI to real usage data. All figures live in plain arrays and table markup inside the file. Replace the usage series, model rows, and token constants with values from your provider's API or billing export, and the charts and panels re-render from the new numbers.
Does the Playground call a real model?
No, the Playground does not call a real model; it simulates a run. Clicking Run prompt shows a brief loading state and then a canned summary. The interaction pattern is in place, so wiring it to a real endpoint means replacing one timeout with a fetch call.
