How It Works

From question to
live dashboard

Three steps. Zero configuration. Agent swarms handle the rest.

01
02
03
01

Describe what you need

Type a question in plain English. No query language, no configuration wizard, no data source selection.

The Intent Analyzer classifies your request across 169 pre-defined domains — finance, weather, sports, health, and more. Ambiguous queries get LLM classification. Clear queries resolve instantly.

Example queries

“Show me Bitcoin price over 30 days”
“Compare weather in NYC vs Tokyo”
“Track my Shopify revenue by channel”
“Monitor server uptime across 3 regions”
New chart

Show me Bitcoin price over the last 30 days

Analyzing intent...
Detected
Domain: Finance Entity: BTC Period: 30d Intent: Visualize
Classification: keyword match Confidence: 0.97
Chart Creator Pipeline run_7kM2xR9
Intent Analyzer 1.2s
API Hunter 2.8s
Access Evaluator 0.9s
Documentation Parser 3.1s
Endpoint Analyzer 1.4s
Chart Recommender running
Chart Generator pending
Step 6 of 7 Elapsed: 11.4s
02

An agent swarm builds your chart

Your request enters a sequential pipeline of specialized agents. Each agent solves one part of the problem and passes enriched context to the next.

Intent → API Hunt → Access Check → Doc Parse → Endpoint Config → Chart Select → Generate

The entire pipeline runs on durable execution — no serverless timeouts, full process checkpointing, graceful fallback at every step.

Average build time: 8–15 seconds for a complete chart with live data.

03

Ask anything about your data

Every chart on your dashboard is queryable. Click any chart and ask questions in natural language — provisioned agents handle monitoring, prediction, and alerts automatically.

Not just charts. Entity queries produce rich profile cards with images, stats, and action buttons.

Change time ranges. Switch visualizations. Ask “why did this metric drop?” The agent has full context of the underlying data schema, refresh intervals, and data source.

The Cross-Chart Orchestrator sees patterns across your entire dashboard — correlating metrics that span multiple data sources and charts.

Monthly Revenue Live · Stripe API

Why did revenue drop last Tuesday?

Revenue decreased 12% on Tuesday due to a payment gateway outage between 2–5pm EST. Stripe reported incident #4821. Recovery began at 5:15pm. Comparing to the previous Tuesday, all other metrics were within normal range.

Sources: Stripe API, Incident Log 1.8s

What makes this different

Not another chat-to-chart demo. Production infrastructure built on specialized agents, real data, and hard constraints.

Not a wrapper around GPT

Specialized agents in sequence, not one generalist LLM trying to do everything at once. Each agent is an expert at one slice of the problem. The result is predictable, production-quality output from natural language.

Real data, real-time

Connected to 80+ data providers. Not cached training data, not demo datasets. Every chart fetches live data from the source, with adaptive refresh rates based on data granularity.

Gets faster with use

Schema caching, signup flow caching, EMA confidence scoring. Every interaction makes future requests faster. Popular APIs resolve in seconds. The system learns from every successful pipeline execution.

Hard guardrails

Free-tier guarantee, output validation, domain classification. Rules agents cannot violate, not suggestions they might ignore. Malformed configs are caught before they reach the frontend.

See it in action

Describe what you want to track. Watch agents build your dashboard in seconds.