From a two-person fintech team to automated monitoring, content production and community alerts, these worked examples show how TickAtlas fits into real software workflows — which endpoints are used, how the pieces connect, and what changes after integration.
The fintech scenario uses TickAtlas as the calculation layer behind its frontend, replacing months of indicator-engine work with an API integration.
Instead of spending months building indicator calculation engines from scratch, a fintech platform integrated 42 pre-calculated indicators via API in a single weekend.
/v1/indicators Filter by implementation type to see how a screener, batch indicator calls, LLM-ready summaries, heatmaps and alert pipelines fit together. Each one is an illustrative scenario written against the documented API.
5 scenarios shown
Automated monitoring of 50 currency pairs 24/7 using the screener and multi endpoints.
/v1/screener/v1/multi/v1/indicator Feeding real-time market data to an LLM for autonomous trading decisions without manual parsing.
/v1/summary/v1/indicators Rule-based market summaries and heatmaps generate consistent newsletter content.
/v1/summary/v1/heatmap Automated screener-based alerts delivered to a growing Telegram community via a trading bot.
/v1/screener/v1/indicator/v1/summary Pre-calculated indicators eliminated months of in-house development for a trading platform.
/v1/indicators/v1/ohlc/v1/symbols The value of a scenario library is not only the story — it is showing the architecture pattern another developer can recognize and reuse.
Use a screener to reduce the universe, then fetch richer detail only for matched symbols.
/v1/screener → /v1/multi Structured summaries can reduce custom parsing before handing market context to an AI workflow.
/v1/summary → LLM Keep indicator math out of the application layer and focus frontend effort on product experience.
/v1/indicators → UI Generate consistent drafts from structured data, then let a human review and add judgment.
/v1/summary + /v1/heatmap Schedule objective checks and deliver formatted events to Telegram, Slack or another channel.
screener → alert channel A compact comparison makes it easy to jump from your own use case to the closest scenario in the library.
| Use case | Core workflow | Scenario outcome | Plan used |
|---|---|---|---|
| Solo Algo Trader | Scheduled screener + batch detail | 3x faster signal detection | Pro |
| AI Trading Agent | Market summary → Claude → human review | Fully autonomous analysis | Starter |
| Forex Newsletter | Weekly summaries + heatmap → draft | 4 hours/week saved | Starter |
| Telegram Community | Hourly screener → Telegram bot | Zero manual effort | Pro |
| Fintech Startup | React app → proxy → indicator API | 2-day integration | Enterprise |
About these figures. These case studies are illustrative implementation scenarios, not audited customer references. The people named in them are composite personas, no company is identified, and every figure describes the scenario as written rather than a measured result from an identified account. The endpoints, parameters and architectures are real and documented; the outcomes you would see depend on your own workflow, configuration, market coverage and surrounding application.
Each scenario combines a small set of primitives. The implementation changes, but the integration contract stays predictable: HTTP requests, JSON responses and an API key.
/v1/screenerReduce many symbols to the ones matching your conditions./v1/multiFetch multiple symbols or indicator combinations efficiently./v1/indicatorsRetrieve the pre-calculated indicator set for a symbol and timeframe./v1/summaryReturn structured market context suited to downstream analysis and content workflows./v1/heatmapAdd cross-currency strength context to dashboards and editorial output.Start with a broad scan, then request detail only where needed.
/v1/screener Keep calculations server-side and render clean values in your interface.
/v1/indicators Use prepared summaries when raw values are not the right abstraction layer.
/v1/summary Combine summaries, cross-market context and your own editorial layer.
/v1/summary + /v1/heatmap The common thread across every scenario is simple: the application owns the user experience and business logic; TickAtlas supplies the market-data and calculation layer behind it. Every account starts pay-as-you-go with $2.50 of credit.