Bring Arthalekh’s return-forensics engine into your own product.
Use the official TypeScript SDK and versioned API to fetch unadjusted prices, corporate actions, IPO metadata, manual bonuses, operational health, and portfolio simulations that stay aligned with the app.
See the API call, the response, and the widget it powers.
DEMO.BSE turns ₹10,000 into ₹33,373 with ₹263 in cash dividends, 210.5263 shares held, and CAGR N/A. Below, the sample request hits the authenticated analysis API, the JSON excerpt shows the real shape developers receive, and the widget demonstrates how quickly that payload becomes a product feature.
Sample curlCopy this request to reproduce the same flow with your own API key.
Expand▾
Copy this request to reproduce the same flow with your own API key.
curl -X POST 'https://arthalekh.com/api/v1/analysis' \
-H 'Authorization: Bearer YOUR_API_KEY' \
-H 'Content-Type: application/json' \
-d '{
"symbol": "DEMO.BSE",
"initialInvestment": 10000,
"includeDividends": true
}'Sample response excerptTrimmed for readability. Actual responses include the full price and simulation arrays.
Expand▾
Trimmed for readability. Actual responses include the full price and simulation arrays.
{
"data": {
"symbol": "DEMO.BSE",
"source": "demo",
"resolvedInputs": {
"ipoDate": "2024-01-02",
"ipoPrice": 95,
"initialInvestment": 10000,
"includeDividends": true
},
"latestQuote": {
"date": "2024-03-04",
"close": 157.27
},
"prices": [
{
"date": "2024-01-02",
"close": 100.9
},
{
"date": "2024-01-03",
"close": 102.16
}
],
"actions": {
"dividends": [
{
"date": "2024-02-10",
"dividendPerShare": 2.5
}
],
"splits": [
{
"date": "2024-02-24",
"splitCoefficient": 2
}
],
"bonuses": [
{
"date": "2024-03-16",
"numerator": 1,
"denominator": 1
}
]
},
"simulation": {
"finalValue": 33372.63157894737,
"totalDividends": 263.1578947368421,
"sharesHeld": 210.52631578947367,
"growthX": 3.3372631578947365,
"cagr": null,
"series": [
{
"date": "2024-01-02",
"close": 100.9,
"shares": 105.26315789473684,
"cash": 0,
"value": 10621.052631578947
},
{
"date": "2024-03-04",
"close": 157.27,
"shares": 210.52631578947367,
"cash": 263.1578947368421,
"value": 33372.63157894737
}
]
}
},
"source": "demo",
"requestId": "req_example_123"
}Build a real widget from one analysis response.
This demo uses the same analysis shape your app receives from Arthalekh. Change the symbol or investment and the widget refreshes with new server-side results.
One response gives you the ingredients to render a meaningful investor widget: resolved IPO assumptions, the latest quote, corporate actions, and a full value curve.
import { createArthalekhClient } from '@arthalekh/sdk';
const client = createArthalekhClient({
apiKey: process.env.ARTHALEKH_API_KEY!,
});
const bundle = await client.analysis.bundle({
symbol: 'WIPRO.NSE',
initialInvestment: 10000,
includeDividends: true,
});
console.log(bundle.data.summary.finalValueLabel);
console.log(bundle.data.markers.price.bonuses);
console.log(bundle.data.analysis.simulation.totalDividends);Return the same unadjusted price history, action overlays, and cash-dividend-aware portfolio math used inside Arthalekh.
Use analysis.bundle to get summary labels and chart marker sets without rebuilding client-side formatting logic.
Run bounded-concurrency symbol batches for research tools, portfolio screens, and editorial workflows.
Ship against a versioned REST surface and a live OpenAPI document instead of reverse engineering app routes.
Built for real workflows
Start with the SDK, then move deeper into docs, OpenAPI, and operational checks.
Show a truthful value curve that separates raw price movement from dividends, splits, and bonus-led share growth.
Generate symbol explainers, “what if” stories, and internal research tables from one normalized workflow.
Backfill IPO assumptions, review manual bonuses, and verify provider health before publishing analytics to users.
The shortest path to a useful integration
Treat this like a launch lane, not a reference dump. Most teams start with one call for the UI, one for batch workflows, and one for operational confidence.
Ship the first user-facing answer
Start with a single analysis call for the screen that matters most, then upgrade to bundle when you want chart markers and ready-made summary copy.
Scale to research and batch jobs
Once the UI path works, run symbol batches with bounded concurrency so editors, research tools, and internal screens stay predictable.
Add health and contract checks
Before other teams depend on the integration, wire in health checks and the live OpenAPI contract so failures are visible and recoverable.
One-call workflow for prices, actions, IPO resolution, and portfolio simulation.
Same as run, plus chart-ready markers and formatted summary strings for UI use.
Batch analysis with bounded concurrency and per-input success or error output.
Check Arthalekh API availability, environment, and cache footprint with your current key.
Fetch the raw live OpenAPI document that describes the public API contract.
Documentation
Start with the quick path, then go deeper into auth, REST, workflow logic, and failures.
Quickstart
Install the SDK, create a client, and run your first return-forensics request in minutes.
MCP Access
Expose Arthalekh content and live return-forensics through a public read-only MCP server.
Authentication
Authenticate with an Arthalekh API key and understand free vs pro behavior.
JavaScript SDK
Understand the SDK client methods, helper utilities, and chart-marker helpers.
REST API
Use the versioned HTTP API directly when you do not want a package dependency.
Analysis Workflow
Understand how Arthalekh resolves IPO assumptions and computes value over time.