Built for capital markets,AI-Ready securities data infrastructure
We collect, refine, and structure scattered disclosure data and deliver it as data that AI can understand and act on.
The real bottleneck for AI is the data, not the model.
Securities data is scattered, identifiers differ everywhere, and relationships and provenance are disconnected. As-is, AI cannot trust it or call it repeatedly. We solve this at the data layer.
Call normalized securities data over API, Stream, and MCP.
# AI-Ready data in a single call
import waiker as wk
client = wk.DataStudio("YOUR_API_KEY")
data = client.dataset.get(
domain="insider-transaction",
symbols=["AAPL", "005930.KS"],
fields=["insiderTransaction", "source", "asOf"],
)
We bind disjoint ISIN, CUSIP, RIC, and tickers with a unique identifier (WIC).
Reproduce outputs and answer audits with source, as-of, and audit logs.
Before an AI answer, you need a verifiable data foundation.
You can verify where the data came from, how it was refined, and on what basis it was connected.
Calls use org-held keys, preserving data sovereignty.
Verify content provenance, authenticity, and rights via C2PA.
Link a WIC identifier and computation basis to every value.
Log inputs, processing, and as-of so identical inputs reproduce identical results.
Control scope and permissions and answer audits with access history.
Same data, shaped for each use.
The same 'AI Ready' data is delivered as Feed, Publish, or Agent depending on the use. It is not a separate product to pick, but one dataset used in different forms.
Receive normalized source data and use it in internal systems and models.
Drop visualizations and analysis straight onto MTS, web, and reports as widgets.
Turn requests into data and tool calls, returning outputs with source and evidence.
Receive normalized source data and use it in internal systems and models.
Drop visualizations and analysis straight onto MTS, web, and reports as widgets.
Turn requests into data and tool calls, returning outputs with source and evidence.
Beyond raw data supply — an evidence layer for AI calls.
It does not stop at handing over the original. We attach identity, classification, and relationships so AI can call and interpret it right away.
Identifiers, formats, and sources differ per source — stitching is the customer's job
A single record with identity, classification, relationships, and evidence — AI calls it directly
{
"wic": "WIC::SEC.EQ:KR.XKRX::005930",
"name": "삼성전자",
"waitics": {
"industry": "SEMICONDUCTORS",
"themes": ["HBM", "AI_MEMORY"]
},
"woosain": {
"peers": ["WIC::SEC.EQ:KR.XKRX::000660"],
"supplyChain": ["WIC::SEC.EQ:US.XNAS::NVDA"],
"impactLine": "AI_MEMORY_UPCYCLE"
},
"closePrice": 78500,
"currency": "KRW",
"source": "KRX",
"asOf": "2026-06-18"
}
Identifiers, formats, and sources differ per source — stitching is the customer's job
10 securities-market data domains, bound by ontology.
Every dataset follows the same delivery specification structure. Open a dataset within a domain to see its full schema, field definitions, and API spec on the detail screen.
Look deeper in the data catalog.
Open each of the 10 domains' datasets to inspect schema, fields, and real samples in detail.