Product 01 · DataStrat

Data infrastructure designed for Quant PMs

DataStrat is ForeStrat's proprietary data ingestion platform, deployed directly into your infrastructure. Institutional-grade pipelines, vendor feeds, and security masters, live in weeks.

Pipeline Ingestion Live
Bloomberg → ingest ok
Refinitiv → ingest ok
Corp actions → enrich review
10-K filings → extract parsed
Output Research-ready dataset

Comprehensive data engineering for research and alpha

DataStrat deploys directly into your environment with pre-built connectors, automated quality gates, and point-in-time data lineage. Your team gets reliable data without managing vendor APIs or fragile script architectures.

Ingestion

DataStrat ships with resilient pipelines for high-frequency and alternative vendor datasets. Pre-configured connectors to hundreds of major financial data vendors. Automated domain-specific quality gates isolate feed anomalies before they corrupt downstream databases.

Transformation

Our modular data architecture is designed so you can securely plug in your own proprietary analytics, feature calculations, and alpha signals directly on top of the pipelines. Your custom code remains sandboxed and protected on your local infrastructure.

Linking

If cross-vendor instrument mapping is an issue, we design custom instrument matching graphs. We normalize diverse vendor reference inputs into unified, point-in-time security master datasets, ensuring research queries resolve consistently across historical cycles.

Data Quality & exception routing

We deploy extensible quality control panels tailored to financial formats. Instead of generic validations, we set up validation rules for complex corporate actions, index rolls, and yield curves. Custom notifications route exceptions directly to operations.

AI-ready data platform

DataStrat delivers production data engineered for agents and models: structured ontologies, entity-linked knowledge graphs, and point-in-time datasets that answer as-of queries without lookahead bias. Delta-on-write storage captures every change at ingest, so downstream features, backtests, and LLM context always reflect what was knowable when. Built-in lineage, versioning, and schema evolution keep your research stack current without rebuilds.

Unstructured data extraction

DataStrat scrapes, aggregates, and structures data from the web, PDFs, scan images, and alternative sources like Twitter and Discord. Example datasets include railroad throughput, prediction markets, and supply chain signals, delivered clean, fast, and ready to use. The platform also collects EDGAR datasets and delivers them faster than major vendors.

The data engineering lifecycle

From raw vendor feed to research-ready datasets. We design, deploy, and verify every step of the pipeline.

Step 01

Source & Audit

Audit current data spend and identify optimal sources. We assist in feed selection and structure vendor contracts for compliance.

Step 02

Ingest Design

Establish secure links via API, SFTP, or direct streaming. Deploy robust retry frameworks and enforce point-in-time integrity.

Step 03

Normalize & Master

Map tickers and identifiers (ISIN, CUSIP, FIGI) into a master graph. Apply adaptive parsers to structure PDF or text filings.

Step 04

Serve & Analyze

Deliver clean, structured tables directly to your research stack. Your proprietary scripts hook in cleanly on top of our database builds.

At a glance

Vendor connectivity
100s
of pre-built dataset connectors available
Pipeline validations
Domain
aware, checking index rolls & corporate actions
Data lineage
Point-in-time
audit trail preserved end-to-end
Infrastructure
Integrated
deployed directly in your database or cloud

Ready to optimize your data infrastructure?

Get a live walkthrough of DataStrat with our product team.

demo@forestrat.ai