Your Product Is Only as Good as Your Data.
Whether you are training a financial foundation model, building an autonomous execution system, or launching a FinTech platform — the quality of your underlying data determines everything. We deliver institutional-grade, LSEG-sourced financial data directly into your infrastructure.
The Data Layer Your Product Is Missing.
AI Research Labs
Training financial models on Yahoo Finance data is academic malpractice. Institutional-grade temporal alignment and survivorship-bias-free datasets are the minimum standard for production-grade model training. If your training data is wrong, your model is wrong.
FinTech Platforms
If your product generates financial analytics, runs risk models, or executes on behalf of users, the integrity of your underlying data is your liability. We provide the institutional data backbone so you can focus on shipping your product instead of building data pipelines from scratch.
Quantitative Infrastructure
Hedge funds, family offices, and proprietary trading desks that need sovereign data delivery without the overhead of maintaining internal data engineering teams. Your firm gets pristine Parquet files on your hardware, on your terms.
Garbage In, Garbage Out.
If you are training a model on data that does not account for survivorship bias, your model is learning from companies that no longer exist. If your temporal alignment is off by even one trading session, your model is making predictions based on information it would not have had in real time. These are not edge cases. These are catastrophic structural flaws that invalidate your entire output.
Most technology companies and AI labs spend months attempting to clean raw financial data before they can even begin training. Unadjusted stock splits, delayed corporate action cascades, and fragmented exchange timestamps create a data quality nightmare that silently destroys model accuracy.
The Reality: Your engineers are not generating alpha or building product features. They are performing janitorial work on raw market logs. We automate that entire pipeline so your team can focus on what actually matters — building the product that moves your company forward.
Sovereign Data Delivery.
Dedicated S3 Mount
We provision a highly secure, isolated AWS S3 Bucket tied explicitly to your firm’s IAM architecture. Your internal servers execute an automated sync to pull daily, pristine Parquet files directly onto your local infrastructure. No API calls. No rate limits. Pure file-level sovereignty.
Zero Compute Lock-In
You are never held hostage by proprietary vendor APIs or forced to utilize external compute. Once downloaded, the canonical data rests permanently on your physical hardware. Your team leverages its own GPU clusters, notebooks, or cloud instances exactly the way it prefers. We are the data refinery. You are the product builder.
Production-Ready on Day One
By the time the data hits your bucket, it is mathematically flawless and instantly ready for your PyTorch, TensorFlow, or Pandas pipelines. Corporate actions are adjusted. Temporal alignment is enforced. Survivorship bias is eliminated. You plug it in and start building.
Six Asset Classes. One Canonical Source.
Equities
Global equity markets with full corporate action adjustment, split normalization, and survivorship-bias-free historical depth.
Foreign Exchange
Institutional FX pairs with tick-level granularity. Temporal alignment across trading sessions and holiday calendars.
Futures
Continuous contract construction with roll-date normalization. Front-month and back-month parity across commodity, index, and rate futures.
Options
Full options chain data with Greeks computation, implied volatility surfaces, and expiration-adjusted temporal alignment.
Crypto
Cross-exchange normalized pricing with volume-weighted aggregation. Handles exchange delistings, forks, and stablecoin peg events.
Indices
Benchmark index composition with historical constituent tracking. Captures index rebalancing events and weighting methodology changes.
Build or Buy?
Building an internal data engineering pipeline for institutional-grade financial data is a multi-year, multi-million dollar undertaking. You need to negotiate direct LSEG licensing contracts, hire specialized data engineers who understand temporal alignment and corporate action cascades, build and maintain the ingestion infrastructure on AWS, and continuously monitor for data quality regressions.
LSEG licensing, 5-10 data engineers, AWS compute, QA infrastructure, and 12-18 months to production readiness.
Flat infrastructure fee. Pristine data delivered to your S3 bucket within days. Zero internal engineering overhead.
The math is simple: $180,000 per year versus $2,000,000 per year. You get the same institutional-grade data, delivered faster, with zero maintenance burden. The only rational reason to build it yourself is if your firm has a regulatory mandate requiring fully internal data provenance.
Start Building on Institutional-Grade Data.
Enterprise integration typically completes within one week. We handle the S3 provisioning, IAM configuration, and onboarding so your team can start training on pristine data immediately.
Schedule a Technical Integration Call$15,000/mo flat infrastructure fee. No hidden costs.