Without Valsys
- You have unique alternative data
- But no standardized ticker mapping
- Can't prove predictive power
- Institutional investors won't buy
Outcome: selling noise, not insight
The intelligence layer for capital markets
Transform your raw alternative data into validated, market-ready intelligence products. Prove predictive power. Reach institutional buyers.
About
Valsys is building the intelligence layer between the data economy and capital markets.
Our goal is simple: give funds a sharper view of reality, and help data providers sell insight instead of noise.
The problem
Raw data is noisy
With Valsys
- We map your data to securities
- Generate a data profile (notebook included)
- Validate statistical significance
- Package for institutional investors
Outcome: sell insight, not noise
For providers
Unlock dataset value
✓Transform raw data into market-ready products
✓Reach institutional buyers
✓Sell insight, not noise
✓Monetize your alternative data
Ways of working
Two ways to engage
Specific projects
Consultative
We tackle specific tickerization, data cleanup, profiling or validation tasks. A consultative approach for discrete projects which require specific expertise to improve your dataset.
- →Tickerization services
- →Data cleanup and transformation
- →Data profiling and validation
Full pipeline
End-to-End
We take your dataset all the way through to market and sell it to investors. Complete transformation from raw data to validated, market-ready intelligence products.
- →Full dataset transformation
- →Market validation
- →Distribution to institutional buyers
Core capabilities
What we do
End-to-end data engineering for alternative datasets.
ETL
Data transformation
Convert raw data to standard format. ETL pipelines with validation and quality assurance checks.
NLP
Ticker mapping
Link your data to securities with precision entity resolution. Coverage across exchanges.
QC
Data profiling and validation
Assess coverage across time and geographies. Build a backtest-ready notebook with statistical significance scores.
The process
From raw data to alpha
Step 01
Submit
Submit your raw dataset
→ →
Step 02
Transform
Agent-powered transformation
→ →
Step 03
Map tickers
Link to listed securities
→ →
Step 04
Validate
Generate validation report
Podcast
Selling Signals - the Data Monetisation Podcast
Selling Signals is the podcast for anyone building, selling, or buying data, with a focus on commercialising data in the investor ecosystem. Each episode brings together industry insiders to share real, first-hand experience from the front lines of data sales. We unpack what actually works when turning raw data into revenue, whilst exploring other data buying silos to break down the walls between them. Selling Signals delivers practical lessons to help data teams sell better and build stronger, more commercial data businesses.
Latest episode
Jordan Hauer: Taking Stock of the Alternative Data Industry
Episode 12 12 June 2026 56 min
In this episode of Selling Signals, we’re joined by Jordan Hauer, Founder and CEO of Amass Insights. Through Amass, Jordan helps investment firms discover, evaluate, and source datasets while also helping data providers better understand and monetise their assets. Having spent more than a decade at the centre of the market, Jordan has a unique perspective on how alternative data has evolved, from the industry’s early days of scarce and highly differentiated datasets to today’s world of abundant data and rapidly advancing AI tools. We discuss which datasets are seeing the strongest demand in 2026, how funds evaluate new data sources, and why sales cycles remain stubbornly long despite significant improvements in the market. Jordan also shares his views on trials, pricing, backtesting, and the common mistakes data providers make when trying to sell to investment firms. Whether you’re a data provider, investor, or anyone building in the data economy, this episode offers a valuable look at where the industry is heading next.
Get in touch
Ready to find harmony in the noise?
Tell us about your alternative data requirements. We'll be in touch shortly.