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
Matthew Bernath: Building a Business Around Your Data
Episode 19 18 September 2026 54 min
In this episode of Selling Signals, we’re joined by Matthew Bernath, co-founder of Alternata. Matthew works with companies exploring whether their existing data could support a new business. We discuss how to assess the commercial opportunity before committing resources. Matthew explains how prototypes built with synthetic data can help test a proposed product with buyers. He also shares his approach to pricing around the value a customer expects to receive. The conversation turns to consumption pricing and Matthew’s preference for long-term relationships in which buyers help improve the product. He explains why one-off AI training deals can still make sense when the revenue justifies the work involved. Throughout the discussion, Matthew returns to one constraint. A data business should not damage the core operation that produces its data. We explore how that affects the opportunities a company should pursue.
Get in touch
Ready to find harmony in the noise?
Tell us about your alternative data requirements. We'll be in touch shortly.