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
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
Outcome: selling noise, not insight
Outcome: sell insight, not noise
For providers
Ways of working
Specific projects
We tackle specific tickerization, data cleanup, profiling or validation tasks. A consultative approach for discrete projects which require specific expertise to improve your dataset.
Full pipeline
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.
Core capabilities
End-to-end data engineering for alternative datasets.
ETL
Convert raw data to standard format. ETL pipelines with validation and quality assurance checks.
NLP
Link your data to securities with precision entity resolution. Coverage across exchanges.
QC
Assess coverage across time and geographies. Build a backtest-ready notebook with statistical significance scores.
The process
Step 01
Submit your raw dataset
Step 02
Agent-powered transformation
Step 03
Link to listed securities
Step 04
Generate validation report
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
In this episode of Selling Signals, we’re joined by Jonathan Chin, co-founder of Facteus and author of Data-Minded. Jonathan brings a founder’s view on what it takes to build a transaction data provider trusted by institutional investors. We talk about why data businesses do not behave like SaaS companies. Data often sells optionality rather than a fixed outcome, which changes the way buyers evaluate products. Jonathan explains where SaaS playbooks break down, what still carries across and why data quality issues are different from software bugs. We also discuss aggregation, alpha decay and the role of AI in the future of alternative data. A big part of the conversation focuses on whether alternative datasets could become part of future model training rather than simply being queried through tools or MCP servers.
Get in touch
Tell us about your alternative data requirements. We'll be in touch shortly.