2026-05-05
Rena Labs
www.renalabs.xyzHeadquarters
NYC
Employee Count
8
Year Founded
2024
Amount raised
$3.3M
Business model
B2B SaaS and usage-based data intelligence layer
Early traction
Contracts with 30+ trading firms; ARR $600k+
Financial firms use sensitive data that others, like investors and regulators, need to verify, such as trades, balances, and risk, but sharing it would expose their strategies, customers, and edge.
This is especially true in prediction markets, where revealing trades or pricing would make it easy for others to copy or trade against them.
Today, the system relies on periodic audits that confirm accuracy but often catch fraud, hidden losses, or risky behavior too late.
This week’s company is giving exchanges a way to verify market makers’ behavior without exposing the private trading data behind it.
Rena Labs helps exchanges and financial platforms verify that market makers are behaving as expected, without requiring them to share the underlying data.
Market Makers: Firms or traders that constantly buy and sell to keep markets active and set prices.
Verify: Market makers provide their trading data to Rena’s secure environment, where the data can be analyzed without being exposed to the exchange, users, or even Rena itself.
Without Sharing: Rena runs checks on the data to detect risk, liquidity issues, or unusual behavior, while the raw data never leaves the system and only a simple pass/fail or risk signal is returned.
Bulleted Version
Market Opportunity: Prediction markets alone are expected to reach $1T in trading volume by 2030, and Rena is positioning itself as a core data layer for exchanges that want to maintain healthy, trustworthy markets.
Regulatory Tailwinds: As prediction markets go mainstream, exchanges are under growing pressure to prove their markets are fair, liquid, and not being manipulated.
Layered Expansion: Rena starts by helping exchanges verify market maker behavior, but the same system can be used anywhere two parties need to check data without exposing it, from financial audits to insurance underwriting to enterprise AI workflows.
Security Dependence: Rena’s model depends on secure computing environments, so any vulnerability or perceived weakness in that infrastructure could undermine trust.
Neutrality: Rena will need to ensure its algorithms are transparent, reliable, and perceived as neutral, especially when predatory behavior may not always be obvious or consistent across different market conditions.
Market Maker Pushback: Market makers may resist being evaluated, even privately, if they feel it limits their strategies or exposes underperformance.
Phala Network: Builds secure environments primarily for AI deployments, while Rena supports broader computation with a specific product tailored for delivering market insights.
Oasis Network: Provides usage-agnostic secure environments, but leaves it to developers to build use cases, whereas Rena delivers ready-made products on top of their own infrastructure stack.
WhyRena Labs
By enabling private trading data to be analyzed without being exposed, the odds are in Rena Labs’ favor to become the trust layer prediction markets need to scale safely.
*Nothing in this content constitutes investment or legal advice. Conduct independent diligence and consult professional advisers before making investment decisions.*
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