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Overview

NextBlock Commits $3 Million to Soda Labs for Soda Labs blockchain privacy

ChainResearch desk
October 8, 2026
3 min read

NextBlock committed $3 million to fully fund a seed investment round in blockchain infrastructure developer Soda Labs, advancing the development of Soda Labs blockchain privacy systems, as detailed in reports from CoinJournal. The capital injection arrives as Soda Labs transitions its architecture from a network-locked privacy implementation toward a broader, chain-agnostic execution model targeting enterprise financial workloads across public ledgers.

Transitioning to Soda Bubble and Soda Labs blockchain privacy

For the past two and a half years, Soda Labs engineered a cryptographic privacy framework utilizing garbled circuits and multiparty computation, known as GC-MPC. The development relies on standard cryptographic primitives including AES and SHA256, running on commodity cloud CPUs without necessitating dedicated cryptographic accelerators. According to data provided by the project, this iteration powered more than 100 million transactions on the COTI network.

That foundational layer currently operates as the gcEVM privacy layer on COTI. With the new capital from NextBlock, the team is scaling its architecture into Soda Bubble, a modular coprocessor designed to ingest developer-defined workloads from separate blockchain environments. The system aims to execute private computations while shielding sensitive inputs from both public observers and Soda Labs itself. Analysts evaluating on-chain activity patterns and asset distributions often cross-reference deployment metrics using a comprehensive DeFi market dashboard to measure broader sectoral liquidity shifts across interconnected networks.

Commercial Deployment and Volume Metrics

Unlike early-stage protocol teams relying purely on testnets, Soda Labs enters its next funding phase with active deployments and commercial counterparties. Its technology underpins tokenisation platform Zoniqx and perpetuals exchange PriveX. Public disclosures indicate that PriveX processed upwards of $20 billion in trading volume, while Zoniqx actively boards asset issuers across multiple legal jurisdictions.

Pieter van Poecke, Founder and General Partner at NextBlock, noted that the existence of a working product, paying customers, and established technical intellectual property served as primary catalysts for the single-investor seed allocation. Evaluating the mechanics of these integrations requires looking at how validator sets handle encrypted state transitions without exposing user data to the underlying settlement layers.

Multi-Chain Expansion Roadmap and Validator Economics

Soda Labs intends to deploy the $3 million over a 12 to 18-month execution window. The capital allocation targets five distinct operational verticals:

  • Go-to-market scaling for commercial clients
  • Expansion of the Bubble Validator Network, which allows participants to mathematically verify private computations
  • Broadening blockchain coverage across major EVM ecosystems including Ethereum, Polygon, Arbitrum, and Base
  • Integrating non-EVM networks, specifically noting active development toward Solana compatibility
  • Deepening integrations with traditional financial entities such as banks, payment gateways, and tokenisation platforms

The Bubble Validator Network forms the core verification layer for this expansion. By decoupling private computation from native chain state execution via a coprocessor design, the protocol attempts to bypass the throughput bottlenecks inherent in standard smart contract execution environments. Whether this architecture can maintain performance under heavy commercial loads remains an open question for network operators monitoring upcoming testnet and mainnet deployments.

Technical Trade-offs in Coprocessor Design

Coprocessor architectures shift computational overhead away from primary validators, distributing heavy zero-knowledge or multi-party computation tasks to specialized nodes. This model alters validator economics by requiring distinct hardware configurations and trust assumptions separate from the base layer. Observers tracking this evolution must monitor how gas costs scale when user requests route through off-chain execution environments back to settlement chains.

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