Projects Header Image

Projects We Back

At synapz, we don't chase hype—we align with protocols and pioneers pushing the edges of decentralization, intelligence, and human potential. Our involvement is rooted in purpose, not profit: we support systems that empower individuals, decentralize control, and unlock new forms of collective coordination across code, data, biology, and machines.

Here's a transparent look at the initiatives we are involved in, invested in, or actively supporting as of January 2026.

🔍 Transparency Disclosure

Derek Barnes (synapz founder) is a member of Covenant AI, the team behind Templar (SN3), Basilica (SN39), and Grail (SN81) on Bittensor. This represents direct involvement and investment beyond general support. We believe in full transparency about our relationships and commitments. Any opinions expressed on this site are my own and do not necessarily reflect those of my employer.


Bittensor Logo

Bittensor: Decentralized AI on the Blockchain

Open networks for open intelligence.

We are long-term believers in Bittensor, a decentralized protocol where machine learning models compete and collaborate on-chain. Our focus lies in the subnet layer, where real innovation happens. Each subnet represents a specialized domain of intelligence, hosted by independent teams.

🔹 Subnets We Support:

Subnet(s)OperatorFocusOur Involvement
3TemplarIncentivized collaborative training of LLMs using permissionless computeTeam Member
39BasilicaDecentralized compute infrastructureTeam Member
81GrailVerifiable post-training pipeline for LLMs - solving the fundamental trust problem in decentralized AI through cryptographically verifiable inference and reinforcement learningTeam Member
2DSperseDecentralized zero-knowledge proof infrastructure for verifiable AI inferenceAlpha Holder
17404-GENDecentralized text-to-3D generation for gaming, VFX, and virtual worldsAlpha Holder
44Score VisionDecentralized computer vision network for AI video analysis—training autonomous systems to understand visual content at scale, with football/soccer as the primary training domainAlpha Holder
50SynthProbabilistic forecasting and volatility modeling using Monte Carlo simulationsAlpha Holder
56GradientsDecentralized fine-tuning and training infrastructureAlpha Holder
62Ridges AIIncentivized Agentic TrainingAlpha Holder
64ChutesServerless model inference and hosting infrastructureAlpha Holder
68NOVA LabsAI for pharmaceutical drug discoveryAlpha Holder
75HippiusDecentralized cloud storage powered by a custom Substrate blockchain, IPFS, and S3-compatible storage—censorship-resistant, community-run infrastructure for AI-ready dataAlpha Holder

We are particularly excited about:

Covenant AI—developing three complementary subnets: Templar (SN3) for decentralized pretraining of large language models, Basilica (SN39) for decentralized compute infrastructure, and Grail (SN81) for verifiable post-training pipelines that solve the fundamental trust problem in decentralized AI through cryptographically verifiable inference and reinforcement learning. Together, these represent a comprehensive approach to decentralized AI infrastructure. As a member of the Covenant AI team and token holder in all three subnets, I'm directly involved in advancing this vision of decentralized AI training and infrastructure.

Ridges AI (SN62)—pioneering incentivized agentic training for AI coding agents. It's hard not to get excited about the development of AI coding agents that threaten to topple the centralized giants. This represents a fundamental shift toward decentralized AI development where agents can be trained, verified, and rewarded through transparent, on-chain mechanisms.

Chutes (SN64) and Gradients (SN56)—complementary subnets for serverless model inference and decentralized fine-tuning. Chutes processes over 90 billion tokens daily and has become Bittensor's first $100M+ subnet, underscoring the scale and adoption of this infrastructure.

DSperse (SN2)—the largest decentralized zero-knowledge machine learning proving cluster in the world. Having produced over 160 million ZK proofs to date, DSperse is pushing forward privacy-preserving computation by enabling verifiable AI inference. This has crucial applications for industries requiring data privacy, such as healthcare, where insurance companies can validate diagnoses without accessing full patient records.

NOVA Labs (SN68)—bringing decentralized science to drug discovery. NOVA uses AI to accelerate pharmaceutical research by incentivizing miners to discover novel molecular compounds. This represents the intersection of two movements we care deeply about: decentralized AI infrastructure and DeSci. Traditional drug discovery is notoriously slow and expensive, dominated by a handful of pharmaceutical giants. NOVA opens this frontier to permissionless participation, where anyone with compute can contribute to finding the next breakthrough treatment.

Additional Resources


Polkadot Logo

Polkadot: The Multichain Protocol of the Future

Cypherpunk roots. Scalable coordination.

Polkadot continues to stand out as one of the most principled and forward-thinking ecosystems in Web3. Built on Wasm-based runtime environments and a modular, forkless upgrade system, its architecture is designed for truly sovereign blockchains to interoperate seamlessly.

We're especially excited about Polkadot's next evolution: the Join-Accumulate Machine (JAM)—a cutting-edge, scalable, and decentralized compute fabric that brings Ethereum-like smart contract functionality and Rollup-style scalability directly into the Polkadot ecosystem. JAM not only preserves Polkadot's core principles of security and decentralization but extends its potential to support a universal, multi-runtime network.

Polkadot JAM Architecture

Polkadot Parachain Projects We Support:

  • PEAQ Logo
    Powering the Machine Economy and enabling DePIN infrastructure for autonomous machines and dApps.
  • Frequency: A Polkadot parachain enabling decentralized social media, backed by Project Liberty and the DSNP protocol.
    • We stand behind initiatives like the People's Bid to reclaim TikTok and decentralize the social graph.
  • Ex Machina DAOs (DEUS): We were Genesis OG holders of the DEUS token. However, after thoroughly reviewing the legal structure and terms, we've decided to exit our position at TGE. Read our full analysis: Why I'm Exiting DEUS at TGE.We remain excited about the robotics industry and will be seeking alternative ways to gain exposure to humanoid robotics and physical AI companies.
JAM reaffirms our belief that Polkadot isn't just a protocol—it's a meta-platform for sovereign innovation.

đź”’ Privacy Infrastructure

Privacy is not a feature. It's infrastructure.

Aztec Network

Aztec is a privacy-first Layer 2 on Ethereum—not just private transactions, but a fully programmable private world computer. After eight years of development, the network launched fully decentralized from day one with permissionless validators, decentralized proving, and community governance.

What makes Aztec different: every transaction is a zero-knowledge proof by default. Smart contracts can have private and public components that compose atomically. Users generate proofs locally—sensitive data never leaves their device. Through "private intents," users can access any DeFi protocol on any L2 or Ethereum mainnet while maintaining full privacy.

The project also funded ZK Passport—a breakthrough in private identity verification using NFC chips in government passports. With AI deepfakes about to break traditional KYC, cryptographic identity may be the only verification that survives.

đź’° Disclosure

We are participating in the Aztec public token sale (December 2025) and hold $AZTEC tokens. Read our full analysis: The Second Crypto War: A Private Ethereum.

DSperse (Bittensor SN2)

DSperse is a decentralized framework enabling verifiable AI inference through zero-knowledge proofs. Operating the largest decentralized zkML proving cluster in the world on Bittensor Subnet 2, DSperse has produced over 160 million ZK proofs to date.

The system uses a novel slice-based verification approach: AI models are automatically segmented into computational pieces, each converted into a zero-knowledge circuit and proven independently. This dramatically reduces verification costs compared to proving entire models end-to-end, while ensuring that AI outputs come with cryptographic proofs that the computation was done correctly.

ZK proofs enable high privacy for sensitive applications. For example, healthcare insurance companies can validate a doctor's diagnosis without accessing full patient data, relying instead on the cryptographic proof. As AI becomes embedded in critical systems, verifiable inference becomes essential infrastructure.

đź’° Disclosure

We hold alpha tokens in Bittensor Subnet 2 (DSperse).


BIO Protocol Logo

BIO Protocols & Decentralized Science

Science liberated from silos.

We actively support the rise of DeSci (Decentralized Science)—a movement reimagining how research is funded, verified, and shared. These DAOs and protocols are unlocking public-good biotech, regenerative medicine, and mycology science.

BioDAOs We Support:

ProjectFocus Area
Longevity research, Matrix Bio, and the Longevity Prize
Psychedelic science and mental health governance
Fungal science, sustainability, and LAB-IN-A-BOX innovation
ReflexDAOHealth data systems and research funding innovation

These DAOs represent a return to science as a commons, where peer-review and access are decentralized.


🤖 AI-Native Economies & Autonomous Agents

Agents are the new apps.

As AI-native protocols emerge, we're laying groundwork to develop, fund, and coordinate autonomous agents that are free, composable, and governed by users—not by centralized APIs.

Our Alignment:

  • AGNO: Currently researching this AI agent platform for its potential in autonomous task execution and decision-making.
  • Tibbir: We have taken a small, speculative position in Tibbir on Virtuals, exploring AI agent coordination and autonomous task execution. Read our analysis.

We'd love to dedicate more time to AI Agent development soon! Stay tuned for updates as we continue experimenting with these platforms and discover new ones.

We see these platforms not as financial assets, but as tools for coordinating machine labor and agency in the open web.


Final Word

We disclose our involvements not to boast, but to invite collaboration, demonstrate transparency, and show where our values lie. These projects reflect our belief that decentralized coordination, AI, and biotech will be the core pillars of a post-platform world—one where code, consciousness, and value can flow freely.

At Synapz, we back builders—not buzzwords.

On My Radar

  • Affine (SN120) — Founded by Const, a co-founder of Bittensor, Affine is a decentralized reinforcement learning platform that serves as an infrastructure layer connecting multiple AI subnets. Using a winner-takes-all RL incentive mechanism, it continuously refines AI models through competition on tasks like program synthesis and code generation. Affine is designed to be sybil-proof, decoy-proof, copy-proof, and overfitting-proof, ensuring only genuine performance improvements are rewarded. We're interested but haven't purchased alpha tokens yet as valuations remain outside our comfortable entry range.
  • Bitcoin — We hold a very small amount, just in case there's something to it.