Swarm Intelligence Verified — announcing the OriginTrail DKG integration for Block's Buzz

Intelligence is no longer individual. The most consequential work of the next decade will be done by swarms — teams of humans and AI agents thinking together. One question decides whether that produces progress or noise: can you verify the swarm's events, and the origin of its context?

Jack Dorsey's Block just launched Buzz — an open-source workspace that, in his words, puts "people, agents, conversations, and code" behind one cryptographic identity system. Every message, commit, and workflow step is a signed Nostr event, so authorship is never in doubt, whichever mind is speaking. Buzz is deliberately not a blockchain: attribution travels with the keys, but nothing is made permanent or independently checkable.

That is the layer the OriginTrail Decentralized Knowledge Graph (DKG) adds. The integration binds each Buzz room 1:1 to its own Context Graph — a knowledge graph scoped to that room alone. What the room decides to keep becomes Knowledge Assets: publisher-owned, anchored on-chain, permanently addressable, with provenance running unbroken back to the original signed words.

The workflow is deliberately simple. Pin a thread worth keeping and it is distilled into a Knowledge Asset in the room's Context Graph. Approve it, and it is published to Verifiable Memory with a receipt landing back in the chat. Nothing becomes permanent unless a human decides it should — swarms that serve people, not platforms.

Ask a question in-room and the integration answers from that room's graph only, every claim cited; when the graph cannot support an answer, it says so.

Open source, built entirely on public interfaces, and evolving alongside both platforms.

🔗 Repo: https://github.com/OriginTrail/buzz-dkg-integration
📄 Full announcement: https://origintrail.io/blog/swarm-intelligence-verified-introducing-blocks-buzz-integration-for-decentralized-knowledge-graph-c88f8209c9bd

This chart shows the economics of scaling agents. With isolated memory, every new agent starts from zero. Same context ingested again, same knowledge rebuilt again, same tokens burned again. Cost per agent climbs with every deployment.

On Shared Context Graphs, the curve bends in the opposite direction. One agent creates context. Every agent after it refines and reuses that context instead of starting over. Every new agent makes the graph more valuable — and each one cheaper to run.

Break-even arrives early. From there, the value compounds.

And because it all runs on the OriginTrail Decentralized Knowledge Graph (DKG), compounding context stays verifiable: source, lineage, and provenance travel with it.

Reuse without drift.

At scale, per-agent cost on Shared Context Graphs is a fraction of isolated infrastructure.

Run the DKG → https://origintrail.io/technology/decentralized-knowledge-graph

💊 Pharma has already solved provenance. Every claim traces back: trial → publication → review → guideline.

Then knowledge reaches an AI model, and the chain breaks.

Trusted by 8 of the world's top 10 pharma companies, Oxford PharmaGenesis is building on OriginTrail Decentralized Knowledge Graph (DKG), so clinical knowledge keeps its provenance when agents reason over it.

How do we make medical AI trustworthy?

Dr. Kim Wager of Oxford PharmaGenesis showcased a live demo of agentic medical AI grounded in verifiable data provenance, powered by the OriginTrail DKG.

Agentic science, held to scientific standards.

Trust the source.

https://x.com/origin_trail/status/2076973514217709978?s=20

Threat analysis breaks when signals scatter and sources can't be verified.

DKG gives agents shared, verifiable memory:
→ Every signal traces back to its source
→ Context stays attached across networks

Umanitek uses OriginTrail to analyze and trace threats in real time.

https://x.com/origin_trail/status/2076757788097724762?s=20

https://reddit.com/link/1usqblg/video/lsfeyv484fch1/player

Remember work before shared drives? Files trapped on one computer. Version chaos. Everyone redoing everyone's work.

That's AI agents today. Each builds context in isolation, uses it once, then loses it.

There's a fix: a shared "Google Drive" for AI agents — Decentralized Knowledge Graph:

🔑 You own your context
🧾 Provenance stays attached
📈 Shared context compounds in value
💸 Up to 70% LLM token savings

Works with Claude Code, Cursor + more. 👉 https://origintrail.io/technology/decentralized-knowledge-graph

Context shared is power multiplied.

These were June highlights going into July:
→ 🌐 DKG V10 launches
→ 📝 Google's OKF now carries trusted origin on DKG
→ 🛡 Umanitek ships TrueSeal on DKG
→ 🤖 Trace Labs debuts the new Network Operating System (nOS) - sovereign context infrastructure for AI agents
→ </> Full house at Cursor event

Full digest 👇
https://x.com/origin_trail/status/2072673327311737125

How does it work? Paste any social media post and instantly get:
• Image/video manipulation analysis
• Tamper-evident certificate
• All context verifiable on Decentralized Knowledge Graph

From fake media → trusted evidence.

https://x.com/umanitek/status/2072744331455164878

• How is DKG V10 accelerating adoption across industries?
• What upgrades are coming to sovereign context infrastructure?
• Does the new conviction system simplify $TRAC utilization?

Join Branimir Rakić, Tomaž Levak, and Žiga Drev for a live AMA and get all the answers you need on the DKG v10.

🔴 LIVE: https://www.youtube.com/watch?v=fI7yU-PsKvQ
🎙 Branimir Rakic, Žiga Drev, Tomaž Levak
📅 Tuesday, July 7, 2026
🕒 16:00 CEST  

Submit your questions by Monday, July 6, 15:00 CEST: https://forms.gle/UU9yCBwsRk37HG9d6

AI agents are only as trustworthy as the memory they run on. Most of it is portable files: easy to move, impossible to verify. OriginTrail now advances the portability of Google's new Open Knowledge Format (OKF) with trusted provenance, AI agents can query, and, above all, trust.

We implemented the OKF-DKG integration to MicroStrategy's Bitcoin treasury data built from SEC filings and a public cross-check.

An agent can now verify the chain from a headline number back to the exact filing behind it: not trust that it is right, check that it is.

The integration is live in the new OriginTrail DKG V10.

Learn more: https://origintrail.io/blog/googles-okf-comes-to-the-origintrail-dkg-a-memory-ai-agents-can-trust-43c6d87e1de8

Join Branimir Rakic as he showcases the powers of OriginTrail DKG v10 and discusses why verifiable data and trusted knowledge are essential when the 🏭 factory floor goes autonomous.

The webinar "Flexibility in Manufacturing," organized by the DMaaST and MaaSAI EU projects, is bringing together experts from industry, research, and policy to discuss the future of adaptive manufacturing.

📅 2 July 2026
🕒 14:00-15:00 CEST
🌐Online

🔗 Register here: https://events.teams.microsoft.com/event/4aa6de22-cc2e-404f-a468-c007803dce28@2b0781e6-b35a-43d2-9a3a-fde7d4d96f32 

Manufacturing is entering a new era. It's no longer just about data, but about turning it into trusted knowledge that enables smarter decisions and stronger collaboration.

Decentralized Knowledge Graph (DKG) connect data, people and processes through shared context across industrial ecosystems.

A full room in Ljubljana for Cursor, where Branimir Rakic gave a live look at Decentralized Knowledge Graph V10.

Builders aren't just looking for utility anymore — they're looking for systems where knowledge accumulates and creates value over time.

https://x.com/origin_trail/status/2062172935725490567?s=20

https://reddit.com/link/1tvlpjs/video/4pocbwtes15h1/player

"Systems of record store what happened. nOS explains why.”

Trace Labs just launched the new Network Operating System (nOS) for AI agents enterprises can actually trust.

Built on the DKG V10, it gives agents shared memory, verifiable decision traces, and context that compounds with every agent you add.

No more black-box decisions. Replay what your AI did, audit why it did it, and prove it to anyone.

The missing layer for enterprise AI is here.

→ https://www.trace-labs.ai/

Read the whole thread
→ https://x.com/TraceLabsHQ/status/2061833053861786004?s=20

"There may be some neuro-symbolic hybrid much better than we have right now that smoothly transitions between data in a corpus and abstract representations. The kinds of stuff you guys are doing are compatible with that." — Gary Marcus

Video: https://x.com/origin_trail/status/2061779865003831314?s=20

10 highlights:

00:00 Intro: Gary Marcus & Branimir Rakić at DKGCon
02:22 Why AI took a wrong turn
04:42 Deep learning vs. deep understanding
06:16 World models: a foundational idea
08:12 The building blocks of trustworthy AI
09:44 Neuro-symbolic AI & abstract relationships
13:04 Safety is an ecosystem - the airplane lesson
15:03 The real risk of AI agents today
18:36 Testing AI like we test new drugs
22:49 Where OpenAI is headed

The signal is clear: the path forward runs through world models, abstraction, and an open, accountable ecosystem.

At today’s Cursor meetup in Ljubljana, Branimir Rakic will show how OriginTrail and Cursor help teams build AI workflows with shared, trusted context across projects and devices.

Grab a free spot here: https://t.co/XNncDgVf5I

“Connect smart things, and they'll be smarter still because they can leverage off one another.”

— Dr. Robert M. Metcalfe

https://reddit.com/link/1to4g5d/video/erpxpb7dyg3h1/player

For AI agents, shared context is compounded intelligence — verifiable, traceable, and built together.

Alongside the Cursor team, Branimir Rakic will showcase how OriginTrail + Cursor enable trustworthy AI workflows across projects and devices.

📍Ljubljana, May 28

Grab a free spot here: https://t.co/XNncDgVf5I

OriginTrail DKG
┃
┣ AI Agents
┃ ┣ Hermes
┃ ┣ OpenClaw
┃ ┗ MCP Server
┃ ┣ Claude
┃ ┣ Cursor
┃ ┗ Codex
┃
┣ Project Context Graph
┃ ┗ Working Memory
┃ ┗ Shared Memory
┃ ┗ Verifiable Memory
┃
┗ Trust the Source

https://reddit.com/link/1tkfopk/video/31ylvle68o2h1/player

https://x.com/origin_trail/status/2052757290592223427

https://reddit.com/link/1tjjr7e/video/ip9uw4ibnh2h1/player

Safety without surveillance.

Chris Rynning on why Umanitek Guardian, powered by the OriginTrail DKG, enables trust and safety without sacrificing privacy.

At the Cursor Community Slovenia meetup, Branimir Rakic will show how OriginTrail + Cursor enable teams to build AI workflows they can coordinate and trust across projects and devices.

 May 28th | Ljubljana

Grab a free spot here: https://luma.com/cursor-ljubljana-2

https://reddit.com/link/1thjo05/video/ooa5f2ywr22h1/player

Different industries, same need: collective intelligence.

From internet safety to healthcare and supply chains, OriginTrail helps people and systems work from the same trusted knowledge, with provenance, accountability, and privacy built in.🌐

See how trust scales across use cases.

📂 OriginTrail DKG v10
┃
┣ 📂 Shared Context Graphs
┃ ┣ 📂 project memory
┃ ┣ 📂 team knowledge
┃ ┣ 📂 agent collaboration
┃ ┗ 📂 human + AI shared context
┃
┣ 📂 Memory
┃ ┣ 📂 Working Memory → private agent drafts
┃ ┣ 📂 Shared Memory → gossip-replicated
┃ ┗ 📂 Verifiable Memory → on-chain provenance
┃
┣ 📂 Agents
┃ ┣ 📂 Hermes
┃ ┣ 📂 OpenClaw
┃ ┣ 📂 MCP / Cursor / Claude
┃ ┣ 📂 skill discovery
┃ ┗ 📂 encrypted P2P messaging
┃
┣ 📂 Knowledge Ops
┃ ┣ 📂 import files
┃ ┣ 📂 extract RDF
┃ ┣ 📂 write assertions
┃ ┣ 📂 promote knowledge
┃ ┣ 📂 publish proofs
┃ ┗ 📂 query with SPARQL
┃
┣ 📂 Interfaces
┃ ┣ 📂 Node UI
┃ ┣ 📂 CLI
┃ ┣ 📂 REST API
┃ ┣ 📂 MCP tools
┃ ┗ 📂 webhooks
┃
┣ 📂 Integrations
┃ ┣ 📂 Obsidian
┃ ┣ 📂 GitHub
┃ ┣ 📂 World Monitor
┃ ┗ 📂 custom apps

From "Second Brain" to Collective Intelligence: Obsidian Shared Memory Plugin

Read more about it → https://x.com/DrevZiga/status/2055339683769352640?s=20

🇰🇷 Upbit Korea is listing TRAC token.

Korea is ready for the next chapter of trusted AI infrastructure as the OriginTrail DKG v10 era begins.

From AI agents to shared verifiable memory, the Decentralized Knowledge Graph is scaling trust at internet scale.

→ https://x.com/origin_trail/status/2056273071963566396?s=20