DATA ECOSYSTEMS

The data refinery.

Raw data flows in. Signed, structured, monetizable content flows out. Every output carries receipts of origin.

The Refinery

01
Raw Data

feeds, APIs, scans

02
Ingest

collect + sign

03
Process

62 pipeline bricks

04
Analyze

AI + scoring

05
Generate

signed output

What comes out

Intelligence

Market signals, scored insights

Podcasts

AI-narrated audio briefings

News

Curated, analyzed, attributed

Reports

Structured analysis documents

Video

Generated visual content

Music

AI-composed audio

Blogs

Long-form content generation

Data Lakes

Structured exports, APIs

Every output carries provenance receipts tracing every source, transformation, and model call that produced it. Some are terminal. Others feed back into the refinery.

RAW DATA TO SCORED TRADING SIGNALS

Market Intelligence

5,500+ data sources flow through the refinery every hour. News from global publishers. SEC filings and FRED economic indicators. Congressional legislation. Weather and seismic data. Blog posts and search results. The refinery extracts entities, sentiment, and market signals, then scores each for direction, magnitude, likelihood, and timeframe. Every step signed. Every source traceable.

INNews, government filings, financial data, weather, events, blogs, search results
OUTScored signals with confidence, urgency, and actionability
5,500+ feeds + dozens of government and financial APIs60+ structured fields per articleSub-second signal scoring

HOW IT RUNS

  1. 01Ingest from 5,500+ news feeds, government APIs, financial filings, weather services, event streams, blogs, and search results
  2. 02Deduplicate articles across URL, content hash, and title similarity
  3. 03AI analysis: 60+ structured fields per article including sentiment, entities, themes, political positioning, and market relevance
  4. 04Signal extraction: direction, magnitude, confidence, timeframe, and actionability scoring
  5. 05Provenance receipt chains from raw source through every transformation to final score

PRODUCTS USED

KNOWLEDGE IN, DELEGATED WORK OUT

Autonomous Agents

AI agents execute tasks, delegate to other agents, and produce outputs. Every action signed. An agent can hire another agent, hand off sub-tasks, and verify every result cryptographically end to end.

INKnowledge corpus, task queue, agent personas
OUTCompleted work with audit trail
50+ persona attributes per agentAgent-to-agent signed delegationEd25519 signed event chains

HOW IT RUNS

  1. 01Define agent persona: beliefs, constraints, skills, communication style
  2. 02Register the agent's Ed25519 signing identity so every action ties to provenance
  3. 03Agent receives work via Telegram, executes Synapse pipelines
  4. 04Agent delegates sub-tasks to specialist agents over signed handoffs
  5. 05Every action signed. Full provenance from persona to deliverable

PRODUCTS USED

CONTINUOUS SCAN TO INFRASTRUCTURE INTELLIGENCE

Network Monitoring

Continuous scanning of thousands of domains produces tech stack fingerprints, service detection, and infrastructure change alerts. Every scan cycle attested at the moment of collection. Not after.

IN16,000+ domains, DNS/TLS/WHOIS/HTTPS records
OUTProvenance-signed infrastructure fingerprints and change detection
16,000+ domains under continuous scan80+ infrastructure provider categoriesProvenance-signed every cycle

HOW IT RUNS

  1. 01Continuous DNS, TLS, WHOIS, and HTTPS scanning across 16,000+ domains
  2. 02Tech stack fingerprinting across 80+ provider categories
  3. 03Change detection and drift alerting
  4. 04Ed25519 provenance receipt on every scan cycle
  5. 05Real-time dashboard with historical scan data

PRODUCTS USED

AGENTS, PIPELINES, AND SERVICES ON ONE SIGNED MESH

Data and Agent Mesh

Synapse connects data pipelines, AI agents, and services into a unified execution layer. An agent can invoke a pipeline, a pipeline can delegate to an agent, and every interaction produces a signed receipt. Content generation, analysis, communication, scheduling, delegation. Every activity across the mesh is signed.

INData pipelines, AI agents, external services, delegation chains
OUTCoordinated work products with provenance across every hop
62 atomic processing bricksAgent-to-agent signed delegationDAG-chained provenance across the mesh

HOW IT RUNS

  1. 01Compose pipelines from 62 atomic processing bricks
  2. 02Agents delegate tasks to other agents or pipelines with signed handoffs
  3. 03Every hop across the mesh produces an Ed25519 receipt
  4. 04Receipts chain into DAGs and roll up into Merkle trees
  5. 05Walk the provenance from any output back through every agent and pipeline that contributed

PRODUCTS USED

FOR TEAMS SHIPPING AI AGENTS TO ENTERPRISE CUSTOMERS

Your AI Agents, Provenance-Signed

You ship AI agents to enterprise customers. They ask: what data did your agent use? What model? When? Can you prove it? Today, you point to logs. Logs are reconstructions. DRM3 provenance gives every operation a signed receipt at the moment it occurs. Your customers verify the chain themselves. No trust required.

INYour agent's data sources, model calls, and transformations
OUTCryptographic proof of what went in and what came out, verifiable by your customers
Ed25519 signed per operationMerkle rollup per sessionZero trust verification

HOW IT RUNS

  1. 01Integrate the Provenance SDK into your agent pipeline
  2. 02Every data fetch, model call, and transformation gets a signed receipt
  3. 03Receipts chain into Merkle trees per session
  4. 04Deliver provenance alongside your agent's output
  5. 05Your customer verifies the chain independently with published keys

PRODUCTS USED

FOR ORGANIZATIONS PREPARING FOR THE EU AI ACT

AI Transparency for Regulated Industries

The EU AI Act enforcement deadline is August 2026. Articles 12, 13, 14, and 17 require record-keeping, transparency, human oversight, and quality management for high-risk AI systems. Most compliance tools generate reports after the fact. DRM3 creates cryptographic proof at the moment of operation. The difference is whether your compliance trail can be independently verified or just trusted.

INAI system operations, data sources, model versions, transformations
OUTAudit-ready provenance trail, verifiable by regulators without system access
Article-by-article EU AI Act alignmentCommit-pinned license verificationThird-party verifiable without system access

HOW IT RUNS

  1. 01Sign every AI operation with Ed25519 provenance receipts
  2. 02Chain receipts to data source licenses pinned to specific versions
  3. 03Roll up into Merkle trees for batch-level attestation
  4. 04Publish signing keys at .well-known endpoints for third-party verification
  5. 05Regulators verify any receipt without accessing your systems or trusting your reports

PRODUCTS USED

Different inputs. Different outputs. Same protocol.

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