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Seed Round — February 2026
Machine.Machine
Building AI Organizations, Not Just AI Agents
Presented by
Peter
Round
$1M Seed Round
Stage
Working Prototype
The Question Everyone's Missing
What if AI could think
collectively — not just individually?
👤
Individual Agents
Isolated reasoning.
Shared data, not shared intelligence.
Coordination without cognition.
Limited to sum of parts.
🌐
Organizational Intelligence
Collective memory & learning.
Autonomous coordination.
Emergent capabilities.
Smarter than the sum of parts.
"It's like the difference between hiring brilliant individuals versus building a high-performing team."
The Problem
AI Agents Work in Isolation
Companies deploy dozens of AI agents — but they behave like a chaotic swarm.
⚡
Coordination without cognition — agents route tasks but never develop shared understanding
🧠
Shared data, not shared intelligence — same database, but every agent still thinks alone
📉
Scale creates overhead, not intelligence — more agents = more coordination cost, diminishing returns
🔗
No organizational memory — every insight dies with the conversation
Coordination frameworks exist. Organizational intelligence doesn't.
Why Now?
The Window Is Open
Three forces converged in 2024–2025. Enterprises are locking in their AI stack right now.
🧠
LLMs Hit Production Grade
GPT-4, Claude, Gemini are capable enough for real enterprise work. The agents are ready. The organization isn't.
🏭
Enterprise Adoption Exploded
Fortune 500s deployed their first AI agents in 2024. The chaos of uncoordinated agents is now a visible, budgeted problem.
🔧
Coordination Hit Its Ceiling
CrewAI, AutoGen, LangGraph — enterprises used them and hit the wall: coordination without organizational intelligence.

2023–2024: enterprises solved individual agents.
2025–2027: they solve organizational intelligence. We're already there.

Market Context
Everyone's Building Individual Agents
The entire industry is solving the wrong problem.
🔧
Salesforce Agentforce — Enterprise AI agent platform
🤖
AutoGPT — Personal AI assistant automation
🚢
CrewAI — Multi-agent task coordination
But they're all missing the bigger opportunity...
AI Agent Market
$47B
2024–2030
34% CAGR
MachineMachine is targeting the organizational layer nobody else sees
The Solution
MachineMachine = Organizational Intelligence
🧬
Collective Intelligence
System becomes smarter than the sum of individual agents
⚙️
Self-Organization
Agents coordinate autonomously using game theory & network science
🔬
Scientific Foundation
Integral theory, systems science & complexity theory applied to AI
📈
Evolutionary
Organizations improve themselves continuously over time

"OpenClaw builds agents.   MachineMachine builds organizations."

The Proof
Proof of Concept: AI Org in Action
We ran a real benchmark. Same model. Same task. Different architecture.
🏗️
Systems Architect
Network topology & infrastructure design
🤝
Coordination Specialist
Protocol & handoff management
⚖️
Governance Designer
Policy & decision frameworks
🧠
Emergence Engineer
Collective intelligence optimization
📊
Network Analyst
Flow analysis & performance metrics
Live Benchmark — Cerebras zai-glm-4.7 · Incident Response Protocol Task
Run Single Agent Multi-Agent Org Delta
Run 1 — baseline 90/100 73/100 −17
Run 2 — after 1 learning cycle 84/100 87/100 +3 ✅
The org learned why it lost. Applied one fix (structured handoff). Flipped the result.
✅ Multi-agent org won 4 of 5 rubric dimensions — added dual-layer detection, complete JSON schemas, 3-tier governance with quorum matrix
✅ Org improved between run 1 and run 2 — self-evolving architecture confirmed
📊 Benchmark open source: github.com/machine-machine/agent-org-simulator
Scientific Foundation
Built on Organizational Science
The only AI platform applying proven frameworks from organizational research.
Framework 01 🔷
Integral Theory
4-quadrant model of organizational development — interior/exterior, individual/collective — applied to agent design
Framework 02 🌀
Systems Science
Complex adaptive systems thinking — feedback loops, emergence, and non-linear dynamics in multi-agent environments
Framework 03 🕸️
Network Theory
Optimal information flow topology — graph-theoretic agent placement for maximum collective intelligence
Framework 04 ♟️
Game Theory
Mechanism design for resource allocation — ensuring agents cooperate efficiently without central coordination
Competitive Advantage
Beyond Every Competitor
Others (AutoGPT / CrewAI / Agentforce) MachineMachine
Individual agents — each works in isolation 🌐 Organizational intelligence — collective thinking
Manual coordination — humans must orchestrate ⚙️ Self-organizing systems — autonomous coordination
Limited to sum of parts — no emergence 🧬 Emergent collective consciousness — smarter together
Vendor-dependent — cloud lock-in 🏠 Self-hosted infrastructure — complete control
No organizational framework — ad-hoc, empirical design 🔬 Proven organizational science — systematic design
Agents discarded — no institutional memory 📚 Evolving organizations — continuous improvement
Market Opportunity
$47B+ Market Transformation
We're not building a productivity tool — we're building the platform for organizational transformation.
🏢
Enterprise
Replace entire departments with AI organizations — measurable ROI vs. hybrid teams
Primary
📈
SMB
AI workforce that scales with business growth — enterprise capabilities at SMB price
Growth
🛠️
Developer Platforms
Infrastructure layer for organizational AI apps — "AWS for AI organizations"
Platform
Competitive Moats
✦ Scientific Foundation — only player using org science
✦ Self-Hosted — no vendor lock-in, unlimited scale
✦ AIEOS Standard — cross-platform agent portability
✦ Collective Intelligence — emergent capabilities
✦ 2-year data advantage — our systems have logged how AI organizations fail, recover, and improve
34%
Market CAGR
2024–2030
$10B+
Organizational AI
sub-market
Business Model
Simple Pricing, Strong Unit Economics
🏢
Enterprise Deployment
€30–50K/year per organization. Annual contract, white-label infrastructure. No per-seat complexity.
Primary
🛠️
Developer Platform
Usage-based API access. Teams building org AI apps on our infrastructure layer.
Growth
🌐
AIEOS Ecosystem
Marketplace for specialized agent roles, org templates, and certified deployments.
Platform
€40K
Avg annual
contract value
25
Customers
= €1M ARR
Path to Series A
→ 3 pilots → validate willingness to pay
→ 10 customers → product-market fit confirmed
→ €300–500K ARR → Series A on our terms
✦ Break-even at 25 customers — no further dilution needed
The Vision
Every organization will have
an AI workforce.

The question is:
Individual agents
or intelligent organizations?
MachineMachine is the platform for
transcendent AI organizational consciousness —
the future of work itself.
Thinks Collectively Evolves Autonomously Scales Exponentially
The Ask
$1M Seed Round
"One thing to prove: a MachineMachine AI organization outperforms a 10-person hybrid team."
Product — 50%
Enterprise Platform v1
Deployable, white-label organizational AI infrastructure
50%
First Pilots — 30%
3–5 Paying Customers
Founders close first deals personally. No sales team needed yet.
30%
IP & Moat — 20%
Own the Category
Patent org intelligence framework. Publish AIEOS as open standard.
20%
18-Month Roadmap
→ Q1 — Enterprise platform v1 shipped
→ Q2 — First 3 paying pilots (€30–50K each)
→ Q2 — AIEOS open standard published
→ Q3 — Benchmark published: AI org vs hybrid team
→ Q3 — Patent portfolio filed
→ Q4 — €300–500K ARR → Series A raise
The Founding Team
Mariusz — Founder & Platform Architect
Nasr — PhD ML · AI Architecture Lead
+ 2 hires at Series A: Enterprise Sales Lead · Customer Success
See It in Action
What Happens Next
30-minute live demo → pilot proposal → 90-day proof of concept. We prove it works in your environment or you walk away.
Get in Touch
👤 Peter — Business Development
📧 [peter.email]
🔗 [peter.linkedin]
🛠️ Mariusz — Founder & CTO
📝 Technical deep-dive available on request
Live Demo Available
Watch 5 specialist AI agents solve complex organizational problems together — demonstrating emergence and collective intelligence in real time.
✦ Network topology design
✦ Autonomous governance decisions
✦ Measurable emergent behavior

"The companies that adopt AI organizational intelligence first will dominate their industries.
MachineMachine is the platform that makes it possible."