Stop Fighting Cloud Vendor Lock-In

Pauhu = Biological Data OS. Deploy anywhere. Decide with AI. Trust every recommendation.

500MB
Full AI catalog
183
AI agents
100+
Languages
0
Cloud dependency

๐ŸŒ Transparent AI

You're using AI that explains itself. Pauhu uses 183 specialized agents. Every decision is auditable. Full transparency. Human oversight available: oversight@pauhu.ai

What Cloud Vendors Can't Do

Pauhu's unique advantages for data scientists

Capability Pauhu Cloud Vendors
๐ŸŒ Deploy Anywhere
Laptop, on-premise, any cloud, edge, air-gapped
โœ“ โœ—
๐Ÿค Decide with AI
Human-AI partnership, not replacement
โœ“ โœ—
โœ… Trust AI Recommendations
Full transparency, audit trail, explainable AI
โœ“ โœ—
๐Ÿงฌ DNA-Encoded Governance
Immutable policies, biological evolution
โœ“ โœ—
๐Ÿ’ป Runs Locally (500MB)
No cloud required, data never leaves your machine
โœ“ โœ—
๐Ÿฆ… 183-Agent Swarm Intelligence
Biological coordination, learns patterns
โœ“ โœ—
๐ŸŒ 100+ Languages
Semantic understanding, any industry, any language
โœ“ โœ—
๐Ÿ” Privacy by Design
Global compliance built into DNA, not bolted on
โœ“ Bolt-on

๐ŸŒ Deploy Anywhere

Your data, your infrastructure, your choice. cloud vendors locks you into their cloud. Pauhu runs everywhere.

๐Ÿ’ป Laptop (500MB)
Full AI catalog + governance on MacBook
๐Ÿข On-Premise Datacenter
Air-gapped, SCIF-compliant, zero cloud
โ˜๏ธ Any Cloud (AWS, Azure, GCP)
No vendor lock-in, migrate anytime
๐Ÿ“ฑ Edge Devices
IoT gateways, field laptops, mobile
โŒ cloud vendors Limitation:
Cloud only. Vendor lock-in. Expensive compute. Data must leave your premises.
# Deploy Pauhu anywhere in 3 commands
$ docker pull pauhu/biological-ai:latest
$ docker run -v ./data:/data pauhu/biological-ai
# Or run natively (500MB):
$ pauhu start --local
โœ“ Running on http://localhost:8000
โœ“ 183 agents initialized
โœ“ DNA governance loaded
โœ“ Zero cloud dependencies
๐Ÿ”ฌ

๐Ÿ† VERIFIABLE PROOF - This Is Your Moat

Don't trust marketing claims. Run the verification script yourself and see proof that Pauhu works in all deployment modes.

Run This Script
$ bash scripts/verify-deployment-modes.sh
โœ… Cloud: Live at validator.pauhu.workers.dev
โœ… On-Device: PII detection (0 network requests)
โœ… Hybrid: PII local, anonymized to cloud
โœ… Air-Gapped: 0 network packets
Same 183 agents. Five deployment modes. Customer chooses per use case.
Pauhu vs cloud-only AI
โœ… Pauhu
โ€ข Cloud, On-Device, Edge, Hybrid, Air-Gapped
โ€ข Customer chooses deployment per use case
โ€ข Same 183 agents work everywhere
โ€ข PROOF: verify-deployment-modes.sh
โŒ cloud-only AI
โ€ข Cloud only
โ€ข No on-device option
โ€ข No deployment choice
โ€ข Vendor lock-in
Real-World Use Cases (Customer Chooses Deployment)
๐Ÿฅ Healthcare - HIPAA
Deployment: On-Device
Why: Patient data never leaves hospital
Proof: 0 network requests
๐Ÿ›๏ธ Government - Classified
Deployment: Air-Gapped
Why: SCIF compliance required
Proof: 0 network packets
๐Ÿญ Manufacturing - IoT
Deployment: Edge
Why: Real-time, low latency
Proof: Runs on field laptops

๐Ÿค Decide with AI

Human-AI partnership, not replacement. You make decisions, AI provides insights.

โœ—
cloud vendors Way
Black box automation
$ snowflake auto-classify
Auto-classification complete.
1,247 fields tagged.
834 as PII.
413 as non-sensitive.
โš  No explanation provided
โš  No alternatives shown
โš  Can't undo without re-running
You have no choice. Trust us or don't use the feature.
โœ“
Pauhu Way
Transparent partnership
$ pauhu analyze --field email_address
๐Ÿ“Š Recommendation: Tag as PII (privacy Art. 4)
๐Ÿ” Why: DistilBERT detected email pattern (98% confidence)
โš ๏ธ Impact: 3 dashboards need anonymization
๐ŸŽฏ Agent: W11 Privacy Filter (M1 Prohibition)
Your options:
1. Apply recommendation (anonymize in dashboards)
2. Pseudonymize (hash emails)
3. Redact completely (replace with ***)
4. Keep raw (add audit justification)
What do you want to do? [1/2/3/4]:
You decide. AI explains why, shows impact, offers alternatives.
The Pauhu Philosophy
AI should augment human expertise, not replace it. Data scientists know their data better than any algorithm. Pauhu provides insights, recommendations, and analysis - but you make the final decisions. Every recommendation can be questioned, every decision can be justified, every choice is yours.

โœ… Trust AI Recommendations

Full transparency. Every recommendation is explainable and auditable.

Sample Recommendation

87% Confidence

Recommendation: Tag field customer_ssn as PII - Sensitive (privacy Article 9)

1
Data Profiling
Analyzed 1,247 values. Found pattern: XXX-XX-XXXX (Social Security Number format)
2
AI Classification
DistilBERT model: 98% match to SSN pattern. Compared against 10,000 known PII types.
3
Compliance Check
privacy Article 9: Special category data. Requires explicit consent + audit trail.
4
Impact Analysis
Used in 12 reports, 3 dashboards, 5 ML models. All require anonymization.
5
Risk Assessment
High risk: โ‚ฌ20M privacy fine if exposed. Current access: 47 users (should be 3).
6
Alternative Solutions
3 options: Pseudonymize (hash), Redact (***), Tokenize (reference table).
7
Recommendation Generation
Agent W11 (Privacy Filter) recommends: Tokenize + restrict access to 3 users.
8
Human Decision
You decide: Apply, modify, or reject. Full audit trail maintained.
โš–๏ธ AI governance Article 52 Compliant
Every recommendation includes: AI models used, confidence score, data sources, processing logic, impact analysis, alternatives, and full audit trail. Contact human oversight: oversight@pauhu.ai

๐Ÿงฌ DNA-Encoded Governance

The world's first biological data governance system

ACTG Base Pairs Encode Policy

A
Adenine = Prohibition
This field must NEVER be exposed (immutable safety)
T
Thymine = Obligation
This PII must ALWAYS be logged (compliance requirement)
C
Cytosine = Permission
This can be shared with analytics (allowed action)
G
Guanine = Freedom
Optional enrichment (no obligation to use)
Why DNA Encoding?
  • โœ“ Immutable: Can't be overridden by admins or hackers
  • โœ“ Biological: Evolves through external memory, not mutation
  • โœ“ Compact: 4MB encodes complete governance for 51 services
  • โœ“ Auditable: Every policy change tracked in RNA sequences
  • โœ“ Universal: Same encoding across all data types
# Sample DNA Sequence for Privacy Filter (W11)
AAAATTTTCCGG AAAATTTTCCGG
# Heavy on A (Prohibition) and T (Obligation)
Decoded Policy:
โ€ข AAAA: NEVER expose SSN, credit cards, health data
โ€ข TTTT: MUST log all PII access
โ€ข CC: MAY pseudonymize for analytics
โ€ข GG: Optional: add encryption tags
โœ“ This DNA sequence is immutable
โœ“ Even root admin cannot override
โœ“ Biological safety by design
๐Ÿ† Unique IP - No Competitor Has This
Traditional cloud platforms: Manual policies that can be changed or bypassed.
Pauhu: Biological DNA encoding. Immutable. Evolutionary. Patent-pending.

๐Ÿฆ… 183-Agent Swarm Intelligence

Like starlings in flight - each agent tracks 7 neighbors, collective intelligence emerges

๐Ÿ”

Data Quality Agents

37 agents monitor schema drift, anomalies, nulls, duplicates, outliers

Example: Agent detects 15% null increase in customer_email โ†’ alerts 7 neighbors โ†’ swarm validates pattern โ†’ recommends fix
๐Ÿ›ก๏ธ

Compliance Agents

91 agents enforce privacy, AI governance, ISO 27001, sector regulations

Example: New field added โ†’ compliance swarm checks against 23 regulations โ†’ auto-tags PII โ†’ updates audit trail
โšก

Optimization Agents

55 agents optimize queries, indexes, partitions, caching strategies

Example: Slow query detected โ†’ 7 neighbors analyze pattern โ†’ recommend index + partition strategy โ†’ 10x speedup
๐Ÿฆ

Murmuration Coordination

Like starling flocks, each Pauhu agent tracks exactly 7 neighbors. No central controller. Swarm intelligence emerges from local interactions. One agent detects anomaly โ†’ tells 7 neighbors โ†’ they tell their 7 โ†’ entire swarm adapts in seconds.

Self-Healing
One agent fails โ†’ neighbors compensate automatically
Pattern Learning
Swarm learns from every data scientist decision
Distributed Sensing
183 viewpoints > 1 monolithic system
Biological Evolution
Swarm adapts to your organization's patterns

๐Ÿง  Autonomously Intelligent

Learns, adapts, evolves - WITHOUT manual tuning. But YOU make the final decisions.

๐Ÿค–

Autonomous Learning (No Human Needed)

โœ“
Hebbian Learning
"Neurons that fire together, wire together" - routes strengthen with use
โœ“
Long-Term Potentiation
Good paths get stronger (weight ร— 1.1), bad paths weaken (weight ร— 0.9)
โœ“
Synaptic Pruning
Unused pathways automatically removed (like brain development)
โœ“
Pattern Recognition
Learns from execution history, adapts strategies automatically
โœ“
Self-Healing
Agent fails โ†’ 7 neighbors detect โ†’ auto-reroute โ†’ zero downtime
๐Ÿ‘ฅ

Human Partnership (You Decide)

โœ“
Approve/Reject Recommendations
AI suggests, you decide. Every recommendation can be declined.
โœ“
Override AI Decisions
Not satisfied? Choose alternative, provide justification, move on.
โœ“
Full Transparency
8-step audit trail shows WHY AI recommended, WHAT impact, WHICH alternatives.
โœ“
Domain Expertise
You know your data. AI learns patterns. Together = better decisions.
โœ“
Strategic Direction
AI optimizes routes. You set business goals. Perfect partnership.
๐Ÿ”ฌ

Verifiable Code Proof (Not Marketing)

Don't trust claims. Read the actual code that implements autonomous learning.

๐Ÿ“„ self_improving_agent.py
# AUTONOMOUS LEARNING
async def learn_from_execution(
context, action, result,
performance_metrics
):
# No human intervention needed
โœ“ Pattern recognition
โœ“ Strategy adaptation
โœ“ Knowledge retention
Location: services/44_pauhu-cache/src/shared/
๐Ÿ“„ bio_enhanced_router_v3.py
# HEBBIAN LEARNING
if success:
pathway.weight *= 1.1
neurotransmitter = DOPAMINE
else:
pathway.weight *= 0.9
โœ“ Long-term potentiation
โœ“ Neurotransmitter rewards
Location: services/50_pauhu-router/src/
๐Ÿงช Test Autonomous Learning Yourself:
# Run same query 10 times, watch latency improve
$ for i in {1..10}; do
curl http://localhost:8050/route \
-d '{"pattern": "PII detection"}' | jq '.latency_ms'
done
Run 1: 150ms (weight: 1.0)
Run 5: 105ms (weight: 1.3)
Run 10: 85ms (weight: 1.5)
Proof: Router LEARNED optimal path autonomously
โŒ Cloud Vendors
  • โ€ข Static rules (manual tuning)
  • โ€ข No learning from execution
  • โ€ข No biological optimization
  • โ€ข Manual performance tuning required
โš ๏ธ cloud-only AI
  • โ€ข Black box learning (no transparency)
  • โ€ข Auto-applies changes (no human control)
  • โ€ข No biological principles
  • โ€ข Cloud only (no local learning)
โœ… Pauhu
  • โ€ข Autonomous learning (Hebbian, synaptic)
  • โ€ข Human partnership (you decide)
  • โ€ข Biological optimization (DNA-encoded)
  • โ€ข Deploy anywhere (edge learning)
The Best of Both Worlds
Autonomous learning (no manual tuning) + Human control (final decision authority) + Full transparency (8-step audit trail)

See Pauhu in Action

Interactive demos of Deploy Anywhere, Decide with AI, and Trust AI

๐Ÿ‡ช๐Ÿ‡บ

Public Procurement Demo

Hilma.fi analysis with 8-step transparent AI process. See recommendations, decide with AI, full audit trail.

Try Live Demo โ†’
๐Ÿ’ป

Local Deployment Demo

Download 500MB, run locally, zero cloud. Full catalog + 183 agents on your laptop.

Coming Soon
๐Ÿงฌ

DNA Governance Simulator

Design ACTG sequences, see biological policy encoding, test immutability guarantees.

Coming Soon

Ready to Break Free from cloud vendors?

Deploy anywhere. Decide with AI. Trust every recommendation.
Biological governance that can't be hacked or overridden.

500MB
Full deployment size
100+
Languages worldwide
0
Cloud dependencies