Pauhu for Data Scientists | Deploy Anywhere. Decide with AI.

What Cloud Vendors Can't Do

Pauhu's unique advantages for data scientists

Capability	Pauhu	Cloud Vendors
Deploy Anywhere Laptop, on-premise, any cloud, edge, air-gapped
Decide with AI Human-AI partnership, not replacement
Trust AI Recommendations Full transparency, audit trail, explainable AI
Rule-Based Governance Immutable policies, biological evolution
Runs Locally small deployment No cloud required, data never leaves your machine
Multi-Agent Swarm Intelligence Biological coordination, learns patterns
100+ Languages Semantic understanding, any industry, any language
Privacy by Design Global compliance built into configuration, not bolted on		Bolt-on

Deploy Anywhere

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

Laptop small deployment

Full AI catalog + governance on MacBook

On-Premise Datacenter

Air-gapped, SCIF-compliant, zero cloud

Any Cloud (AWS, Azure, GCP)

No vendor lock-in, migrate anytime

Edge Devices

IoT gateways, field laptops, mobile

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 small deployment:
$ pauhu start --local
 Running on http://localhost
 multiple specialized agents initialized
 governance system loaded
 Zero cloud dependencies

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
 Cloud: Live at validator.pauhu.workers.dev
 On-Device: PII detection (0 network requests)
 Hybrid: PII local, anonymized to cloud
 Air-Gapped: 0 network packets

Same multiple specialized agents. Five deployment modes. Customer chooses per use case.

Pauhu vs cloud-only AI

Pauhu

• Cloud, On-Device, Edge, Hybrid, Air-Gapped
• Customer chooses deployment per use case
• Same multiple specialized agents work everywhere
• PROOF: verify-deployment-modes.sh

cloud-only AI

• Cloud only
• No on-device option
• No deployment choice
• Vendor lock-in

Real-World Use Cases (Customer Chooses Deployment)

Healthcare - HIPAA

Deployment: On-Device
Why: Patient data never leaves hospital
Proof: 0 network requests

Government - Classified

Deployment: Air-Gapped
Why: SCIF compliance required
Proof: 0 network packets

Manufacturing - IoT

Deployment: Edge
Why: Real-time, low latency
Proof: Runs on field laptops

Download Verification Script View Source Code

Decide with AI

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

cloud vendors Way

Black box automation

$ snowflake auto-classify
Auto-classification complete.
1,247 fields tagged.
834 as PII.
413 as non-sensitive.
 No explanation provided
 No alternatives shown
 Can't undo without re-running

You have no choice. Trust us or don't use the feature.

Pauhu Way

Transparent partnership

$ pauhu analyze --field email_address
 Recommendation: Tag as PII (privacy Art. 4)
 Why: DistilBERT detected email pattern (98% confidence)
  Impact: 3 dashboards need anonymization
 Agent: PII Detection 
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.

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: €20M 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 (PII Detection) recommends: Tokenize + restrict access to 3 users.

8

Human Decision

You decide: Apply, modify, or reject. Full audit trail maintained.

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

Rule-Based Governance

The world's first biological data governance system

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 governance policy Encoding?

Immutable: Can't be overridden by admins or hackers
Biological: Evolves through external memory, not mutation
Compact: compact encodes complete governance for microservices
Auditable: Every policy change tracked in RNA sequences
Universal: Same encoding across all data types

# Sample governance policy Sequence for PII Detection (Agent)

                        CCGG
                        CCGG
                    
# Heavy on A (Prohibition) and T (Obligation)
Decoded Policy:
• : NEVER expose SSN, credit cards, health data
• : MUST log all PII access
• CC: MAY pseudonymize for analytics
• GG: Optional: add encryption tags
 This governance policy is immutable
 Even root admin cannot override
 Biological safety by design

Unique IP - No Competitor Has This

Traditional cloud platforms: Manual policies that can be changed or bypassed.
Pauhu: Biological encoding system. Immutable. Evolutionary. Patent-pending.

Multi-Agent Swarm Intelligence

Like starlings in flight - each agent tracks adjacent agents, collective intelligence emerges

Data Quality Agents

quality monitoring agents monitor schema drift, anomalies, nulls, duplicates, outliers

Example: Agent detects 15% null increase in customer_email → alerts adjacent agents → swarm validates pattern → recommends fix

Compliance Agents

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

Example: New field added → compliance swarm checks against 23 regulations → auto-tags PII → updates audit trail

Optimization Agents

optimization agents optimize queries, indexes, partitions, caching strategies

Example: Slow query detected → adjacent agents analyze pattern → recommend index + partition strategy → 10x speedup

Murmuration Coordination

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

Self-Healing

One agent fails → neighbors compensate automatically

Pattern Learning

Swarm learns from every data scientist decision

Distributed Sensing

multiple viewpoints > 1 monolithic system

Biological Evolution

Swarm adapts to your organization's patterns

Autonomously Intelligent

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

Autonomous Learning (No Human Needed)

Hebbian Learning

"Neurons that fire together, wire together" - routes strengthen with use

Long-Term Potentiation

Good paths get stronger (weight × 1.1), bad paths weaken (weight × 0.9)

Synaptic Pruning

Unused pathways automatically removed (like brain development)

Pattern Recognition

Learns from execution history, adapts strategies automatically

Self-Healing

Agent fails → adjacent agents detect → auto-reroute → zero downtime

Human Partnership (You Decide)

Approve/Reject Recommendations

AI suggests, you decide. Every recommendation can be declined.

Override AI Decisions

Not satisfied? Choose alternative, provide justification, move on.

Full Transparency

8-step audit trail shows WHY AI recommended, WHAT impact, WHICH alternatives.

Domain Expertise

You know your data. AI learns patterns. Together = better decisions.

Strategic Direction

AI optimizes routes. You set business goals. Perfect partnership.

Verifiable Code Proof (Not Marketing)

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

self_improving_agent.py

# AUTONOMOUS LEARNING
async def learn_from_execution(
    context, action, result,
    performance_metrics
):
# No human intervention needed
 Pattern recognition
 Strategy adaptation
 Knowledge retention

Location: internal modules

bio_enhanced_router_v3.py

# HEBBIAN LEARNING
if success:
    pathway.weight *= 1.1
    neurotransmitter = DOPAMINE
else:
    pathway.weight *= 0.9
 Long-term potentiation
 Neurotransmitter rewards

Location: internal modules

Test Autonomous Learning Yourself:

# Run same query 10 times, watch latency improve
$ for i in {1..10}; do
    curl http://localhost/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

Read Full Technical Documentation

Cloud Vendors

• Static rules (manual tuning)
• No learning from execution
• No biological optimization
• Manual performance tuning required

cloud-only AI

• Black box learning (no transparency)
• Auto-applies changes (no human control)
• No biological principles
• Cloud only (no local learning)

Pauhu

• Autonomous learning (Hebbian, synaptic)
• Human partnership (you decide)
• Biological optimization (rule-based)
• 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

Public Procurement Demo

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

Try Live Demo →

Local Deployment Demo

Download small, run locally, zero cloud. Full catalog + multiple specialized agents on your laptop.

Coming Soon

Rule-Based Governance Simulator

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

Coming Soon

Request Custom Demo for Your Data

Ready to Break Free from cloud vendors?

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

Contact Sales Try Demo First

compact

Full deployment size

100+

Languages worldwide

0

Cloud dependencies

Stop Fighting Cloud Vendor Lock-In