Why Pauhu?¶

Hybrid intelligence that gets better with every translation. Pauhu is the only platform where AI learns from translation memory and term bases - and improves them automatically.

The Problem with Current Solutions¶

Traditional MT (DeepL, Google Translate)¶

Great AI. Zero memory.

User → Model → Translation

Every translation starts fresh. No learning from corrections. No terminology management. No organizational knowledge retention.

Result: - Same mistakes repeated - Inconsistent terminology - Manual quality checking required - No improvement over time

Traditional CAT Tools (SDL Trados, memoQ)¶

Great memory. Zero AI learning.

User → TM Lookup → Translation

Fixed term bases that require manual maintenance. No AI to extract new terms. Exact matches or nothing.

Result: - Manual term base updates - No fuzzy terminology matching - Limited to historical translations - Expensive human intervention

How Pauhu Works Differently¶

Hybrid intelligence: AI and traditional resources working together.

User → TM + TB + AI + Memory → Translation
       ↓         ↓
    Learning ← Extraction

Bidirectional Semantic Flow¶

graph TB
    subgraph "Your Knowledge"
        TM[Translation Memory<br/>10+ years of translations]
        TB[Term Base<br/>Your approved terminology]
    end

    subgraph "Pauhu AI"
        AI[AI Translation<br/>Real-time accuracy]
        AIM[AI Memory<br/>Learns your style]
        AITB[AI Term Base<br/>Auto-discovers terms]
    end

    TM -->|Teaches| AI
    TB -->|Enforces| AI
    AI -->|Learns| AIM
    AI -->|Extracts| AITB
    AITB -->|Suggests| TB
    AIM -->|Improves| AI

    style AI fill:#002855,stroke:#fff,color:#fff
    style AIM fill:#002855,stroke:#fff,color:#fff
    style AITB fill:#002855,stroke:#fff,color:#fff

This is unique. No other platform connects these systems bidirectionally.

What You Get¶

1. AI Learns From Your History¶

Translation Memory teaches AI context:

# Your TM contains:
"data controller" → "rekisterinpitäjä" (used 500×)

# AI learns this preference automatically
# Next translation of "data controller":
result = pauhu.translate("The data controller shall...")
# → "Rekisterinpitäjän on..."
# ✓ Consistent with your 500 previous uses

Impact: +5% quality improvement from day one.

2. Term Base Enforces Consistency¶

IATE + EuroVoc + Your Terms = 8.4M+ approved translations:

# Automatic term recognition
result = pauhu.translate(
    "GDPR requires encryption of personal data",
    domain="12 Law"
)

# Terms automatically applied:
# "GDPR" → "tietosuoja-asetus" (IATE ⭐⭐⭐⭐)
# "personal data" → "henkilötiedot" (IATE ⭐⭐⭐⭐)
# "encryption" → "salaus" (EuroVoc)

Impact: +10% terminology consistency.

3. AI Discovers New Terms Automatically¶

No manual term base maintenance:

# Upload a document
doc = pauhu.documents.upload("eu-ai-act.pdf")

# AI extracts terms automatically
terms = doc.extract_terms()

# High-confidence terms found:
# "artificial intelligence system" → "tekoälyjärjestelmä" (98% confidence)
# "high-risk AI" → "korkean riskin tekoäly" (95% confidence)
# "conformity assessment" → "vaatimustenmukaisuuden arviointi" (92%)

Impact: 300-500 terms auto-discovered per 100 pages.

4. AI Memory Learns Your Preferences¶

Organization style remembered automatically:

# You correct once:
pauhu.correct(
    was="koneoppimisalgoritmi",
    should_be="koneoppimisen algoritmi",
    reason="Organization style guide"
)

# AI remembers forever
# All future translations use your preference
# Both AI and Translation Memory updated

Impact: +18% quality after 10,000 translations.

Quantified Benefits¶

Real-World Example¶

Finnish Ministry of Justice¶

6-month deployment, 10,000+ translations

Before Pauhu (SDL Trados): - Manual term base updates: 40 hours/month - Terminology consistency: 82% - Average translation time: 450 words/hour - Quality (BLEU score): 0.72

After Pauhu: - Term base updates: Automatic (AI suggests, human approves) - Terminology consistency: 97% - Average translation time: 610 words/hour (+35% faster) - Quality (BLEU score): 0.85 (+18% improvement)

ROI: - Time saved: 320 hours over 6 months - Cost savings: €28,000 (human translation avoided) - Quality improvement: Measurable (+18% BLEU) - Term base growth: 2,500 new terms automatically discovered

Technical Differentiators¶

1. Double Encryption Throughout¶

Quantum-safe (ML-KEM-768) + Client-side (AES-256-GCM)

# All data encrypted twice
pauhu = Pauhu(
    quantum_safe=True,      # Post-quantum cryptography
    client_side=True        # Your keys, your device
)

# We literally cannot read your content
# Even in transit, even at rest, even during processing

Why it matters: EU AI Act Article 10 compliance, GDPR Article 32 requirements, VAHTI ST IV security.

2. Offline-First Architecture¶

695 GB of ONNX models run locally

# Works without internet
pauhu = Pauhu(offline=True)

# Full translation capability
# Full term base access
# Full AI memory
# Air-gapped deployments supported

Why it matters: Classified documents, defense contractors, sensitive government work.

3. Edge Deployment Flexibility¶

Same API, any infrastructure

# Deploy anywhere
pauhu.deploy(
    mode="on-premises",     # Your datacenter
    # OR mode="cloud",      # Your AWS/Azure/GCP
    # OR mode="edge",       # Cloudflare Workers
    jurisdiction="eu"       # Data stays in EU
)

# Same capabilities everywhere
# Same API everywhere
# Your infrastructure, your rules

Why it matters: Data sovereignty, compliance requirements, zero vendor lock-in.

Compliance Built-In¶

EU AI Act¶

• ✅ Article 52 transparency (watermarking, labeling)
• ✅ Article 10 data governance (double encryption)
• ✅ Article 13 transparency (audit logs, explainability)
• ✅ Recital 60 high-risk assessment (accuracy testing)

GDPR¶

• ✅ Article 32 encryption (client-side + quantum-safe)
• ✅ Article 22 automated decision-making (human-in-loop)
• ✅ Article 5 data minimization (no source content stored)
• ✅ Article 44 data transfers (EU jurisdiction enforced)

Industry Standards¶

• ✅ ISO 17100:2015 (translation services)
• ✅ ISO 18587:2017 (post-editing MT output)
• ✅ ISO 27001 (information security)
• ✅ SOC 2 Type II (security controls)

Pricing That Makes Sense¶

Pay for what you use. No hidden costs.

Annual billing: 10× monthly (17% savings)

What's included: - ✅ All features at all tiers - ✅ Double encryption (quantum-safe + client-side) - ✅ Offline mode - ✅ IATE term base (8.4M terms) - ✅ AI Memory and AI Term Base - ✅ EU AI Act compliance - ✅ GDPR compliance - ✅ ISO 17100 compliance

What scales with tier: - Translation volume (requests/day, characters/day) - Translation Memory size (1k → 100k → 1M → Unlimited) - File Hubs (1 → 3 → 10 → Unlimited) - Support SLA (24h → 8h → 4h → 1h)

See detailed pricing →

Start Today¶

# Install Pauhu SDK
pip install pauhu

# Initialize with your API key
from pauhu import Pauhu
client = Pauhu(api_key="pk_...")

# Start translating with hybrid intelligence
result = client.translate(
    text="Your content here",
    target="fi",
    use_memory=True,        # Learn from history
    enforce_terms=True,     # Ensure consistency
    extract_terms=True      # Discover new terminology
)

print(result.translation)
# High quality, consistent, improving over time

Free trial: 14 days, no credit card required

Start Free Trial Read Documentation

Questions?¶

"How is this different from DeepL API + SDL Trados?"¶

Short answer: Integrated vs. separate systems.

Long answer: - DeepL API: AI translation only, no TM integration, no term enforcement - SDL Trados: TM + term base, minimal AI learning - Pauhu: AI learns from TM, auto-discovers terms, continuous improvement loop

You can't replicate Pauhu's bidirectional flow by combining separate tools.

"Can I import my existing Translation Memory and Term Base?"¶

Yes. Full import support:

# Import Translation Memory (TMX standard)
project.tm.import_file("your-tm.tmx")

# Import Term Base (TBX standard)
project.terms.import_file("your-termbase.tbx")

# Import CSV glossaries
project.terms.import_csv("your-glossary.csv")

# Pauhu AI immediately learns from your historical data

"What happens to my AI Memory if I cancel?"¶

You keep it. Full export:

# Export everything
project.export(
    translation_memory="your-tm-export.tmx",
    term_base="your-tb-export.tbx",
    ai_memory="your-ai-memory.json",
    ai_term_base="your-ai-terms.tbx"
)

# No vendor lock-in
# All data portable
# Standard formats (TMX, TBX, JSON)

"Can Pauhu work offline for classified documents?"¶

Yes. Full offline capability:

# Download all models (695 GB)
pauhu download-models --all

# Deploy on air-gapped network
pauhu deploy --mode offline --jurisdiction eu

# Full functionality:
# - AI translation (ONNX models run locally)
# - Translation Memory (local D1 database)
# - Term Base (local IATE/EuroVoc data)
# - AI Memory (local encrypted storage)

Use case: Defense contractors, classified government work, sensitive R&D.

Further Reading¶

• Capabilities Overview - See the bidirectional flow diagram
• Translation Memory - How AI learns from history
• Term Base - IATE, EuroVoc, custom glossaries
• AI Memory - Context-aware learning
• AI Term Base - Automatic term extraction
• Double Encryption - Quantum-safe + client-side
• Offline-First - Air-gapped deployments
• Pricing - Transparent, predictable costs

Pauhu. Hybrid intelligence that improves with every translation.

Est. 1989 · "Meaning persists"