Case Study: Sovereign AI Stack Integration

This example demonstrates the Pragmatic AI Labs Sovereign AI Stack integration, showing how aprender fits into the broader ecosystem.

Overview

The Sovereign AI Stack is a collection of pure Rust tools for ML workflows:

alimentar → aprender → pacha → realizar
    ↓           ↓          ↓         ↓
             presentar (WASM viz)
                   ↓
             batuta (orchestration)

Stack Components

Design Principles

• Pure Rust: Zero cloud dependencies
• Format Independence: Each tool has its own binary format
• Toyota Way: Jidoka, Muda elimination, Kaizen
• Auditability: Hash-chain provenance for tamper-evident audit trails

Real-Time Audit & Explainability

The entire Sovereign AI Stack now includes unified audit trails with hash-chain provenance:

Stack-Wide Integration

Hash Chain Provenance

Every operation across the stack generates cryptographically-linked audit entries:

use aprender::explainability::{HashChainCollector, Explainable};

// Create audit collector for ML predictions
let mut audit = HashChainCollector::new("sovereign-inference-2025");

// Each prediction records its decision path
let (prediction, path) = model.predict_explain(&input)?;
audit.record(path);

// Verify chain integrity (detects tampering)
let verification = audit.verify_chain();
assert!(verification.valid, "Audit chain compromised!");

Toyota Way: 失敗を隠さない (Never Hide Failures)

The audit system embodies the Toyota Way principle of transparency:

1. Jidoka: Quality built into every prediction with mandatory explainability
2. Genchi Genbutsu: Decision paths let you trace exactly why a model decided what it did
3. Shihai wo Kakusanai: Every decision is auditable, nothing is hidden

Running the Example

cargo run --example sovereign_stack

Stack Components in Code

for component in StackComponent::all() {
    println!("{}", component);  // "aprender (to learn)"
    println!("Description: {}", component.description());
    println!("Format: {:?}", component.format());  // Some(".apr")
    println!("Magic: {:?}", component.magic());    // Some([0x41, 0x50, 0x52, 0x4E])
}

Model Lifecycle (Pacha Registry)

Model Stages

assert!(ModelStage::Development.can_transition_to(ModelStage::Staging));
assert!(ModelStage::Staging.can_transition_to(ModelStage::Production));
assert!(!ModelStage::Archived.can_transition_to(ModelStage::Development));

Model Version

let version = ModelVersion::new("1.0.0", [0xAB; 32])
    .with_stage(ModelStage::Production)
    .with_size(5_000_000)
    .with_quality_score(92.5)
    .with_tag("classification")
    .with_tag("iris");

println!("Version: {}", version.version);
println!("Stage: {}", version.stage);
println!("Quality: {:?}", version.quality_score);
println!("Hash: {}...", &version.hash_hex()[..16]);
println!("Production Ready: {}", version.is_production_ready());

Model Derivation (Lineage)

Track model provenance through the DAG:

let derivations = [
    DerivationType::Original,
    DerivationType::FineTune { parent_hash: [0x11; 32], epochs: 10 },
    DerivationType::Distillation { teacher_hash: [0x22; 32], temperature: 3.0 },
    DerivationType::Merge {
        parent_hashes: vec![[0x33; 32], [0x44; 32]],
        method: "TIES".into()
    },
    DerivationType::Quantize {
        parent_hash: [0x11; 32],
        quant_type: QuantizationType::Int8
    },
    DerivationType::Prune { parent_hash: [0x11; 32], sparsity: 0.5 },
];

for deriv in &derivations {
    println!("{}: derived={}, parents={}",
        deriv.type_name(),
        deriv.is_derived(),
        deriv.parent_hashes().len());
}

Quantization Types

Inference Configuration (Realizar)

Configure inference endpoints:

let config = InferenceConfig::new("/models/iris_rf.apr")
    .with_port(9000)
    .with_batch_size(64)
    .with_timeout_ms(50)
    .without_cors();

println!("Predict URL: {}", config.predict_url());
// http://localhost:9000/predict

println!("Batch URL: {}", config.batch_predict_url());
// http://localhost:9000/batch_predict

Health Monitoring

Monitor stack health:

let mut health = StackHealth::new();

health.set_component(
    StackComponent::Aprender,
    ComponentHealth::healthy("0.15.0").with_response_time(5),
);

health.set_component(
    StackComponent::Pacha,
    ComponentHealth::degraded("1.0.0", "high latency").with_response_time(250),
);

health.set_component(
    StackComponent::Presentar,
    ComponentHealth::unhealthy("connection refused"),
);

println!("Overall: {}", health.overall);  // Unhealthy
println!("Operational: {}", health.overall.is_operational());  // false

Health Status Levels

Format Compatibility

let compat = FormatCompatibility::current();

// Check APR version compatibility
println!("APR 1.0: {}", compat.is_apr_compatible(1, 0));  // true
println!("APR 2.0: {}", compat.is_apr_compatible(2, 0));  // false

// Check ALD version compatibility
println!("ALD 1.2: {}", compat.is_ald_compatible(1, 2));  // true
println!("ALD 1.3: {}", compat.is_ald_compatible(1, 3));  // false

Source Code

• Example: examples/sovereign_stack.rs
• Module: src/stack/mod.rs