Trust Architecture for Machine Intelligence.
Built by Engineers Who Deploy Models in Production.

bladestack.io provides technical advisory for the AI era. We operate without theoretical frameworks or black box excuses. We are engineers who embed with your data science teams to build ISO 42001 and NIST AI RMF compliance structures that survive the reality of production inference.

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  5. Artificial Intelligence | bladestack.io | Artificial Intelligence, ISO 42001 & NIST AI RMF Advisory
Why bladestack.io?

We Engineer Weights. Not Just Words.

Governing a deterministic SQL database differs entirely from governing a stochastic Large Language Model. The compliance industry struggles with probability, but we run towards the math. We understand that effective governance requires managing confidence intervals and entropy. We bridge the gap between rigid ISO 42001 controls and the fluid nature of generative AI.

We sit down with your ML Engineers to review training data lineage and validation sets. When your team asks how to apply access control to a vector embedding, we do not quote a standard. We architect the solution. We treat compliance as a function of your inference pipeline.

Differentiators

Same Standards. Different Compute.

Advisory-only. Model-aware. Cloud-Agnostic. Here is why the AI ecosystem trusts us with their weights and biases.

Engineers Who Ship Models

Ask your current AI governance advisor to explain the difference between model drift and data drift, then ask them to implement a detection pipeline for both. We build monitoring systems that catch concept drift before it manifests as fairness violations. We configure feature stores with lineage tracking that satisfies NIST AI RMF's GOVERN function requirements. We write the Terraform modules that deploy model registries with immutable versioning. Your AI governance partner should understand PyTorch checkpoints as fluently as they understand regulatory checkpoints.

Governance as Architecture, Not Documentation

Generic ISO knowledge falls short in the cloud. We possess deep expertise in the cloud-specific extensions. We understand the shared responsibility model at a granular level. We know how to implement the specific virtual machine hardening required by ISO 27017 and the customer-data deletion routines mandated by ISO 27018. We translate these standards into AWS Config rules, Azure Policies, and GCP Organization constraints.

Framework Fluency Across the Stack

ISO 42001 certification. NIST AI RMF implementation. EU AI Act high-risk system requirements. SR 11-7 model risk management for financial services. We navigate multiple frameworks simultaneously because modern AI deployments face overlapping regulatory demands. Your recommendation engine might need ISO 42001 for international customers, NIST AI RMF for federal contracts, and EU AI Act compliance for European markets. We build governance architectures that satisfy all three without tripling your operational burden.

Production-Grade, Not Proof-of-Concept

Governance that works in a Jupyter notebook is not governance. We build for scale. Model monitoring that handles thousands of inferences per second. Audit logging that does not introduce latency into real-time decisioning. Explainability that works on your actual production models, not simplified versions built for demonstration purposes. When your AI system processes a million predictions daily, governance controls must operate at that scale without becoming the bottleneck.

Custom Implementation, Zero Boilerplate

Every AI system has different risk profiles, different deployment patterns, different organizational contexts. A computer vision system for quality inspection has fundamentally different governance requirements than a large language model powering customer service. We design governance architectures specific to your models, your data pipelines, your deployment infrastructure. The resulting documentation reflects how your AI systems actually operate, not how a generic AI system might theoretically function.

We Stay Through Certification

Governance frameworks require ongoing operational commitment. ISO 42001 certification audits. NIST AI RMF continuous monitoring. EU AI Act conformity assessments. We do not hand you a governance design and disappear. We remain engaged through certification processes, audit preparation, and the inevitable questions that surface when assessors examine your AI systems in detail. The engagement ends when you have the certifications and operational capabilities you need, not when our deliverables are complete.

Differentiators

Same Industry. Different Architecture.

Advisory-only. Engineer-led. Cloud-native. Operationally focused. Here's what those words actually mean.

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AI · Advisory Service Components

For organizations building the AI Management System (AIMS) foundation.

Effective AI governance requires more than a policy document. It demands a structural commitment to responsible engineering. We build the entire ISO 42001 AIMS architecture by mapping the NIST AI RMF functions directly to your MLOps pipeline. We translate regulatory requirements into engineering tasks your data scientists can actually execute.

  • AI Governance Readiness Assessment For organizations evaluating their AI governance posture. A technical deep-dive into your ML infrastructure, model inventory, data pipelines, and deployment patterns. We map your current state against ISO 42001 requirements, NIST AI RMF functions, and EU AI Act obligations. You receive a comprehensive roadmap showing exactly what architectural changes, tooling deployments, and process implementations separate your current state from certification readiness.
  • Phase 0: AI Discovery Fast Track For organizations committed to the full governance journey. Accelerated discovery that bypasses the standalone assessment and flows directly into implementation. We produce foundational artifacts including your AI system inventory, risk classification matrix, data lineage documentation, and governance architecture blueprint. Everything discovered becomes input for the build phase. No assessment report gathering dust while you decide next steps.
  • AI Governance Advisory The core engagement. We design and document your complete AI governance program. AI Management System documentation for ISO 42001. Risk management artifacts for NIST AI RMF. Technical documentation for EU AI Act conformity. Model cards, datasheets, impact assessments, and the governance architecture that connects them. We embed with your ML platform team, work through implementation challenges together, and ensure governance designs translate into operational reality.
  • Sentinel: Assessment & Audit Support We stay until certification is achieved. Evidence coordination for ISO 42001 audits. Interview preparation for NIST AI RMF assessments. Technical demonstration support for EU AI Act conformity reviews. Real-time response to assessor findings. The engagement ends when you have the certifications you need, not when documentation delivery is complete.

Every deliverable reflects your actual AI infrastructure. Your models. Your pipelines. Your deployment patterns. Documentation that your ML engineers recognize as accurate descriptions of systems they built and operate daily. When auditors review our packages, technical claims trace to implementation evidence, governance controls trace to infrastructure configurations, and interviews validate rather than contradict written artifacts.

Includes:

  • AI Governance Readiness Assessment
  • Phase 0 (Fast Track) Discovery
  • AI Management System Documentation (ISO 42001)
  • NIST AI RMF Artifacts (GOVERN, MAP, MEASURE, MANAGE)
  • EU AI Act Technical Documentation
  • Model Cards & Datasheets
  • Algorithmic Impact Assessments
  • Sentinel Assessment & Audit Support
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AI · Enjinia Blade Division

For organizations that need ML platform engineering, not just governance consulting

Governance documentation without implementation capability is a recipe for audit failures. Your policies say you track model lineage, but your ML platform has no lineage tracking system. Your risk assessment identifies bias detection requirements, but no bias detection pipeline exists. Our Enjinia Blade Division provides on-demand ML platform engineering through Bitstream Merc engagements. Engineers who understand both PyTorch and ISO 42001. Architects who can design a feature store and explain why it satisfies NIST AI RMF MEASURE function requirements.

  • MLOps Governance Implementation Hands-on engineering to build governance-aware ML infrastructure. Model registry deployment with immutable versioning. Feature stores with lineage tracking. Experiment tracking systems configured for audit requirements. Inference pipeline instrumentation for continuous monitoring. We build the platform capabilities that make governance operationally possible.
  • Model Registry & Lifecycle Engineering Purpose-built model management infrastructure. Version control for model artifacts, training data references, and hyperparameters. Approval workflows that enforce human oversight requirements. Deployment gates that validate governance checkpoints before production promotion. Model retirement procedures that satisfy data retention and deletion requirements.
  • AI Observability Stack Deployment Monitoring infrastructure for production AI systems. Model drift detection pipelines. Performance degradation alerting. Fairness metric dashboards. Explainability logging. Inference audit trails. The observability capabilities that transform AI governance from periodic assessment into continuous validation.
  • Bias Detection & Mitigation Engineering Technical implementation of fairness controls. Bias detection integrated into training pipelines. Fairness constraint enforcement during model optimization. Post-deployment monitoring for demographic performance disparities. Remediation workflows when bias is detected. We build the technical systems that make fairness measurable and actionable.

Resources are not junior consultants reading MLOps documentation for the first time. They are engineers who have debugged gradient explosions at 2 AM, optimized inference latency for real-time applications, and understand why your team architected the ML platform the way they did. Engagements are scoped to the work, whether that is a two-week registry deployment or ongoing platform architecture support.

Includes:

  • MLOps Governance Implementation
  • Model Registry Deployment & Configuration
  • Feature Store Architecture & Deployment
  • Experiment Tracking System Integration
  • AI Observability Stack Deployment
  • Bias Detection Pipeline Engineering
  • Explainability Infrastructure Implementation
  • ML Pipeline Security Hardening
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AI · bladeAI Managed Services

For organizations that want AI governance operated, not just implemented

Certification is a milestone, not a destination. What comes after, continuous model monitoring, bias drift detection, incident response, recertification preparation, is an operational commitment that never stops. bladeAI is our managed platform for ongoing AI governance operations, run by the team that already knows your architecture because we designed the governance program.

  • bladeAI The complete managed AI governance platform. Includes Platform Build (MLOps governance infrastructure, monitoring stack, model registry), RONIN continuous model monitoring, and AI risk operations capability. Full-stack governance operations from the team that built your program.
  • GENJI · Continuous Monitoring (ConMon) Operational capability for organizations that manage their own ML platform but need ongoing governance expertise. Model drift detection and alerting. Fairness metric monitoring. Incident investigation and response. Evidence generation for ongoing compliance. Audit preparation and support.
  • HANZO · 24/7 Security Operations (SecOps) Active defense for your AI surface area. We monitor for prompt injection attacks, model inversion attempts, and membership inference attacks. We update your system prompts and guardrails in response to new jailbreak techniques to keep your models secure against an evolving threat landscape.
  • Drift & Bias Telemetry Automated tracking of statistical properties. We configure the tooling to detect when your production data diverges from your training data. We alert you to potential fairness issues or performance degradation before they become compliance failures.

You built a governance program to deploy AI responsibly. bladeAI transforms ongoing compliance from a staffing problem into an operational service. Your ML team stays focused on model development while we keep the governance program running, the certifications valid, and the regulators satisfied.

Includes:

  • Platform Build & Deployment
  • HANZO (24/7 Security Operations)
  • GENJI (Continuous Monitoring)
  • Annual Assessment Support
  • Agency Reporting & Communication
  • POA&M Lifecycle Management
  • SRE Infrastructure Operations
  • Reauthorization Preparation
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AI · Sentience Scaling

For organizations preparing for agentic workflows and AGI-adjacent complexity.

The future of AI involves autonomous agents rather than just chatbots. Sentience Scaling is our service for organizations deploying agentic workflows where AI takes actions. When your AI starts calling APIs, executing code, and making decisions, you need a governance framework that scales with autonomy.

  • Agentic Governance Frameworks Defining bounds for autonomous agents. We map the permission structures and the human-in-the-loop break-glass mechanisms. We engineer the constraints that prevent agents from hallucinating a destructive API call or exceeding their authorization boundary.
  • Multi-Modal Risk Architecture Governance for text, image, audio, and video. As models become multi-modal, the risk surface expands. We update your AIMS and technical controls to handle the specific risks of deepfakes, copyright ingress in image generation, and voice cloning security.
  • Cross-Jurisdiction Alignment Mapping your AI stack to the EU AI Act, the White House Executive Order, Canada's AIDA, and emerging state laws. We create a unified control framework that allows you to deploy globally without rebuilding your compliance program for every border you cross.
  • Trust Repository Development Building the public-facing trust center for your AI. We engineer the transparency artifacts, system cards, and model cards that allow your customers to trust your stochastic systems. We turn compliance into a competitive advantage by making your governance visible.
  • Validation Support We prep your team for Technical Exchange Meetings and help you respond to JVT comments with technical precision, not churn. When CAO or NIC representatives raise connectivity concerns, we address them with implementation specifics.

The shift from generative text to autonomous action is an architectural transformation. Organizations that build compliance programs around static policies will fail when agents start moving. Organizations that build compliance programs around engineering constraints are ready for the future.

Includes:

  • Agentic Workflow Governance
  • Human-in-the-Loop Architecture
  • Multi-Modal Risk Assessment
  • Global Regulatory Alignment
  • Model Card & System Card Development
  • Trust Center Engineering
  • Automated Transparency Reporting
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AI · APEX Global AI Services

For organizations expanding their AI footprint into global regulatory markets.

AI has no borders, but laws do. The EU AI Act, the US Executive Order, Canada's AIDA, and China's generative AI measures create a minefield of conflicting requirements. APEX (Alignment & Policy EXpansion) is our service for organizations deploying models across jurisdictions. We map your AI architecture to the global regulatory fabric to ensure that a single model can serve the world without violating local sovereignty.

  • EU AI Act Conformity High-risk categorization and conformity assessment. We guide you through the tiered requirements of the EU AI Act. From prohibited practices to high-risk obligations, we build the technical documentation and quality management systems required for CE marking of AI systems.
  • Sovereignty Architecture Deploying models in regions with strict data residency requirements. We help architect federated learning approaches or localized inference nodes. You use your global model weights while keeping sensitive training or inference data within national borders.
  • High-Impact Vertical Overlays Healthcare (FDA AI/ML), Finance (SR 11-7), and Defense. We layer the specific, stringent requirements of these verticals onto your foundational AIMS. We handle the delta analysis and implementation to take a general-purpose model and certify it for critical use cases.
  • Automated Transparency Dynamic disclosure engineering. Different jurisdictions require different disclosures. We engineer the systems to dynamically generate the required watermarking, user notifications, and public registrations based on the user's geolocation.

Regulatory divergence is the biggest threat to global AI scalability. We treat regulation as a system variable. We engineer your compliance posture to adapt to the jurisdiction of the user. One model, global compliance.

  • EU AI Act Gap Analysis & Conformity
  • Global Regulatory Mapping
  • Sovereign Data Architecture
  • Unified AI Control Framework
  • Automated Disclosure Systems
  • High-Risk System Registration
Our Approach

How We Build Trustworthy AI.

Most firms treat AI governance like a documentation project. Interview stakeholders. Draft policies. Create an ethics board. Hope the AI systems behave. We treat AI governance as an infrastructure engineering challenge, because it is. Our four-phase approach builds governance into your ML platform architecture, where model versioning, bias detection, and explainability become structural properties of how your AI systems operate.

00.

PHASE 0: Discovery & Architecture Review

For organizations committed to the full governance journey

Traditional assessments produce reports that describe problems without solving them. We skip that. Phase 0 is an intensive architecture deep-dive that flows directly into implementation. We map your ML infrastructure, inventory your deployed models, trace your data pipelines, and assess your current governance capabilities against framework requirements.

Phase 0 produces foundational artifacts, not a static report:

  • AI System Inventory with risk classifications
  • Data Lineage Documentation
  • Model Lifecycle State Assessment
  • Governance Architecture Blueprint
  • Framework Gap Analysis (ISO 42001 / NIST AI RMF / EU AI Act)
  • Remediation Roadmap with implementation priorities

Everything discovered flows directly into Phase 2. No assessment gathering dust. We are already building.

01.

AI · AI Governance Readiness Assessment

For organizations evaluating the AI governance journey

Not ready to commit to the full program? Start here. Our readiness assessment is a technical deep-dive that tells you exactly where you stand and exactly what it will take to achieve compliance.

We do not spend cycles reviewing every theoretical AI risk when a subset will determine your success or failure. We focus on the controls that determine outcomes: model inventory requirements, lifecycle management capabilities, monitoring infrastructure, and the architectural decisions that become expensive to change later.

  • Comprehensive Technical Roadmap
  • Framework-by-Framework Readiness Status
  • Infrastructure Gap Analysis
  • Risk-Prioritized Remediation Recommendations
  • Realistic Timeline and Resource Projections

02.

AI · Advisory & Governance Build & Implementation

Engineering your AI governance program

Most advisors identify gaps and leave you to figure out implementation. We design and build the complete governance program, then stay embedded with your team until the architecture is operational.

We write AI Management System documentation with technical precision, not compliance generalities. We design model registries that enforce versioning requirements through architecture, not policy statements. We configure monitoring pipelines that generate compliance evidence automatically. We build governance infrastructure that your ML engineers operate as part of their standard workflows.

And when ISO 42001 auditors or EU AI Act assessors examine your systems, the governance controls they evaluate are the same controls your team uses daily.

  • Complete AI Management System (AIMS) Documentation
  • Model Registry Architecture & Configuration
  • Bias Detection Pipeline Design
  • Explainability Infrastructure Specifications
  • Monitoring Dashboard Requirements
  • Evidence Automation Pipelines

When technical questions arise at midnight before a certification deadline, we answer them directly, with implementation specifics, not a knowledge base article.

Every word written for your architecture. Documentation that your ML team recognizes as accurate.

03.

AI · Sentinel: Assessment & Audit Defense

We stay until you're certified.

The engagement does not end when documentation is complete. Sentinel is your hardened defensive position. We remain engaged from audit kickoff through certification, standing between your engineering team and the assessment process.

Certification is where AI governance programs stall. Auditors request evidence that should have been obvious. Assessors ask questions that reveal assumptions you did not know you made. Regulators push back on risk classifications that seemed clear six months ago.

Assessment failures follow patterns. Evidence gaps. Documentation inconsistencies. Interview misalignment. We engineer governance programs to eliminate these failure modes before they surface.

When findings emerge, we do not just log them. We triage in real-time, coordinate responses, and get your team the technical guidance to close gaps fast. Your engineers focus on fixes. We handle the documentation, the communication, and the strategy.

  • Evidence Package Preparation & Organization
  • Interview Preparation & Technical Coaching
  • Auditor Coordination & Clarification
  • Real-Time Finding Response
  • Regulatory Communication Management

Certification is the finish line, not documentation delivery. We stay engaged through the full assessment cycle.

AI · Governed.

The certification is the starting line, not the finish

You are certified. Your AI systems operate within a documented governance framework. The work it took to get here, the architecture, the implementation, the documentation, the assessment, it paid off.

AI governance does not stop at certification. Continuous monitoring, model drift response, bias incident management, and recertification preparation are now part of your operational reality.

Whether you handle that internally or want a team that already knows your architecture, the path forward is yours.

  • bladeAI Managed Services Full-stack AI governance operations from the team that designed your program
  • Engineering Support Enjinia Blade resources for future implementation work
  • Advisory Services Ongoing access to architecture guidance for future decisions
  • Framework APEX Additional certifications, new frameworks, expanded AI portfolios. When your governance program needs to grow, we engineer the path
  • Sentience Scaling Preparing your architecture for agentic workflows and automated decision-making.

Ready to Engineer Trust Into Your AI?

Skip the policy theater. Schedule a consultation with ML platform architects who understand both PyTorch and ISO 42001. We will assess your current infrastructure, map your framework obligations, and give you a realistic path to certification. No pressure. Just engineering expertise.