Platform Features and Capabilities

Runs anywhere—from rugged edge appliances to air‑gapped clusters and major clouds—via secure, container‑native orchestration.

• Adaptive Resource Allocation & Real-Time Autoscaling
• Flexible Compute (GPU/CPU) & GPU Scheduling
• Automated Parallelism with Dask & Multi-Node Coordination
• Air-Gapped Install & DIL Connectivity Support
• Fault-Tolerant Execution & High-Throughput Pipelines
• Hyperscale Cloud Support & Kubernetes Integration

Axonis delivers enterprise-grade scalability through adaptive resource allocation, real-time autoscaling, and flexible GPU/CPU compute scheduling with automated Dask parallelism across multi-node clusters. The platform ensures reliable operations in challenging environments with air-gapped installations, DIL (Denied, Intermittant and Limited) connectivity support, and fault-tolerant execution for high-throughput pipelines. Built for hyperscale cloud deployments, Axonis seamlessly integrates with Kubernetes to provide robust, scalable infrastructure for mission-critical workloads.

Enforces least‑privilege, mutual TLS, and fine‑grained ABAC/RBAC across every microservice and federated peer.

• Encryption at Rest (AES-256) & End-to-End Encryption
• Hardware Security Integration (HSMs, TPM, Intel SGX)
• Multi-Factor Authentication (MFA) & Single Sign-On (SSO)
• IronBank Container Images & STIG Compliance
• Network Threat Intelligence (NTI) Integration
• Zero Trust Architecture (ZTA)

Axonis has comprehensive enterprise security including AES-256 encryption at rest, end-to-end encryption, and hardware security integration with HSMs, TPM, and Intel SGX. The platform supports multi-factor authentication, single sign-on, STIG compliance, and IronBank container images for defense-grade deployments. Built on Zero Trust Architecture, Axonis enforces least-privilege access, mutual TLS, and fine-grained ABAC/RBAC across every microservice and federated peer.

Seamlessly integrate with major SIEM platforms through open APIs and modular architecture, enabling real-time threat detection and rapid AI model deployment without infrastructure changes.

• SIEM Integration (Splunk, ELK, Sentinel)
• Real-time threat detection and automated response
• Add models/connectors without infrastructure changes
• Open APIs and modular architecture
• Pre-built connectors for security platforms
• Scalable log ingestion and flexible deployment

Axonis seamlessly integrates with leading SIEM platforms like Splunk, ELK, and Sentinel, streaming logs, metrics, and security alerts directly into your existing security infrastructure. The platform’s modular architecture and open APIs enable rapid deployment of new models, connectors, and tools without requiring core infrastructure modifications. This flexible design supports continuous innovation while maintaining compatibility with your current security operations.

Automated failover, offline caching, and resumable updates keep AI services running in disconnected or degraded networks.

• Auto-Dependency Resolution & Resource Optimization
• CLI & REST API Integration
• Consistent Environment Management
• Data Management & Notebook Integration
• Python & ML Stack Support
• Cross-Platform Compatibility

Axonis provides a comprehensive development environment with Python 3.8+, scikit-learn, XGBoost, TensorFlow, PyTorch, and Jupyter notebook integration for data scientists. The platform automatically resolves library conflicts, maintains consistent container environments across nodes, and offers both CLI and REST API access for programmatic control. Built-in automated failover, offline caching, and resumable updates ensure AI services remain operational even in disconnected or degraded network conditions.

Schema‑on‑read ingestion, high‑speed connectors, and unified catalog with cryptographic hashing for integrity.

• Enterprise Data Sources
• Specialized Data Processing
• Industry-Specific Compliance
• IoT & Real-Time Integration
• Security & Operations
• Distributed Architecture

Axonis supports comprehensive data integration across cloud warehouses (Snowflake, BigQuery, Redshift), relational and NoSQL databases, along with specialized processing for documents, geospatial data, IoT sensors, and streaming analytics. It features in-namespace execution where pipelines run locally with the data using containerized tasks, while maintaining global coordination through its own secure pipeline engine that avoids external DAG tools. Security and privacy are ensured through role-aware orchestration with ABAC controls, minimal metadata exchange that only shares partial statistics, and flexible workflow definition via both no-code UI and programmatic APIs.

Attribute tagging, lineage, retention rules, and compliance workflows that satisfy HIPAA, GDPR, and DoD CUI.

• Access Control & Security
• Data Classification & Filtering
• Model Management & Monitoring
• Audit & Compliance
• Policy Enforcement & Governance
• Integration & Observability

Axonis provides comprehensive governance through attribute-based access control (ABAC) that enforces role-based permissions on data transformations, model deployments, and policy enforcement, while automatically classifying data and applying appropriate security measures. Advanced monitoring capabilities include drift detection with automatic retraining triggers, diff-based audits that track minimal parameter changes, and end-to-end lineage tracking that links every transformation and deployment for compliance purposes. The system ensures seamless policy enforcement with real-time alerts via Slack and email, version tagging for model rollbacks, and compliance workflows that satisfy HIPAA, GDPR, and DoD CUI requirements across distributed environments.

Unified metrics, traces, and logs with alerting and SLO dashboards for model & data pipelines.

• Real-Time Monitoring & Alerts
• Live Dashboard & Metrics
• Data Lineage & Provenance
• Performance & Execution Logging
• Security & Anomaly Detection
• SIEM Integration & Analytics

Axonis delivers comprehensive real-time monitoring through automatic charts and metrics that track training progress, accuracy, and resource usage, while live progress indicators and workflow status boards keep teams informed of pipeline completion status. All pipeline actions are logged with detailed execution information including start/end times, resource usage, and user identities, creating compliance-ready audit trails that simplify regulatory reporting. A unified log index stores every transformation, training run, and aggregator merge event with timestamps, while real-time alerts notify stakeholders via Slack or email when failures or anomalies occur, ensuring continuous oversight and governance across all distributed nodes.

Curated foundation models plus SHAP, LIME, Grad‑CAM and dashboards for transparent AI.

• Federated LLM Collaboration
• Parameter-Efficient Fine-Tuning (PEFT)
• Model Explainability & Interpretability
• Secure Model Handling & DRM
• Foundation Model Storage & Versioning
• Bias & Fairness Audits

Axonis enables federated large language (LLM) model collaboration through parameter-efficient fine-tuning (PEFT) techniques like LoRA injection and adapter modules, which freeze main LLM weights while allowing only small components to update, drastically reducing GPU/CPU demands and enabling faster training cycles even on modest hardware. Each node can contribute domain-specific knowledge from healthcare, finance, or government sectors while maintaining secure model handling through classification tags and encrypted gradient exchange to protect sensitive data. The system supports seamless integration of popular models like GPT-2, BERT, Bloom, and LLaMA, with final distillation capabilities that merge contributions from multiple sites into a unified model for optional shared deployment while preserving tiered access controls for IP protection.

Secure aggregation using SMPC & HE so only encrypted updates travel—never raw data.

• Federated Model Training & Execution
• Privacy-Preserving Technologies (DP & HE)
• Multi-Framework Support (TensorFlow, PyTorch, scikit-learn)
• Secure Delta Exchange & Aggregations
• Local Efficiency & Global Merging
• Comprehensive Logging & Policy Controls

Axonis enables federated model training where each node trains or refines models locally using supported frameworks like TensorFlow, PyTorch, scikit-learn, and XGBoost, while the aggregator merges them into a global version through secure delta exchange of only model weights and summary statistics. The platform supports incremental updates allowing nodes to retrain and push fresh results at any time, with weighted aggregations based on data volume or quality, and policy overrides to exclude quarantined or out-of-date nodes from the global model. Comprehensive logging tracks all merge events with timestamps and node involvement, while advanced features include transfer learning, vertical federated learning for cross-domain data unification, and automatic scheduling for deep learning across local or multi-node HPC environments.

Push‑down SQL, vector ops, and preprocessing pipelines executed locally, exchanging only minimal statistics.

• Federated Feature Engineering & Distributed Compute
• Multi-Modal Data Support (Tabular, Image, Text & NLP)
• Built-In Data Operations & Transformations
• Privacy-Preserving Processing (Minimal Metadata Sharing)
• Scalable Infrastructure (Dask, Lazy Evaluation, Fault Tolerance)
• Advanced Analytics (PCA, FFT, Policy-Driven Filters)

Axonis offers comprehensive federated feature engineering capabilities through push-down SQL, vector operations, and preprocessing pipelines that execute locally while exchanging only minimal statistics for privacy preservation. The platform provides a rich library of built-in data operations and transformations for tabular, text, and image data, including cleaning operations, encoding methods, image augmentations, and advanced NLP processing with automatic PII removal. Powered by Dask for distributed computing, the system enables scalable data processing with fault tolerance, lazy evaluation for performance optimization, and policy-driven filters that automatically exclude sensitive data from global statistics sharing.

Drag‑and‑drop pipelines, shared‑kernel notebooks, prompt playgrounds, and approval workflows.

• Studio Developer Interface & Experimentation
• Multi-User Project Collaboration
• Python & No-Code AI Model Support
• Python Version Management (3.8, 3.10)
• REST API for Model Serving & Data Access
• WebSocket & gRPC API Support

Axonis serves as a comprehensive developer interface and experimentation platform, featuring drag-and-drop pipelines, shared-kernel notebooks, prompt playgrounds, and approval workflows for streamlined AI development. The platform supports multi-user project collaboration with flexible Python version management (3.8 and 3.10) and custom library integration. It offers both no-code AI models and traditional Python development capabilities, accessible through REST APIs, WebSocket, and gRPC interfaces for seamless model serving and data access.

Versioned registry, CI/CD promotion, canary rollout, drift detection, and automated retraining.

• Federated Model Serving & Real-Time Inference
• Model Deployment & Integration (Seldon, MLFlow, Enterprise AI)
• Model Space Storage & Versioning (Gitea-based)
• Model Drift Detection & Retraining Triggers
• Secure Encrypted Model Deployments
• Advanced Model Observability & Grad-CAM Analysis

Axonis enables comprehensive model lifecycle management through scalable local training with aggregator merges, integrated logging and alerts for full observability. It features a versioned registry with CI/CD promotion capabilities, canary rollout support, drift detection, and automated retraining to ensure models remain accurate and up-to-date. Additional capabilities include federated serving, secure encrypted deployments, enterprise AI pipeline integration, and advanced analysis tools like Grad-CAM for model interpretability.

Seamlessly orchestrates horizontal, vertical, and transfer learning across heterogeneous schemas.

• Federated Feature Engineering & AI Workflows
• Federated Transfer Learning (FTL)
• Horizontal Federated Learning (HFL)
• Secure Cross-Domain Data Sharing
• Secure Multi-Party Computation (SMPC)
• Vertical Federated Learning (VFL)

Axonis provides comprehensive federated learning capabilities through its core engine that orchestrates data transformations and model training across distributed nodes without moving raw data. The platform supports multiple federated learning approaches including horizontal, vertical, and transfer learning methodologies, along with secure multi-party computation and cross-domain data sharing. This seamless orchestration enables organizations to collaborate on AI workflows across heterogeneous schemas while maintaining data privacy and security through advanced cryptographic techniques.

One‑click templates and SDK for privacy‑preserving training rounds with GPU scheduling.

• Automated Model Selection
• Custom, Distributed Workflow Orchestration
• Hyperparameter Tuning
• Model Workflow Creation
• Multi-Federate Model Execution
• Cross-Platform Pipeline Management

Axonis provides comprehensive model management capabilities including automated model selection, hyperparameter tuning, and multi-federate model execution across distributed environments. The platform features custom, distributed workflow orchestration where each site runs localized pipelines inside its Kubernetes namespace, exchanging only minimal metadata for global coordination. Users can leverage one-click templates and SDK for privacy-preserving training rounds with GPU scheduling, streamlining the entire model workflow creation and execution process.

Combines text, vision, and sensor embeddings with ABAC‑enforced retrieval‑augmented generation.

• Chatbot Integration (Aether, RAG)
• Data Preview & Sampling
• Multi-Federate Data Exploration
• Interactive Data Visualization
• Federated Query Processing
• Cross-Site Data Discover

Axonis offers offers advanced data exploration capabilities through secure chatbot integration that enables RAG workflows using local context with attribute-based access control. The platform seamlessly integrates structured, unstructured, image, and geospatial data across organizational silos, providing comprehensive data preview and sampling functionality. This multi-federate approach combines text, vision, and sensor embeddings with ABAC-enforced retrieval-augmented generation to deliver intelligent, privacy-preserving data discovery and analysis.

End‑to‑end test harness for privacy attacks, bias, explainability, and performance regressions.

• Federated Model Validation
• Model Optimization
• Cross-Validation & Performance Metrics
• Hyperparameter Tuning
• Model Ensemble Methods
• Automated Model Selection

Axonis provides comprehensive federated model validation and optimization capabilities that enable decentralized evaluation and explainability without aggregating sensitive data. The platform includes an end-to-end test harness for assessing privacy attacks, bias detection, explainability metrics, and performance regressions across distributed nodes. This federated MLOps approach ensures model quality and transparency while maintaining data privacy throughout the validation and optimization process.