Enterprise AI Orchestration Platform | Features
The secure enterprise AI orchestration platform
With Kamiwaza, you don’t have to wait for your data to be ready
Kamiwaza solves the enterprise AI production gap by giving agents secure access to data where it already lives, with an ontology layer that makes that data interpretable and ready to use.
AI Orchestration That Turns Your Distributed Chaos Into a Competitive Advantage
Financial records. Technical manuals. Diagrams and presentations. Even videos and handwritten notes. Imagine being able to use AI on all of the structured (and unstructured) data in your enterprise.
Most AI solutions can only use what’s been uploaded to the cloud. Kamiwaza lets you make fast, accountable decisions on data that can’t be moved. And that changes the way you do business.
Distributed Data Engine
Send AI agents to securely query and process data from any database, legacy system, or edge location, even behind firewalls. Our Distributed Data Engine connects to sources across silos and locations, making data practical for AI without migration. You activate your information where it resides.
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Inference Mesh
Run inference across many different compute types and sources on a single platform. Inference Mesh is a silicon-agnostic AI workload orchestrator that eliminates hardware vendor lock-in and scales AI workloads across any silicon (GPU or CPU). No manual tuning needed.
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Security and Compliance
Overcome security and data sovereignty challenges with AI that complies with policies and regulations. Contextual authorization and Relationship-Based Access Controls (ReBAC) make it possible to understand not just who is accessing your data, but why, when, and how, with a comprehensive audit trail.
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Context Manager and Ontology
Ensure that your AI always acts on the source of truth right now, not outdated snapshots. As your data changes, new documents are uploaded, and policies are revised, our Context Manager produces a living ontology that automatically discovers and maps relationships to create a dynamic knowledge layer.
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Apps and Tools
Eliminate the months of development that usually come with deploying AI. Kamiwaza gives you fast and easy ways to run AI solutions and agents inside your firewall. This frees your developers to focus on more strategic projects.
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Kamiwaza Product Features
Connect to All Your Data Sources
Stop moving data. Start running AI where your data lives. With Kamiwaza's distributed orchestration, you can access and process data across any system without moving it. This allows you to overcome the "data gravity” problem that blocks your most critical AI initiatives.
Kamiwaza securely connects to every data source in your enterprise: private servers, public clouds, laptops, cameras, and other edge devices. Now, you can run inference on data that was too sensitive, regulated, or costly to move.
Use Your Data Without Formatting It
Your data is ready today—no need to clean, reformat, or centralize it. Using the Context Manager, Kamiwaza automatically builds a living data ontology across all your data sources and always keeps it up to date. Use it for structured and unstructured data, including images, videos, and handwritten notes. This knowledge graph connects entities, relationships, and insights that span organizational boundaries.
No manual mapping, no data movement. Just intelligent understanding of how your information connects to drive better decisions.
Keep Your Data Secure
Some of the most exciting ways to use AI have been constrained by security policies, especially when it comes to using sensitive data.
Kamiwaza gets you over the hurdle with secure AI authorization that enforces policies based on real organizational relationships, preventing data leakage and ensuring you stay in compliance with security policies and regulations like GDPR or HIPAA. Now you can make AI safe and governable at scale by understanding the full context of every AI action, right where your data lives.
Secure AI Authorization
Relationship-based Access Control (ReBAC) with a unified graph engine and full auditability for contextual authorization
Activity Logging and Audit
Comprehensive audit trail for user actions, system events, and AI agent activities with immutable, append-only logging
Chainguard integration
Hardened, zero-CVE (common vulnerabilities and exposures) container images to support a secure-by-default platform
Workrooms
Isolated multi-tenant execution spaces with compartmentalized access controls and ephemeral session management
Classification & Security Markings
Standardized markings to meet federal and defense classification requirements out of the box
Distributed Data Engine
Core architecture that connects to enterprise data sources and processes data where it lives, without migration
Context Manager
System that automatically discovers data and maps relationships across the enterprise to create a living ontology
Inference Mesh
Silicon-agnostic orchestration that routes AI workloads to data across distributed systems–cloud, on-prem, and edge
Embedding and Vector Service
Text-to-vector conversion and vector database management for semantic search, integrated with existing infrastructure
Data Catalog
Metadata management and DataHub integration for data discovery, governance, and lineage tracking
Retrieval Service
One unified service to handle data retrieval from any connected source, without the need to manage adapters
Semantic Search
Semantic search, keyword matching, and knowledge graph traversal with automatic summarization
App Garden
Library of production-ready AI applications that deploy to secure infrastructure instantly
Kaizen
Conversational AI agent that can take multi-step actions inside the enterprise firewall, acting as a secure orchestrator
Model Management
Model repository with full lifecycle management, including discovery from Hugging Face and versioning
Tool Shed
Catalog of secure connectors that allow AI agents to interact with databases, mainframes, APIs, and operational tools
Connector Framework
Standardized connector architecture that supports Microsoft 365, S3, SharePoint, Outlook, Gmail, Slack, and more
Cluster Management
Distributed multi-node orchestration that includes etcd coordination and resource management
Observability and Monitoring
Monitoring features to standardize observability and detect anomalies, investigate incidents, and demonstrate compliance
SDK & API
OpenAI-compatible APIs, Model Context Protocol (MCP) extensibility, and Python SDK
Lab Notebook
Integrated JupyterLab environment for data science experimentation, model prototyping, and interactive analysis
FAQs About Data Ontologies for AI
What Features Should I Look for in an AI Orchestration Platform?
A data ontology defines the relationships between concepts, entities, and data types within an enterprise. Enterprise data ontologies provide the structure that helps AI reason about data instead of just retrieve it. When an AI understands this context, it can generate answers that reflect how your enterprise operates, not just the text of your documents.
How Can I Make AI Work Safely Across My Enterprise?
To build a data ontology, an enterprise must map key business relationships and attributes to data. This creates the foundation for semantic reasoning, which allows AI models to accurately use your data. While manually creating a data ontology can take months, Kamiwaza can automate key parts of the process and dramatically accelerate your time to deployment.
What Hardware Do I Need to Run Kamiwaza?
As your enterprise evolves, so does your ontology. Rather than requiring a static, pre-built knowledge graph, Kamiwaza’s ontologies continuously map the relationships and semantics across your enterprise data sources. This dynamic context graph updates as your data changes and remains synchronized with the systems of record your business relies on.
What Is a Living Ontology and Why Do I Need One?
What Makes Kamiwaza Different From Other AI Orchestration Platforms?
With a data ontology, data retrieval system, and LLM working in sync, enterprise users can go beyond simple search and ask complex questions about projects, trends, and workflows. Here are a few examples of the kinds of questions they can ask:
- "Which products were discussed in meetings with our top clients last quarter?"
- "What services depend on the authentication API?"
- "Which internal subject matter experts worked on patented technology used by our main competitor?"
How Can Kamiwaza Help Me Deploy AI Faster Than Other AI Orchestration Platforms?
See What Distributed AI Orchestration Can Do for Your Enterprise
Schedule a personalized walkthrough to see how Kamiwaza transforms enterprise AI deployment.