Built for enterprises that don’t just build AI - but operate it.
The Architecture Behind The Enterprise AI Operating System
DSW is built for enterprises that are moving AI from experiments into long-running production systems.It provides the operating layer required to run AI safely, continuously, and at scale - without losing governance, ownership, or architectural freedom.
Why Enterprises Need an AI Operating System
AI no longer lives in one team, one model, or one tool.
It Runs Across
Models and Agents
Business Workflows
Data Platforms And Applications
Regulated Environments With Real Risk
Without a system layer, AI becomes fragmented, difficult to govern, and dangerous to scale. Enterprises don’t just need more AI tools.They need a foundation to operate AI as part of the enterprise itself.
That foundation is the DSW Enterprise AI Operating System.
From AI Projects to Enterprise Infrastructure
With DSW, enterprises can:
Run AI entirely inside customer-controlled environments. (on-premises, private cloud, or hybrid)
Retain full ownership of models, agents, workflows, and source code
Integrate any AI ecosystem without vendor lock-in
Treat AI use cases as production infrastructure - not short-term projects
This is how AI becomes durable, governable, and enterprise ready.
Built as an AI ecosystem, not a Platform
At the core of the DSW Enterprise AI Operating System is UnifyAI, operating as a kernel that governs all AI and agentic execution
Governance is not layered on later. It is enforced at runtime - by design.
Kernel-level governance
- Policies execute as code
- Audit, traceability, and reversibility are native
- Controls cannot be bypassed or bolted on later
Governed AI and agentic execution
- Models and agents operate inside defined constraints
- Autonomy is controlled, not improvised
- Lifecycles are managed like system processes
AI as enterprise infrastructure
- Long-running, production-grade execution
- Independent of vendors, clouds, or tools
- Fully owned and operated by your enterprise
DSW Enterprise AI OS Kernel First Architecture
Hardware / Cloud Infrastructure
- Servers, storage, network, accelerators
AI Fabric (Kernel-Mediated Extension & Integration Layer)
- External models, LLMs, OSS, ISV tools
- Accessed only via kernel-defined interfaces
- No direct execution without kernel mediation
DSW Enterprise AI OS Kernel (UnifyAI Core)
- Governance-as-Code (mandatory, non-bypassable)
- Policy enforcement, lineage, audit, reversibility
- AI lifecycle, versioning, execution contracts
- Defines allowed interactions with runtimes & fabric
AI Execution Subsystems (Kernel-Controlled)
- ML Runtime - inference, scoring, monitoring
- Agentic Runtime - multi-agent orchestration
- No execution bypasses kernel policies
Enterprise & AI Applications
- Business applications, workflows, and decision systems
- AI behaves as long-running production systems
A Kernel-Centric Enterprise AI Architecture
The DSW Enterprise AI Operating System is designed to operationalize AI and agentic systems with long-running enterprise capabilities, not isolated applications.
Optimized for regulated and hybrid environments, governance and control are embedded at the system level — not added as compliance afterthoughts.
Architectural Principles
Kernel-centric governance
Policy enforcement and auditability are implemented as non-bypassable kernel functions.
Separation of control and execution
AI workloads execute in governed subsystems while policy, lineage, and lifecycle remain centralized.
Infrastructure independence
The AI OS operates above existing operating systems and infrastructure without replacing them.
Enterprise custody and sovereignty
All AI artifacts remain under enterprise ownership and control.
Controlled ecosystem integration
External models, tools, and services integrate only through kernel-governed interfaces.
The Five Timeless Anchors of the Enterprise AI Operating System
Continuous Adaption
Data Sovereignty
Human Centric
Strategic Flexibility
Adaption Reality
How the System is Structured
DSW Enterprise AI Operating System
ML Runtime
- •Batch and real-time inference
- •Model versioning and controlled rollout
- •Performance monitoring and drift detection
Agentic Runtime
- •Multi-agent orchestration
- •Policy-aware autonomy
- •Human-in-the-loop controls
- •Agent lifecycle management
AI Fabric
- •Foundation models and LLMs
- •Open-source frameworks
- •Partner tools and services
- •Enterprise APIs and data systems
AI OS Kernel (UnifyAI Core)
The authoritative control plane for all AI execution, responsible for:
- •Governance as code
- •Runtime policy enforcement
- •Lifecycle and lineage management
- •Auditability, traceability and reversibility
- •Execution contracts for integrations
Base Infrastructure Layer
Linux, Windows, Unix, or container runtimes manage compute, memory, and networking.
DSW operates above this layer without modifying it.
Operates above existing infrastructure without modification
Governance Built In, Not Bolted On
Audit is native
Every AI action and agent decision is recorded automatically.
Reversibility is native
Models, workflows, and decisions can be rolled back, overridden, or replayed.
Traceability is native
Any outcome can be traced end-to-end — from data to decision.
These capabilities are part of the operating system itself — not plugins, dashboards, or reporting layers.
Deployment, Sovereignty, and Control
Deploy the DSW Enterprise AI Operating System in:
01
On-premises environments
02
Private data centers
03
Private cloud
04
Hybrid architectures
There is no mandatory SaaS dependency, no forced hyperscaler coupling, and no external data egress.
You choose the environment.
You own the system.
You control how AI runs.
Who This Is Built For
CIOs, CTOs, CDOs, and COOs
Enterprise architects and
platform teams
AI, data, and ML
engineering leaders
Risk, compliance, and
security stakeholders
For organizations where AI must be trusted, governed, continuously operational,
and aligned with enterprise risk frameworks.
Tailor-made for regulated insurance environments
Designed for compliance-driven, risk-sensitive operations.
Infosys Finacle’s Open Source Services Partner FY25
InsurTech of the Year 2025
Supports governance, audit, and regulatory workflows across underwriting, claims, and servicing.
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