Infosys unveils Topaz Fabric to redefine enterprise AI delivery through a purpose-built cloud fabric that unifies data, models, and governance at scale. This initiative responds to growing demand for secure, scalable, and observable AI across complex enterprise landscapes.
The platform-level approach emphasizes modular design, real-time orchestration, and policy-driven automation, enabling organizations to move from experimental proofs to production AI with reduced risk and faster time to value. By integrating infrastructure, security, and workflow controls into a unified fabric, Topaz Fabric aims to simplify management and increase transparency for AI initiatives.
| Fabric Layer | Primary Capability | Security & Compliance Control | Observability Feature |
|---|---|---|---|
| Data Ingestion | Multi-modal, multi-cloud ingestion | Tokenization, field-level encryption | Schema drift alerts |
| Model Orchestration | Hybrid model routing and caching | Role-based access, model signing | Latency and cost tracking |
| Policy Enforcement | Unified guardrails and quotas | Compliance mapping (GDPR, HIPAA) | Audit trails and incident logs |
| Developer Experience | Integrated SDKs and APIs | Scoped credentials and secrets rotation | Traces, metrics, and feedback loops |
Infrastructure as a Fabric Strategy
Topaz Fabric rethinks infrastructure by treating compute, storage, and networking as interconnected fabric resources rather than isolated products. This approach supports dynamic scaling, fine-grained governance, and consistent policy enforcement across hybrid environments. By abstracting underlying complexity, the fabric enables safer experimentation and simpler lifecycle management for enterprise AI workloads.
AI Workflow Orchestration and Governance
Streamlining Model Deployment
Infosys positions Topaz Fabric as an orchestration layer that coordinates data preparation, model training, and inference while embedding governance checkpoints. Teams can define stage-specific policies, automate approvals, and monitor resource utilization in near real time. This reduces manual intervention and helps prevent configuration drift across environments.
Policy-driven Automation
The fabric enforces policies tied to data sensitivity, regulatory requirements, and cost thresholds. Conditional routing, model version controls, and quota management are codified as code, making governance auditable and repeatable. Organizations gain clearer accountability for AI behavior and more predictable operational outcomes.
Enterprise Security and Compliance Alignment
Security and compliance features are embedded directly into Topaz Fabric, with encryption in transit and at rest, fine-grained identity and access management, and continuous risk assessment. The platform maps controls to frameworks such as GDPR, HIPAA, and industry-specific standards, providing evidence-ready documentation for audits. These capabilities help reduce the operational burden of maintaining secure AI deployments at scale.
Developer Productivity and Ecosystem Integration
Topaz Fabric provides unified SDKs, CLI tools, and API contracts to streamline integration with existing data platforms and CI/CD pipelines. Developers can build, test, and deploy AI artifacts within a consistent environment while benefiting from shared services such as monitoring, logging, and feedback collection. The fabric aims to accelerate delivery by reducing context switching and minimizing custom glue code.
Operationalizing Enterprise AI with Topaz Fabric
- Evaluate workloads for fit, starting with controlled proofs of concept before scaling.
- Define clear guardrails and policies that reflect regulatory, security, and business constraints.
- Standardize data and model artifacts to simplify orchestration and reduce integration complexity.
- Monitor latency, cost, and quality metrics continuously to drive optimization decisions.
- Leverage platform-level dashboards and audit logs to maintain transparency and accelerate audits.
- Build cross-functional teams including data engineers, security, and domain experts to realize full value.
FAQ
Reader questions
How does Topaz Fabric change AI delivery compared to traditional platforms?
Topaz Fabric unifies infrastructure, security, and orchestration into a single fabric layer, enabling policy-driven automation and consistent governance across the full AI lifecycle, unlike fragmented point solutions.
What security and compliance features are built into Topaz Fabric?
The platform includes encryption, tokenization, role-based access, model signing, and compliance mappings to GDPR, HIPAA, and other regulations, supported by audit trails and incident logging.
Can Topaz Fabric integrate with existing data and AI tools in my enterprise?
Yes, Topaz Fabric offers SDKs, APIs, and connector patterns designed to integrate with major data platforms, CI/CD systems, and model serving stacks without replacing existing investments.
What observability and feedback capabilities does Topaz Fabric provide for production AI?
It delivers tracing, metrics, schema drift detection, cost and latency tracking, and feedback loops that feed into model retraining and policy refinement, supporting continuous improvement and transparent operations.