These are technology references, not KCR LABS partners or clients. No affiliation, certification, or endorsement is claimed.
Cloud infrastructure & enterprise data
Oracle
Oracle Cloud Infrastructure includes compute, database, integration, and generative AI services. These categories may be considered when a solution needs to connect enterprise information with application and AI workloads.
What to assess
Assess existing Oracle systems, integration paths, data-location requirements, and the operating responsibilities of the proposed architecture.
Official vendor information ↗ (opens in a new tab)Enterprise applications & business AI
SAP
SAP offers business applications and AI capabilities connected to enterprise processes. Its platform and integration tools can be part of a discussion about extending established business workflows.
What to assess
Review the organization’s application landscape, available APIs, licensing, process ownership, and the supported options for the specific system.
Official vendor information ↗ (opens in a new tab)Data, cloud & AI development
Google Cloud
Google Cloud provides cloud infrastructure, data services, and tooling for developing and operating AI applications and agents. Its AI platform supports model and agent development with evaluation and governance capabilities.
What to assess
Compare data integration, application deployment, model needs, and the organization’s cloud operating requirements.
Official vendor information ↗ (opens in a new tab)Azure AI & application platforms
Microsoft
Microsoft Azure provides services for cloud applications, AI development, and connected enterprise solutions. Platform selection can account for an organization’s existing identity, data, and application environment.
What to assess
Review approved information boundaries, service availability, identity integration, and the requirements of the intended application.
Official vendor information ↗ (opens in a new tab)AI software & accelerated workloads
NVIDIA
NVIDIA AI Enterprise provides software for developing, deploying, and managing AI applications across cloud, data-center, and edge environments. It is relevant to discussions about specialized AI workloads and their infrastructure.
What to assess
Assess workload suitability, infrastructure compatibility, licensing, deployment requirements, and the resources needed to operate the solution.
Official vendor information ↗ (opens in a new tab)Cloud services & generative AI
Amazon Web Services
AWS provides cloud infrastructure and managed AI services. Amazon Bedrock offers access to foundation models for building generative AI applications, alongside the broader AWS application and data services.
What to assess
Evaluate the application architecture, model access, information handling, regional requirements, and ongoing service consumption.
Official vendor information ↗ (opens in a new tab)Customer platforms & agent workflows
Salesforce
Salesforce offers customer relationship applications and Agentforce capabilities for AI-supported workflows. These may be considered when a proposed experience is closely connected to existing customer-service or business processes.
What to assess
Review permissions, process design, integration requirements, licensing, and the distinction between a suggested action and an approved business change.
Official vendor information ↗ (opens in a new tab)