
AnalyticsCreator helps Microsoft data teams turn governed design into deployable data solutions without introducing a proprietary runtime layer.
Teams use AnalyticsCreator to define warehouse structures, transformation logic, historisation rules, relationships and dependencies in a central model. From that model, the application can generate native implementation assets for technologies such as SQL Server, SSIS, Azure Data Factory, Microsoft Fabric and Power BI.
The approach is designed for organisations that want to standardise how data warehouses and data products are engineered while keeping full control of the resulting code and project artefacts. Generated outputs can be integrated into existing Git, Azure DevOps and CI/CD workflows for versioning, review and controlled deployment across environments.
AnalyticsCreator supports dimensional, 3NF and hybrid modelling as well as common engineering patterns including delta loading, Slowly Changing Dimensions, snapshots and historisation. Documentation, lineage and dependency information are maintained alongside the project design, making it easier to assess the impact of proposed changes and keep implementation aligned with the underlying model.
The AnalyticsCreator Governed Control Model provides the foundation for this process by keeping business meaning, technical structures and implementation logic connected. Design Intelligence builds on that context by making governed project metadata, lineage, dependencies and design rules available to authorised AI tools and agents.
Typical use cases include modernising SQL Server and SSIS estates, building Microsoft Fabric solutions, standardising Power BI delivery and creating repeatable data warehouse and data product engineering processes.
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SearchUnify is an enterprise Agentic AI platform that connects fragmented enterprise knowledge and deploys autonomous AI agents to handle customer support operations from first contact to resolution. At its core, the platform is powered by SearchUnifyFRAGâ„¢ (Federated Retrieval Augmented Generation), Agentic RAG, and the SCORE (Contextual Relevance Engine) framework, enabling accurate, grounded responses drawn from unified enterprise data.
The product suite spans five core tools. Cognitive Search retrieves contextually relevant answers across distributed knowledge sources. SearchUnifyGPTâ„¢ generates cited AI responses at every support touchpoint. SUVA, the virtual assistant, handles multi-turn conversations autonomously. Knowbler supports knowledge capture, structuring, and surfacing at the point of need. Agent Helper delivers next-best-action recommendations to support agents during live case resolution.
Extending these capabilities, the Agentic AI Suite comprises eight AI agents: AI Support Agent for self-service resolution, AI SupportPlus Agent for autonomous CRM ticket handling, AI Classification Agent for case tagging and routing, AI Escalation Manager for escalation risk prediction, AI Knowledge Agent for automated content creation and gap detection, AI Competency Agent for L2 technical workflow resolution, AI Agent Partner for real-time agent guidance, and AI Case Quality Auditor for evaluating every closed case.
SearchUnify supports BYOLLM for LLM flexibility, Model Context Protocol (MCP) for secure system connectivity, and a governance layer covering role-based access control, PII masking, and ISO 27001, HIPAA, and SOC 2 compliance. The platform connects with 100+ enterprise tools including Salesforce, Zendesk, and ServiceNow.
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reDock
reDock leverages artificial intelligence and machine learning to streamline content search activities. This capability empowers team members to locate pertinent information without the need to chase subject matter experts or sift through unhelpful results. By enabling swift access to the most relevant content across various data repositories and software platforms, your team can enhance their success in securing more RFPs, acquiring additional projects, boosting revenue, and ultimately driving business growth. Furthermore, this efficiency fosters a more productive work environment, allowing for better collaboration and innovation.
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OpenText Knowledge Discovery
OpenText Knowledge Discovery is an AI-powered knowledge management and content intelligence platform for extracting insights from unstructured information across enterprise repositories. It enables organizations to search, categorize, visualize, review, classify, and enrich documents and rich media regardless of where the information is stored. The platform supports more than 160 repository and application connectors, helping organizations access information distributed across numerous business systems. It can process more than 2,300 content types to extract information from a wide variety of enterprise files and media. AI-driven analytics provide capabilities including entity extraction, semantic analysis, natural language querying, content classification, sensitive data detection, speech recognition, and identification of people and objects. OpenText Knowledge Discovery enriches metadata with labels, classifications, categories, and other contextual information that can make existing content more useful within business processes. Metadata enrichment can also support GenAI initiatives by helping organizations identify, organize, and protect documents, video, audio, and other information assets before they are used by AI systems. Knowledge discovery capabilities can support investigations by making scattered enterprise information more visible, searchable, and understandable. Organizations can also apply the platform to risk management, compliance, intelligent processes, enterprise search, and AI-readiness initiatives. Integrations include Microsoft SharePoint, Teams, Exchange and OneDrive, Google Drive and other Google services, Amazon S3, Salesforce, ServiceNow, Slack, Jira, Webex, Box, Dropbox, Hadoop, Confluence, and additional repositories.
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