SCIKIQ is an AI-native Data & Intelligence Platform designed to help enterprises make their data trusted, governed, connected, and ready for AI in weeks rather than years. Recognized by Forrester, NASSCOM League of 10, YourStory Tech30, Inc42, and DataIQ, SCIKIQ supports enterprises across the USA, India, UK, and UAE.
SCIKIQ brings together Data Integration, Data Quality, Data Governance, Metadata Management, Data Lineage, Semantic Intelligence, Knowledge Graphs, Conversational Analytics, Generative AI, Data Products, and AI Agents within one unified platform.
Unlike traditional data platforms that often require extensive replatforming or migration, SCIKIQ works with an enterprise’s existing technology ecosystem. Organizations can connect SAP, Salesforce, Oracle, Snowflake, Databricks, AWS, Azure, GCP, data lakes, data warehouses, and enterprise applications through 200+ pre-built connectors, without rip-and-replace.
Contextual Intelligence at the Core
SCIKIQ goes beyond connecting data by helping AI understand the business context behind it.
Its semantic intelligence layer brings together business terminology, KPI definitions, metadata, lineage, ownership, business rules, ontologies, and relationships to create a trusted context layer for enterprise analytics and AI.
Business users can ask questions in natural language, investigate KPIs, identify root causes, and generate insights without writing SQL. Data teams gain enterprise-grade capabilities for data integration, quality, governance, lineage, metadata, and control.
AI teams gain trusted, contextual enterprise data for building Generative AI applications, copilots, and intelligent AI agents.
Why Enterprises Choose SCIKIQ
AI-ready in 3–6 weeks | 200+ connectors | 99.9% availability | No-code | Multi-cloud | No vendor lock-in | No replatforming
SCIKIQ has production deployments across industries including manufacturing, retail, aviation, logistics, BFSI, healthcare, and other data-intensive enterprises.
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AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack.
At its core is the AnalyticsCreator Governed Control Model, which keeps business meaning, data structures, transformation rules, dependencies and technical implementation connected in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design.
Generated assets can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, Microsoft Fabric components, deployment artefacts and Power BI semantic models. AnalyticsCreator supports dimensional, 3NF and hybrid modelling approaches together with ingestion, transformations, delta loading, historisation, Slowly Changing Dimensions, snapshots and repeatable data-processing patterns.
Changes made in the model can be propagated across dependent project assets, while lineage, documentation and impact analysis remain connected to the underlying design. This helps teams reduce repetitive engineering work, standardise delivery and understand the effect of change before regenerating affected assets.
AnalyticsCreator generates native Microsoft technology rather than requiring a proprietary runtime. Organisations retain ownership of the resulting implementation and can integrate generated assets into existing Git, Azure DevOps and CI/CD processes.
Design Intelligence extends this governed project context into AI-assisted data engineering by giving authorised AI tools and agents structured access to metadata, lineage, dependencies and design rules.
Typical use cases include enterprise data warehouse development, Microsoft Fabric adoption, SQL Server and SSIS modernisation, governed Power BI delivery, SAP-to-Microsoft analytics architectures and repeatable data product engineering.
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SQLFlow
SQLFlow provides a visual representation of the overall flow of data. Automated SQL data lineage analysis across databases, ETL, business intelligence, cloud and Hadoop environments by parsing SQL Script and stored procedure. Depict all the data movement graphically. Support more than 20 major databases and still growing. Provide automation in building the lineage no matter where the SQL resides: databases, file system, Github, Bitbucket and etc. Shows data flows in a way that is user-friendly, clear, and understandable. Get full visibility into your BI environment. Discovering Root-Cause of Reporting Errors, creates invaluable business confidence. Simplify regulatory compliance. The visualization of data lineage provide greater transparency and audit ability. Enable impact analysis at a granular level, drill down into table, column, and query-level lineage. Add the powerful data lineage analysis capability to your product instantly.
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