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What is SCIKIQ?
SCIKIQ is one of the most innovative AI-native Data & Intelligence platforms for enterprises, built to make enterprise data AI-ready in weeks, not years.
Recognized by Forrester among leading AI-augmented data platforms, NASSCOM League of 10, YourStory Tech30, Inc42 and DataIQ, SCIKIQ is trusted by leading global enterprises across the USA, India, UK and UAE.
SCIKIQ brings Data Integration, Data Quality, Data Governance, Metadata Management, Data Lineage, Semantic Intelligence, Knowledge Graphs, Conversational Analytics, Generative AI, Data Products and AI Agents together in one unified platform. Unlike traditional data platforms that require enterprises to move or rebuild their technology stack, SCIKIQ works with what you already have. Connect SAP, Salesforce, Oracle, Snowflake, Databricks, AWS, Azure, GCP, data lakes, warehouses and enterprise applications through 200+ pre-built connectors, with no rip-and-replace.
What makes SCIKIQ different is Contextual Intelligence.
SCIKIQ doesn't just connect data; it helps AI understand its business meaning. Its semantic layer combines business terms, KPI definitions, metadata, lineage, ownership, rules, ontologies and relationships to create a trusted foundation for enterprise AI. Business users can talk to their data in natural language, investigate KPIs, discover root causes and generate insights without SQL. Data teams gain enterprise-grade governance, quality, lineage and control. AI teams get trusted, contextual data for building GenAI applications and intelligent AI agents.
Why enterprises choose SCIKIQ
AI-ready in 3–6 weeks | 167+ connectors | 99.9% availability | Multi-cloud | No-code | No vendor lock-in | No replatforming
Proven production deployments across Manufacturing retail, airlines, logistics, BFSI, Healthcare and others
What is Foundational?
Identify and tackle coding and optimization issues in real-time, proactively address data incidents prior to deployment, and thoroughly manage any code changes that impact data—from the operational database right through to the user interface dashboard. Through automated, column-level data lineage tracking, the entire progression from the operational database to the reporting layer is meticulously analyzed, ensuring that every dependency is taken into account. Foundational enhances the enforcement of data contracts by inspecting each repository in both upstream and downstream contexts, starting directly from the source code. Utilize Foundational to detect code and data-related problems early, avert potential complications, and enforce essential controls and guidelines. Furthermore, the implementation process for Foundational can be completed in just a few minutes and does not require any modifications to the current codebase, providing a practical solution for organizations. This efficient setup not only fosters rapid responses to challenges in data governance but also empowers teams to maintain a higher standard of data integrity. By streamlining these processes, organizations can focus more on innovation while ensuring compliance with data regulations.
Integrations Supported
Apache Kafka
PostgreSQL
Snowflake
Amazon S3
Apache Spark
Census
Databricks
Dropbox
GitLab
Google Analytics
Integrations Supported
Apache Kafka
PostgreSQL
Snowflake
Amazon S3
Apache Spark
Census
Databricks
Dropbox
GitLab
Google Analytics
API Availability
Has API
API Availability
Has API
Pricing Information
Yearly License
Contract Pricing
Contract Pricing
Free Version
Free Trial Offered?
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
SCIKIQ
Date Founded
2023
Company Location
India
Company Website
scikiq.com
Company Facts
Organization Name
Foundational
Company Location
United States
Company Website
www.foundational.io
Categories and Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Business Intelligence
Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics
Catalog Management
Catalog Creation
Content Library
Content Management
Cross Selling Functionality
Custom Product Attributes
Customizable Catalogs
Desktop Publishing
Pricing Management
Product Comparison
Search
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Fabric
Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services
Master Data Management
Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization
PIM
Content Syndication
Data Modeling
Data Quality Control
Digital Asset Management
Documentation Management
Master Record Management
Version Control
Categories and Features
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
Data Lineage
Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
Static Code Analysis
Analytics / Reporting
Code Standardization / Validation
Multiple Programming Language Support
Provides Recommendations
Standard Security/Industry Libraries
Vulnerability Management