You cannot automate what you cannot see.

Is your data fueling growth — or silently holding you back?

Most enterprise intelligence today is “Dark Data”: trapped in silos, invisible, and deteriorating. Leadership often makes high-stakes decisions based on incomplete snapshots, leaving the promise of a single source of truth unrealized.

The Samta Advantage:

We illuminate your data landscape, synchronizing legacy siloes with modern enterprise systems. By engineering a robust data value chain—from discovery and annotation to Master Data Management—we transform your fragmented archives into an AI-ready launchpad. 

Stop guessing. Start seeing.

Most enterprises utilize less than 20% of their collected data. Discover what the other 80% is hiding.

What We Deliver

Data Discovery & Profiling

Identify data sources: Discover structured and unstructured data across enterprise systems
Assess data quality: Evaluate completeness, accuracy, and consistency of data
Map data gaps: Identify missing, redundant, or misaligned data affecting insights

Cataloguing & Classification

Build searchable catalogs: Create centralized, searchable inventories of data assets
Classify sensitive data: Identify and label sensitive and regulated data elements
Define ownership: Establish clear data ownership and stewardship responsibilities

Aggregation & Integration

Consolidate enterprise systems: Integrate data from ERP, CRM, finance, ITSM, CMDB, and operational platforms
Enable seamless data flows: Build reliable pipelines for continuous data movement
Support analytics consumption: Deliver integrated datasets for reporting and AI use

Cleansing & Standardization

Normalize data formats: Apply consistent structures, formats, and definitions
Remove duplicates: Eliminate redundant and conflicting records
Improve data consistency: Align data values across sources and platforms

Master Data Foundations

Define master data domains: Identify core entities such as customers, products, vendors, and employees
Create reference data: Standardize codes, hierarchies, and business definitions
Enable governance: Apply controls to maintain long-term data accuracy and consistency

Business Value Delivered

Faster AI adoption

by removing data readiness bottlenecks

Better decision-making

with consistent and connected datasets

Lower data operations cost

through automation and standard pipelines

Higher trust in reporting

and analytics across business functions

Real Industry Outcomes

Retail

Unified customer data enabling personalization and pricing intelligence

Healthcare

Compliant datasets prepared for diagnostics and clinical analytics

Banking

Integrated data improving fraud monitoring and regulatory reporting

Manufacturing

Sensor and operations data prepared for predictive maintenance

Case Studies

AI-Powered Assessment & Recruitment Platform

Challenge:

Hiring teams often struggle with slow, manual, and inconsistent assessment processes. Creating role-...

Banking — Unified Data for Risk & Compliance

Challenge:

A mid-to-large financial institution operated multiple core banking, compliance, and reporting syste...