Data and AI Governance | Fractal Analytics

Governance

Adding the flavor of
AI governance

Adding the flavor of AI governance

Adding the flavor of
AI governance

Unified governance for accurate data, secure access, and accountable AI operations.

The data and AI governance gap is holding businesses back

Fragmented systems and untrusted data undermine decisions, compliance, and AI value.

Siloed data management

Key business data sets are scattered across multiple systems, leading to duplication, poor service, and missed revenue opportunities.

Siloed data management

Key business data sets are scattered across multiple systems, leading to duplication, poor service, and missed revenue opportunities.

Inconsistent data standards

Business units use different codes, definitions, and hierarchies, leading to inconsistent KPIs and unreliable insights.

Inconsistent data standards

Business units use different codes, definitions, and hierarchies, leading to inconsistent KPIs and unreliable insights.

Untrusted data and models

Advanced analytics and AI models fail due to inconsistent or untrusted input data.

Untrusted data and models

Advanced analytics and AI models fail due to inconsistent or untrusted input data.

Compliance drag and risk

Manual controls and opaque models increase audit burden and regulatory exposure.

Compliance drag and risk

Manual controls and opaque models increase audit burden and regulatory exposure.

Building a trusted data and AI foundation for enterprise growth

Enterprises win when trusted, business-ready data powers Responsible AI and informed decisions, enabled by our eight core data and AI governance capabilities.

Data governance strategy

Assess the current state, design a future-ready model, codify policies and controls, and build a clear roadmap to drive consistency, compliance, and scalable value.

Data governance strategy

Assess the current state, design a future-ready model, codify policies and controls, and build a clear roadmap to drive consistency, compliance, and scalable value.

AI governance and Responsible AI

Embed guardrails to ensure fairness, transparency, privacy, and accountability across AI lifecycle, aligning outcomes with human values and regulations to earn trust at scale.

AI governance and Responsible AI

Embed guardrails to ensure fairness, transparency, privacy, and accountability across AI lifecycle, aligning outcomes with human values and regulations to earn trust at scale.

Metadata management

Turn metadata into a strategic asset, a roadmap that unlocks faster insights, ensures stronger governance, and makes data easier to find, trust, and use.

Metadata management

Turn metadata into a strategic asset, a roadmap that unlocks faster insights, ensures stronger governance, and makes data easier to find, trust, and use.

Data quality management

Embed governance and continuous improvement into a scalable “factory model,” ensuring decisions are always powered by accurate, consistent, and reliable information.

Data quality management

Embed governance and continuous improvement into a scalable “factory model,” ensuring decisions are always powered by accurate, consistent, and reliable information.

Data literacy

Empower leaders and teams with the ability to understand, interpret, and communicate with data, driving innovation, agility, and competitive advantage.

Data literacy

Empower leaders and teams with the ability to understand, interpret, and communicate with data, driving innovation, agility, and competitive advantage.

Data privacy, compliance, and security

Safeguard reputation and minimize regulatory risk by protecting sensitive information with enterprise-grade privacy, compliance, and security controls.

Data privacy, compliance, and security

Safeguard reputation and minimize regulatory risk by protecting sensitive information with enterprise-grade privacy, compliance, and security controls.

Master and reference data management

Enable enterprise-wide harmonization by establishing a single, trusted source of truth, delivering consistency, efficiency, and alignment for business-critical decisions.

Master and reference data management

Enable enterprise-wide harmonization by establishing a single, trusted source of truth, delivering consistency, efficiency, and alignment for business-critical decisions.

Third party data management

Strategically acquire, validate, integrate, and monitor external data to align with internal standards, ensure fitness for use, and meet regulatory requirements.

Third party data management

Strategically acquire, validate, integrate, and monitor external data to align with internal standards, ensure fitness for use, and meet regulatory requirements.

Fast-track innovation, deliver impactful outcomes

Leverage AI, automation, and analytics to simplify data, strengthen governance, and unlock insights that accelerate smarter business growth.

An agentic AI solution for enterprise-scale data ops, enabling governed, reusable Data Products across the global markets

A metadata-driven platform for scalable, AI-powered app development across multiple LLMs and engines

Success stories

Case Study

Enterprise DLP reinvented at scale

Implemented a modern, automated framework to classify and protect high-value data across a complex financial ecosystem

Case Study

Building Agile data governance framework

Establishing a scalable data governance operating model for a global pharma leader

Case Study

Enabling data literacy for smarter governance

Driving responsible data use through persona-aligned learning for a global consumer goods leader

Case Study

Operationalizing data governance for scalable & sustainable impact

Embedding governance into business workflows to ensure consistency, accountability, and enterprise-wide data value realization

Minimal Touch Governance

At Fractal, we believe governance should be effortless yet effective. Our Minimal Touch Data Governance approach embeds control where it counts, automation, compliance, and scalable data operations, reducing manual effort while enhancing trust and agility. Our service offerings across eight capabilities

Data governance strategy

Data governance assessment and roadmap

Data governance policies, standards and controls

Data governance operating model

AI governance and Responsible AI

AI strategy & policy development

Monitoring and oversight systems for AI model performance

Data lineage and impact analysis

AI-driven assignment of stewardship

Data quality management

DQ framework

Data quality as a service with AI augmented quality operations

Data quality stewardship covering profiling, monitoring and root cause analysis

Data quality for unstructured data

Data literacy

Assessment and benchmarking

Tailored training programs and role-specific learning paths.

Change management, including establishing a community of practice, engagement strategy.

AI-driven tracking of impact measurement and optimization.

Data privacy, compliance, and security

Data protection and privacy regulations such as GDPR, CCPA, and Canada Digital Privacy Act, Australia APP Privacy Act, Singapore PDPA, DPDPA, and industry-specific regulations like ISO 27001, SOC 2, FedRAMP, and others.