About ClairX | Your trusted partner for Data and AI Solutions

Who We Are

What separates pilots from production in your AI journey? It’s complete, accurate, and comprehensive data. ClairX accelerates AI outcomes by making data foundations rock-solid. For us, Clair means clarity, and “X” is the multiplier of agility, speed, and imagination.

Wherever you are on the AI trajectory, we turn your ideas into elevated operational resilience and outcomes – one AI transformation at a time. Our seasoned team of data, AI, and engineering experts brings decades of industry experience, converting your enterprise data into governed, production-grade systems that deliver significant value for customers, investors, and employees.

Vision and Mission

Enable enterprises to meet regulatory requirements while scaling trustworthy, consistent, auditable AI that automates decisions, improves outcomes, and preserves transparency.

Deliver engineered, production-grade AI platforms that convert data into reliable decisions, reduce risk, accelerate outcomes, and generate measurable business value.

Our Leaders

Amita Mirajkar

Co-founder and Chief Executive Officer

Leads AI strategy and delivery, engineering excellence, and large-scale data transformation. Over 15 years of experience delivering production data platforms and AI on an enterprise scale.

Shantanu Mirajkar

Co-founder and Chief Technology Officer

Expert in data strategy, cloud, and enterprise architecture, solution blueprints, and client growth. Leads the architecture of scalable platforms for mission-critical AI deployments.

Leading Hyperscalers and Platforms

Platforms

We bring extensive experience architecting and managing platforms with Databricks, Snowflake, Palantir, Cloudera, AWS, Azure, and GCP. Our expert teams have sharp focus to accelerate deployments with reference architectures, robust integrations, and operational runbooks.

Cloud & Infrastructure

Whether you prefer Cloud-agnostic or Cloud-native or hybrid approach, we meet you as a trusted team. We bring experience from several deployments on AWS, Azure, and GCP with automated CI/CD, secure networking, and FinOps optimisation for resilient, cost-efficient AI operations.

MLOps & Observability

Integrated MLOps, observability, and model governance—lineage, explainability, monitoring, and automated retraining pipelines that keep models accurate and auditable in production.

Trust, Governance & Responsible AI

Responsible AI Framework

Responsible AI is engineering-first, covering bias audits, fairness testing, XAI, and accountability gates integrated into development and release workflows for sustained trust.

Compliance & Data Privacy

GDPR-ready architecture, data minimisation, encryption, and strict access controls protect PII and consistently meet regulatory requirements across geographies and deployments.

Auditability & Explainability

Full audit trails, model lineage, and explainability tooling provide transparent traceability of decisions for regulators, auditors, and stakeholders across the AI lifecycle.

About Us