Data & AI Foundation

We make AI reliable and scalable by unlocking unified, governed, AI-ready data

Unify your data. Profile your customer. Unlock your AI.

Connected, governed data and modern platforms unlock AI and analytics. ADA builds unified data foundations that consolidate customer, product, and commerce data into one governed layer that is ready for reporting, activation, and AI at scale

How AI Transforms Healthcare: Risk Prediction to Clean Claims

Blogs

24 Jan 2026

Our solutions

Unified Data Platform

A complete view of your data: unifying customer, product, and commerce data into one governed foundation for activation and analytics. Built for AI readiness, not just reporting

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Time-to-insight reduction

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Data connectors built

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Data quality achieved across critical datasets

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Data for AI

An AI-ready data layer that is structured, governed, and optimized to power AI agents, and enable intelligent automation at scale. The foundation AI needs to deliver

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Data prep time reduction

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Governance coverage for GenAI deployments

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Data quality improvement for AI training

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Our Services

Unified Data Platform

Data for AI

Unified Data Platform

Data Engineering & Integration

We connect to any source—whether CRM, POS, marketing platforms, IoT, or legacy systems—using leading ingestion tools like Fivetran, Airbyte, and cloud-native connectors. We’ve built 500+ connectors, including custom integrations for hard-to-reach sources. Both real-time streaming and batch ingestion, with schema validation and change data capture built in.

Customer Data Platform (CDP)

CDP implementation as part of your unified data foundation, not a standalone silo. Identity resolution, profile unification, and activation readiness built on your data warehouse. Composable CDP architecture that avoids vendor lock-in while enabling real-time personalization and segmentation.

Data Migration

Full data infrastructure migration—on-premise to cloud, legacy warehouse to modern lakehouse, or platform-to-platform moves. We implement across Snowflake, Databricks, AWS, GCP, and Azure with data validation, parallel running, and cutover planning. Migration that modernises your architecture, not just lift-and-shift.

Data Warehouse Lakehouse Implementation

Snowflake, Databricks, or BigQuery implementation with data modelling, dimensional design, and medallion architecture. Platform-agnostic—we work with your preferred cloud. Accelerators for common Retail, BFSI, CPG, and Healthcare data models. Optimised for analytics, reporting, and AI workloads.

Custom Data Connectors

Custom connector development for sources without standard integrations, legacy systems, regional platforms, proprietary APIs, and niche applications. Pre-built connectors for APAC ecosystem including local payment gateways, marketplaces, and regional CRMs. We’ve built 500+ connectors for enterprises and platforms like Fivetran.

Data Governance & Quality

Enterprise data governance frameworks, data quality rules, lineage tracking, access control, data masking, and audit logging. Regulatory-ready frameworks for PDPA, data residency, and compliance requirements. Governance as foundation, not afterthought.

Data for AI

AI Data Engineering & Integration

Data engineering specifically designed for AI workloads: feature pipelines, training data preparation, model serving infrastructure, and real-time inference feeds. We connect, transform, and structure your data for what AI models actually need. Feature engineering, data versioning, and ML-ready transformations included.

Data Labeling Services

Domain-specific data labeling and annotation services for AI/ML model training, text annotation, image/video labeling, entity extraction, sentiment tagging, and custom taxonomy development. Quality assurance workflows and vertical expertise in BFSI, Retail, and Telco ensure training data that reflects real-world complexity.

Data Migration (AI-Ready)

Data migration with AI as the destination, this is not just cloud migration, but migration to platforms optimized for ML training, feature stores, and model serving. Databricks ML, Snowflake ML, Vertex AI, and SageMaker implementations with AI workload requirements built into architecture from day one.

GenAI Guardrails & AI Governance

Governance frameworks specifically designed for GenAI and AI agent deployments: hallucination prevention, compliance filters, prompt injection protection, output validation, and explainability requirements. Goes beyond general data governance to address AI-specific risks that regulators and boards are asking about.

AI/ML Ops

Operationalization of AI/ML models: model deployment, performance monitoring, drift detection, automated retraining pipelines, and feature store management. The last mile that turns trained models into business value. Integrated with ADA’s AI accelerators and composable architecture.

Customer Stories

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Unified Data Platform

How ADA Built 500+ Data Connectors for a Leading Data Integration Platform

Where every touchpoint earns trust, every interaction creates value, and every decision is powered by realtime insight.

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Connectors

Indonesia Unified Data Platform

How a Leading Indonesian Telco Modernized their Data Foundation Mid-cloud Migration

Where every touchpoint earns trust, every interaction creates value, and every decision is powered by realtime insight.

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Connectors

Consumer Goods Data For AI

How a Global Media Group Built AI-powered Creative Generation with Governed Data

Where every touchpoint earns trust, every interaction creates value, and every decision is powered by realtime insight.

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Engagement

Indonesia Unified Data Platform

How a Conglomerate Replaced Excel-based Reporting with Governed Finance Data

Where every touchpoint earns trust, every interaction creates value, and every decision is powered by realtime insight.

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automated reporting workflow

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FAQs

Do we need both solutions?

No. Unified Data Platform creates the foundation. Data for AI adds AI-specific capabilities when needed. Start where the constraint is — if you have fragmented data, start with UDP. If you have data but need AI-readiness, start with Data for AI.

How is this different from a data warehouse?

A data warehouse is storage. We deliver the full stack — ingestion, transformation, governance, and activation readiness. Plus, we design for AI from day one, not as an afterthought.

We already have Snowflake/Databricks. Why do we need you?

Great — we work with your preferred platform. The challenge is not the warehouse tool; it is getting data into it cleanly, governing it properly, and making it usable for business. That is what we do.

What is the fastest path to value?

Start with a data assessment (2-4 weeks) to identify gaps and quick wins. First phase with core sources live in 8-12 weeks. Full platform typically 4-6 months depending on source complexity.

How is Data for AI different from standard data engineering?

Standard data engineering focuses on warehousing and reporting. Data for AI is specifically optimised for AI workloads — labeling, GenAI guardrails, model operationalisation, and AI-specific governance. It is the layer between raw data and working AI.

What if our AI projects are still in pilot phase?

That is the best time to engage. Building the right foundation now prevents technical debt later. We can start with a focused labeling or governance project that supports your pilots, then expand as you scale.