AI is only as powerful as the data behind it. We help enterprises design and build the data infrastructure, governance frameworks, and AI-ready pipelines that make sustained AI performance possible, not just in one pilot, but across the org. Powered by Gen-e2™, our AI-first delivery methodology, we build the platform your AI strategy can actually run on.

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AI-ready data infrastructure

We design and implement the data architecture, pipelines, and storage layers your AI systems need to perform at scale. Cloud-native, modular and built to grow with your use cases rather than constrain them.

47% average productivity gain

AI output shouldn't depend on who's prompting. We set you up with a shared operating layer of reusable rules, standards, and role-based patterns, our Gen-e2 Common setup package, so teams work from one vetted foundation and see an average 47% productivity gain.

Defensible by design

Data should be defensible by design. We embed security and regulatory compliance into the platform from the start, not bolted on at the end, with enterprise-grade encryption, access controls, and governance aligned to your industry.

One governed hub for AI access

As AI systems multiply, governing how they access data becomes critical. Our Enterprise AI Hub gives you one governed place to curate, approve, and distribute AI capabilities, with role-based access, audit trails, and oversight built in from the start.

AI-ready data infrastructure

We design and implement the data architecture, pipelines, and storage layers your AI systems need to perform at scale. Cloud-native, modular and built to grow with your use cases rather than constrain them.

47% average productivity gain

AI output shouldn't depend on who's prompting. We set you up with a shared operating layer of reusable rules, standards, and role-based patterns, our Gen-e2 Common setup package, so teams work from one vetted foundation and see an average 47% productivity gain.

Defensible by design

Data should be defensible by design. We embed security and regulatory compliance into the platform from the start, not bolted on at the end, with enterprise-grade encryption, access controls, and governance aligned to your industry.

One governed hub for AI access

As AI systems multiply, governing how they access data becomes critical. Our Enterprise AI Hub gives you one governed place to curate, approve, and distribute AI capabilities, with role-based access, audit trails, and oversight built in from the start.

How can we help?

We work with enterprises to design and build the data and AI platform foundations that make sustained AI performance possible, from initial architecture through to governance at scale.

Data Architecture & Infrastructure Design

We design the underlying data architecture your AI systems need to perform reliably at scale: storage layers, pipeline design, cloud infrastructure, and integration patterns matched to your specific AI use cases and organizational complexity. This includes preparing data for AI-native workloads, from analytics pipelines to the vector and feature stores that retrieval and agent-based systems depend on. The output is a modular, scalable foundation that grows with your AI ambitions rather than becoming a bottleneck.

Platform Migration & Consolidation

We migrate and consolidate fragmented data sources, warehouses, and lakes onto modern, well-governed platforms, reducing sprawl and setting a clean foundation for AI. Migrations are planned and executed with the integration, security, and lineage patterns enterprises expect, so nothing critical breaks and the resulting environment is easier to secure, audit, and build on.

Data Quality, Security & Compliance

Poor data quality and weak controls are two of the most common reasons AI initiatives underdeliver or stall in review. We establish the quality standards, validation, cataloging, and lineage that keep your data accurate, consistent, and trusted, and we embed security and compliance from the ground up: access controls, encryption, data classification, data residency, and regulatory alignment for your industry and regions. We also put data-loss and leakage safeguards in place, so sensitive data stays protected as more AI systems come to depend on it. Building this in from the start is far less costly than retrofitting it later.

AI Governance & Data Oversight

As AI systems and agents multiply, governing how they access and use enterprise data becomes the defining operational challenge. Through our Enterprise AI Hub, you get one governed place to curate, approve, and distribute AI capabilities, with role-based access, per-agent scoping, MCP-based connections, and full audit trails. Every agent reaches only the data it's authorized to, monitored end to end, so leadership gets visibility and your teams get the confidence to move fast without losing control.

FAQ

A data and AI platform is the foundational layer that makes enterprise AI work in practice: the infrastructure, pipelines, governance, and quality standards that give your AI systems reliable, secure, well-managed data to run on. Without it, AI initiatives tend to stall after the pilot, because the underlying data can't support consistent performance at scale.

We make data AI-ready by combining sound architecture with strong quality and governance. That means designing cloud-native storage and pipelines, then establishing the validation, cataloging, and lineage practices that keep data accurate and trusted. And where retrieval or agents are involved, we prepare data through the vector and feature stores those systems depend on, so your models and agents work from information you can rely on.

Gen-e2 Common is a shared setup package of reusable rules, standards, and role-based patterns that we deploy in your environment. It gives every team the same vetted foundation from day one, so AI output stays consistent across engineers, analysts, and reviewers rather than depending on who is prompting.

We govern AI access through a single, controlled hub, our Enterprise AI Hub, where capabilities are curated, approved, and distributed with role-based access, per-agent scoping, and audit trails. Approved agents connect through MCP-based, monitored connections, so oversight and accountability are built in rather than added later.

Yes. We migrate and consolidate fragmented data sources, warehouses, and lakes onto modern, well-governed platforms, reducing sprawl before you scale AI on top. Migrations are planned and executed with the integration, security, and lineage patterns enterprises expect, so nothing critical breaks and the resulting environment is easier to secure, audit, and build on.

We build security and compliance into the platform from the start, not as a later add-on. This covers access controls, encryption, data residency, and alignment to the regulatory frameworks relevant to your industry and regions, so your data stays defensible by design even as more AI systems come to depend on it.

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Virgin Active membership migration & mobile innovation

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Our clients & tech ecosystem

Our clients and partners are amongst the world's most successful companies. We innovate with established Fortune 1000s and pioneers in tech and AI who aim to lead, not follow.

  • Clients
  • Tech Ecosystem
Standard chartered
AXA-1
Orange
SIA_logo_1
Total
LVMH
Virgin_Active_Logo
UNDP
DBS
AIA_logo
Ericsson
Qantas_logo_2
Engie
Loreal
Sodexo_logo
Unicef
BNP Paribas
Manulife
StarHub_logo_1
SNCF
CLP
Carrefour
Accor_logo
WWF
Santander
Prudential
Sacem_logo_1
MTR_logo
Alstom_logo
PG_logo
Edenred_logo
Singapore_Government_Logo_1
ING_logo
MunichRE_logo
Canal+
OOCL_logo
Alcatel_Lucent_logo
Pernod_Ricard_logo
The1_logo
GovTech Singapore
GIC
Krungsri
Singtel_logo
CMA_CGM_logo
Safran_logo
Colgate_logo
HP_logo
MPA_logo_2
Microsoft
GitHub_Lockup_Black_Clearspace 2
Anthropic dark grey
OpenAI
Google Deepmind dark grey
xi dark grey
Mistral AI dark grey 1
Figma dark grey
Atlassian
Stripe
Snowflake
Hedera
Confluent dark grey 3
AWS
Microsoft Azure dark grey
Google Cloud
Alibaba Cloud dark grey

Partner Awards & Recognition

APAC Services and Channel Partner of the Year Award

GitHub

Finalist in Accelerate Developer Productivity Award

Microsoft

APAC Partner of the Year for Channel Security

GitHub

Digital & App Innovation (Azure) Partner of the Year Award

Microsoft

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FAQ

A data and AI platform is the foundational layer that makes enterprise AI work in practice: the infrastructure, pipelines, governance frameworks and quality standards that ensure your AI systems have reliable, secure and well-managed data to operate on. Without it, AI initiatives tend to deliver inconsistent results in pilots and fail to scale. With it, AI performance compounds across the organization rather than staying confined to isolated use cases.

We start by understanding your current data landscape, what exists, where it lives, how it's managed and what your AI use cases actually require. From there we identify the gaps between your current state and what's needed to support your AI roadmap. This assessment shapes the architecture and infrastructure recommendations rather than applying a generic blueprint to your situation.

Governance is not a separate workstream. It's embedded into how the platform is designed. This means defining who can access what data, how AI systems are permitted to use it, how decisions made by AI are audited and how compliance is maintained as the platform evolves. As AI use cases multiply across an organization, governance is what keeps the whole system defensible and trustworthy.

Both approaches are possible and the right answer depends on your current state. In many cases we work with and extend existing infrastructure, integrating new layers around what's already in place. In others, legacy data architecture creates enough technical debt that a more substantial rebuild is the more cost-effective path. We assess both options honestly before recommending either.

A data and AI platform is the execution layer beneath your AI strategy. If you're working with PALO IT on AI strategy, the platform work follows directly from the use cases and priorities defined there. If you're coming to us specifically for data platform work, we'll ensure what we build is aligned to where your AI ambitions are heading, not just where you are today.

Both. The AI-first approach applies to new (greenfield) product builds and to evolving or modernizing existing systems. Because agents work from your structured context and repository, they can extend current products and rebuild legacy ones with the same speed and governance.

Ready to build the data foundation your AI strategy needs?
Let's design a platform that performs at enterprise scale, from day one.
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