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Page index

Our work with Google Cloud

From modernizing monolithic infrastructure for Fortune 50 organizations to developing digital products and experiences for venture backed scale-ups, we have a proven track record of exceeding customers’ expectations as they digitally transform their businesses on Google Cloud Platform.

We bring the very best of our technology, product and change capabilities to address our customers’ challenges and deliver the desired outcomes.

Learn how we can help you harness the power of Google Cloud

Contact us

At Google Cloud, we're famous for:

App development and modernization

Whether developing greenfield applications for digital natives or modernizing legacy applications for enterprise, building exceptional data-driven products and experiences is what we’re famous for at Google Cloud.

AI/ML solutions

We have significant experience helping enterprises test and deploy Google Cloud’s market-leading AI/ML solutions, whether it's building chatbots and voice solutions through CCAI and Dialogflow, implementing MLOps with Vertex AI, or enhancing retailers’ ecommerce experiences with Vertex AI Search for Retail and Recommendations AI.

Commerce

We're advocates of composable commerce. With our Integrated Commerce Accelerator, we can implement a future-proof data foundation in Google Cloud that accelerates your journey to a modern commerce platform in just six weeks.

Smart analytics and data modernization

Our teams focus on removing barriers to accessing and using data via tools such as BigQuery and Looker. We look to increase trust and awareness of the data in your business and apply product thinking so business teams can start to take value from their data as early as possible in the modernization journeys.

Marketing analytics

Drive smarter marketing and more intelligent customer experiences by connecting your marketing data into the Google Cloud platform. With Cloud and BigQuery, you can bring valuable marketing data together from GA4 and other tools into one unified place. That way, you can manage, analyze and activate your data better.

Managed services

We manage, monitor and maintain the platforms that underpin your mission-critical workloads through automated software, agile practices and proven governance models via a global team of engineers.

Results

40+

91%

9

Joint clients and counting

Increase in releases for customers on Google Kubernetes (GKE)

Business days to release enterprise chatbot with Dialogflow

 

 

Vertex AI launchpad: Accelerating AI impact with MLOps

Realizing the impact of ML across the enterprise requires strong data foundations, visibility into model performance and a cloud-powered strategy to deliver AI at scale. Valtech can help unlock a roadmap for sustainable AI value, connecting intelligent experiences across the enterprise.

With Vertex AI, Google Cloud’s unified ML platform, Valtech supports companies through the full ML lifecycle, from activating data into model production to automating end-to-end ML workflows at scale (MLOps).

The Vertex AI Launchpad is designed to ramp clients through a key use case to demonstrate MLOps practices with tangible improvements for long-term impact. A templated framework including the following Vertex AI modules will help continuously deliver new capabilities:

  • AutoML. Simplified model development for images, video, tables and text.

  • Feature store. Highly available online plus batch feature serving repository.

  • Vertex AI pipelines. Modular components to orchestrate end-to-end ML workflows.

  • Monitoring and continuous training. Triggers for retraining pipelines on key indicators.

 

A diagram illustrating the components and workflow of Vertex AI, a unified platform for data science and machine learning. The diagram highlights features such as rapid model generation, lakehouse integration, and custom workflow development. The main sections include Auto ML (with capabilities like Vision, Video, Language, Speech, Translation, Tables, Forecast, BigQuery ML), Workbench, Integration with Data Services (Cloud Storage, BigQuery, Spark, BI), Experiment (Datasets, Vertex SDK, Experiments), Train (Training, NAS, Vizier), and Deploy (Prediction, Matching Engine). The bottom row emphasizes Vertex AI pipelines, Model monitoring, Explainable AI, ML Metadata, Feature store, and Model Registry.

What to expect

Working toward an achievable, high-ROI initiative, the five-week launchpad will align a north star to deliver continuous AI business value in four phases:

Phase 1: Align

North star roadmap with short and long-term targets to hone pilot.

Phase 2: Define

Design and documentation of key Vertex AI services to enable MLOps.

Phase 3: Design

Composable Vertex AI pipelines with template for extensible workflows.

Phase 4: Deploy

End-to-End Pipeline testing, deployment, monitoring and KPI validation.

Outcomes

Measurable impact against profit-generating use-case and KPIs to direct new applications for continuous lift.

A roadmap and knowledge transfer for sustainable productionalization of MLOps Level 1 and 2 capabilities, including:

  • Rapid experimentation

  • Continuous delivery and training

  • Code and pipeline modularity

  • Pipeline orchestration

  • CI/CD automation

 

Liberate ML initiatives with a repeatable build and deployment framework to accelerate use case adoption for rapid business value at enterprise scale.

Visible ROI and blueprint to link AI Center of Excellence initiatives with enterprise mandates for operational agility and profitability.

 

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Generative AI opportunity assessment: Explore what’s possible with generative AI

Generative AI is the hottest topic of conversation among business leaders today. While it promises to boost efficiency, spread expertise, improve the customer experience and deliver many other benefits — how do you separate the hype from the true value assistive generative technology can bring to your organization?

The challenge

Before you embark on your AI journey, it’s important to consider issues such as these:

  • Do you have AI-ready data foundations and governance in place?

  • Are your people and processes ready to support new ways of working?

  • What AI safety, ethics and guardrails do you need?

  • How do you determine the viability and value of projects?

  • How do you align AI initiatives with your broader data strategy?

 

Learn how to use generative AI for maximum business impact

Get started on your assessment

Our approach

At Valtech, we have a long history of working with human-friendly data and natural language user experiences — including conversational AI, enterprise search and experimentation.

Our Generative AI Opportunity Assessment is designed to help you accelerate toward your automation goals and gain an understanding of how to use generative AI in a safe, effective way.

This collaborative two-week engagement will help you:

  • Support development of current thinking around AI trends and practices

  • Understand how to apply AI for maximum impact based on fact, not fiction

  • Develop a strategy for Human in the Loop (HITL) design to accelerate business opportunities

  • Identify new possibilities for automation leveraging Google generative AI apps and the Google Cloud ecosystem of products

  • Highlight shifts in the competitive landscape based on rule changes enabled through generative AI

  • Explore initiatives and opportunities that may impact your sustainability targets

Assessment activities include:

Week 1: Initiate
  • Generative AI overview briefing, including a state-of-world summary and Google GenAI briefing (Vertex AI, Generative AI App Builder, MakerSuite, Google PaLM, Bard)

  • Stakeholder interviews

  • Identification and prioritization of challenges, opportunities and scenarios

Week 2: Discovery
  • Benchmark current organizational knowledge

  • Map initiatives and opportunities that may impact sustainability targets

  • Half-day executive workshop to report out and iterate a near-term AI strategy and roadmap

Outcomes

  • Generative AI assessment

  • Executive data strategic opportunity recommendations and roadmap tied to business KPIs

  • Fully estimated proof of value (POV) for your highest value application recommendation

Start using generative AI now to make your organization work better

Contact us

 

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  • Two women are seated at a table, looking at a laptop screen that displays an online store with various furniture items. They are browsing together in a bright, well-lit room with large windows in the background. The focus is on the laptop and their interaction, suggesting a collaborative shopping or decision-making process. The scene has a casual, relaxed atmosphere.
  •  A man with a beard is focused on working on his laptop in a modern indoor setting, possibly a café or co-working space. He is dressed in a blue blazer and a light blue shirt, with a serious expression as he concentrates on his work. The background is blurred, showing other people and a warm, casual environment, with plants and soft lighting adding to the ambiance. A coffee cup and a smartphone are placed on the table next to him.
  • A close-up of a person browsing through a collection of vinyl records while holding a smartphone in their other hand. The person is wearing a light blue sweater, and the setting appears to be a record store or a similar environment with a nostalgic ambiance. The image captures the act of searching for music while possibly researching or cataloging information on the phone. The focus is on the hands, with the background softly blurred.

Vertex AI search for retail evaluation: Lift revenue and lifetime value with AI-powered search experiences

The challenge

The retail search experience can be an exercise in frustration for many consumers. Most search solutions today are static in nature and lack the functionality to understand user intent and context. This can negatively impact brand loyalty and cause significant revenue losses for retailers.

In fact, Google’s own research underscores just how important the search bar is to customers and why retailers need to step up their game:

  • $2 trillion is lost each year from search abandonment globally

  • 78% of consumers view a brand differently and 82% avoid websites after experiencing search difficulties

  • 9 in 10 consumers say a good search function is very important or absolutely essential

Our solution

Three-step Vertex AI Search for Retail Evaluation

Retail search technology is changing quickly, and Google is leading the way with Vertex AI Search for Retail. Combined with Quantum Metric’s insight and monitoring platform, brands are empowered to deliver rapid, data-driven product discovery.

Valtech is here to help you assess the potential and ROI of this next-generation search solution with our three-step evaluation and application approach.

In just a few weeks, our team can ingest your product catalog and events data, then evaluate our solution against your existing search experience to determine its potential impact on your business.

Evaluation and application approach: 3 to 4 weeks

Step 1: Gather data

Our team ingests your product catalog and events data

Step 2: Evaluate

We evaluate the Google and Quantum Metric solution against your existing search experience to determine its potential impact on your business

Step 3: Results readout

We present assessment findings and opportunities for metric uplifts

How your organization will benefit

  1. Identify potential areas of opportunity for your organization to leverage a data-driven approach to search.

  2. Learn how Vertex AI Search for Retail can deliver query understanding and results relevancy that will delight your customers and drive performance metrics for your business.

  3. Learn how Quantum Metric captures user behavior insights and uses machine intelligence to help you understand how customers find your products, where they get stuck, and how their product discovery journeys lead to revenue and lifetime value.

  4. Learn about Valtech’s professional services, proven retail vertical expertise, search engineering, optimization and extensive managed services capabilities.

Customer results (on average)

+12%

+7%

CTR Lift

CVR Lift

 

+6%

+15%

RPV Lift

ROI Lift

 

Get started with next gen search

Contact us

 

A group of diners at a restaurant are paying for their meal. One woman, seated at the table, is holding a smartphone and using a contactless payment system held by the server, who is wearing an apron. Another person at the table looks on, smiling. The setting is a warm, cozy restaurant with wooden tables and a relaxed atmosphere, where people are enjoying their meal. The background shows additional diners and kitchen staff, contributing to the bustling yet comfortable ambiance.

Integrated Commerce Network: Pre-integrated best-in-class data, commerce and personalization capabilities

The challenge

Digital commerce has become increasingly crucial for businesses in today's world, driving more than $5.7 trillion in sales globally. Yet digital has leveled the playing field. New businesses can quickly capture market share by responding and reacting to the needs of consumers and customers alike.

This agility is enabled by technology, and no business can afford to stand still without investing in their commerce platforms.

Our own research also reveals a consistent theme: Business leaders are struggling to trust and use their data. These data silos are limiting the ability of brands to enrich their data and innovate, and to improve the customer experience.

According to our State of Omnichannel Report 2023, 72% of consumers say they have never had a memorable, positive experience with a retailer in exchange for their data.

In order to navigate an ever changing world, we at Valtech believe businesses need a foundation that supports future innovation and enables them to reach time to value quickly. Monolithic legacy technology can prevent organizations from releasing new features at pace — and slow means costly.

Understanding the consumer or customer is also at the heart of this modernization journey, with tailored marketing, personalized experiences and the use of customer data key focuses that enable growth.

Summary of the challenge:

  • Unclear customer experience strategies, including an inability to reach consensus on defining the customer experience and how to improve it

  • Siloed information in terms of collecting, managing and storing customer data

  • Confusing procurement choices and integration path for modern commerce solutions

  • Risk of data leakage from disparate solutions

Start modernizing your commerce architecture now

Chat with us

Our approach

In order to accelerate our clients’ time to value with a modern and future-proofed commerce tech stack, Valtech has launched the Integrated Commerce Network (ICN), a curated group of software partners who enable this transformation across commerce, marketing and customer experience. We believe these partners represent the best-in-breed solutions in their respective domains, while also being complementary to one another.

The ICN was launched with:

  • commercetools, a robust and flexible foundation with unlimited scalability that supports all commerce operations. It offers all the components you need to build and run shopping experiences across all digital and physical touchpoints, and adapt to changing market dynamics and customer preferences.

  • Bloomreach, an Al-powered ecommerce personalization platform that includes a marketing automation solution enabled by BigQuery, Google Cloud’s serverless data warehouse. The Bloomreach customer data engine seamlessly integrates with the Google Cloud partner ecosystem to help you create engaging experiences for your customers and increase conversion rates.

  • Quantum Metric, a customer-centered digital analytics platform that provides a simplified approach to monitor, diagnose and optimize the digital journeys that matter most. The Quantum Metric platform offers in depth customer understanding, quantified and tied to core business objectives.

  • MongoDB Atlas, a developer data platform, trusted by thousands of businesses to power their modern retail applications. With its powerful, flexible and scalable architecture, MongoDB provides the foundation for creating seamless and engaging shopping experiences across all digital and physical touchpoints.

 

The ICN will continue to expand to include complementary partners that will help businesses like yours activate data and unlock new revenue. Now is the time for data-driven commerce transformation, and Valtech is leading the way.

In partnership with

logo-google-cloud.png logo-commercetools.png logo-bloomreach.png logo-quantum-metric.png

 

Also supported by

logo-mongodb.png logo-eagleeye.png logo-spoonguru.png logo-alokai.png

Integrated Commerce Accelerator

Built in tandem with the ICN, our Integrated Commerce Accelerator brings together data from each software vendor on Google Cloud BigQuery. The goal of this accelerator is to help generate new and innovative insights that ultimately enhance the customer experience. This accelerator can also enable the rapid deployment of a modern composable commerce platform on Google Cloud — in a matter of weeks — to visualize and showcase the benefits of a composable solution.

Outcomes the accelerator enables:

  • Understand how to incorporate multiple best-in-class solutions into a composable yet tightly integrated whole

  • Harness the power of data, design and technology to create intelligent customer experiences

  • Boost customer personalization, loyalty and advocacy

  • Increase profitability and achieve fast time to value through rapid deployment and data-driven insights

Learn from our experts

Watch our on-demand webinar now

Components of the foundational accelerator

An infographic outlining the foundational components of a digital platform. The sections include “Commerce,” “Insights,” and “Personalization,” each describing key features and partnerships. The “Commerce” section highlights a partnership with commercetools for scalable solutions. The “Insights” section emphasizes using Quantum Metric for monitoring and optimizing customer journeys. The “Personalization” section details harnessing customer data through Bloomreach for campaign management. The bottom of the infographic notes that the platform is built and integrated with Google Cloud & BigQuery, implemented by Valtech, and powered by MongoDB.

 

Get started

There are multiple entry points to help you begin to activate your data on Google Cloud.

Commerce maturity assessment

We will partner with you to understand your current estate and propose a detailed plan on how to modernize on Google Cloud.

Commerce data activation

Deploy the accelerator to enhance your time to data insights by targeting a high-value use case that demonstrates a clear revenue uplift.

Generative AI quick start

Deploy a generative AI model using your commerce datasets for personalized shopping, pricing optimization or consumer behavior.

Contact us

Want to learn more? Fill in the form in the bottom on the page and one of our experts will get back to you shortly.

Contact us

 

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Data activation launchpad: Unlock your data to enable intelligent experiences

Maximizing data value requires empowered ownership, strong cloud foundations and a strategy to unlock insights through intelligent experiences. Valtech can help consistently drive new enterprise value with a scalable approach to activate data-led transformation on Google Cloud.

Book a meeting

 

Valtech’s Data Activation Launchpad ramps clients through a high-ROI use-case to activate data and accelerate time to business value.

Aimed at maximizing long-term data value through extensible integrations across Google’s Data Cloud, we’ll design and build a future-proof analytics foundation that extends to reimagined customer experiences, accelerate digital commerce and transform data into AI at scale.

We'll deploy a data modernization blueprint on Google Cloud to enable:

  • Google Cloud Landing zone. Implement IaC with Cloud Foundation Toolkit for secure organizational policy alignment on Google Cloud.

  • Integration. Flexible patterns for ingestion, streaming and transformation with Pub/Sub, Dataflow and Data Fusion.

  • Modern data platform. Open big data processing, federated access and governance controls with BigQuery, Dataproc and Dataplex.

  • Insights. Enable BI anywhere with Looker to visualize your customer journey across Google Analytics and GMP, and enrich operational and 1P CRM data.

  • Activation. Extensive, pluggable integrations for Discovery AI for Retail Search, CCAI platform modernization and accelerating data into AI applications.

What to expect

The six-week Data Activation Launchpad will align to a north star and KPIs to continuously prove value and enable cross-domain data value for stakeholder adoption of sustainable data cloud modernization.

Phase 1: Align

Discovery workshop with north star roadmap for immediate workloads honed to long-term modernization and enablement goals

Phase 2: Define

Custom blueprint with well-defined reference patterns to iteratively unlock data value across key ecosystem integration points

Phase 3: Deploy

Scalable data pipelines and analytics access on Google Cloud with extensive integrations to client environment, systems and consumer targets

Phase 4: Activate

Key use-case applications designed to leverage near-real-time BI and data into ML, digital commerce, customer experience and AI applications

Phase 5: Optimize

Project review and TDD aimed to scale data product utilization and lower TCO with Lakehouse and Data Mesh designs to serve digital transformation goals

Outcomes

The launchpad will deliver measurable uplift and ROI to bridge data silos into strategic data products aligned with intelligent experiences through the following outcomes:

  • Repeatable infrastructure and roadmap to adapt any type, scale, location and use of data use-case with Google Cloud’s Lakehouse and Data Mesh capabilities.

  • Activate and extend your data platform with integrations through BigQuery Omni, Data Fusion and Dataplex.

  • Empower self-service and embedded data applications across the customer lifecycle with Looker's cloud-native BI platform.

  • Accelerate AI using BigQuery ML and enable predictive applications with omnichannel retail and CCAI applications.

  • Extensive integrations between BigQuery and Vertex AI to experiment, build and deploy models at scale.

Learn how we can help you harness the power of Google Cloud

Contact us

 

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Data foundation assessment: Get your five-point data maturity score

Look at your data foundation before you leap into generative AI. As tempting as it is to jump ahead with generative AI initiatives, how do you know whether your organization’s data foundation — including people, process and technology — can support your ambitions?

Complimentary one-hour data foundation consultation

Book it now

The challenge

In the past year or so, many organizations have effectively navigated the generative AI landscape. They are exploring the potential of this transformative technology, overcoming challenges and achieving successes.

While these early adopters vary greatly in terms of size, industry and how they’ve applied generative AI, they all have this in common: a sound data strategy combined with a reliable and governed data foundation.

But other organizations have not been so successful, due to these obstacles:

  • Inadequate technology to provide advanced data capabilities

  • Limited or non-existent data-driven innovation

  • Gaps in data roles, skills and processes

  • Anxiety around governance, security and compliance

When it comes to data maturity, how does your organization stack up?

Our solution

A no-cost one-hour data foundation discovery consultation

Valtech has curated a data foundation assessment to help organizations like yours gain a baseline understanding of data maturity across these five dynamics:

  • Value. How well you manage to extract value from data

  • People. The coverage you have across roles, responsibilities and skills

  • Process. The degree to which data is improving employee jobs and customer experiences

  • Data. How well data is governed and quality managed

  • Technology. Whether you have the systems needed to reliably turn data into insight

 

Following the consultation, you will receive:

  • Your overall data maturity score and classification rating (chaotic/reactive/stable/proactive)

  • A visual representation of your scoring across five data foundation dynamics

  • An executive summary

  • An anonymized benchmarking report of aggregated data maturity trends

Valtech’s data experts will continue to be available to discuss your results in more detail and help you create an action plan to create an optimal data foundation to support your organization’s generative AI initiatives.

Get your data maturity score

Book your consultation

 

Frequently asked questions

What is a data maturity assessment?

A data maturity assessment is a comprehensive evaluation of your organization's ability to effectively manage and leverage data. It assesses your data strategies, infrastructure, governance, skills and technology across five key dimensions (value, people, process, data and technology). This assessment helps you understand your current data maturity level, identify areas for improvement and develop a roadmap for building a stronger data foundation that supports your generative AI ambitions.

Why do we need a data maturity assessment?

A data maturity assessment offers several benefits:

  • Identify challenges and opportunities. Understanding your current strengths and weaknesses in data management will help you prioritize improvement areas.

  • Benchmark your progres. Compare your data maturity level against industry standards and track progress over time.

  • Support generative AI initiatives. Ensure your data foundation is ready for successful GenAI implementation.

  • Improve decision-making: Data-driven insights from the assessment inform better choices about data investments and strategies.

How do you measure data maturity?

Valtech’s data foundation assessment uses a combination of questionnaires, interviews with key stakeholders and analysis of your existing data infrastructure and processes. This holistic approach provides a comprehensive view of your data maturity level.

What are the four stages of data maturity?

Several data maturity models exist, but the framework used at Valtech categorizes organizations into four stages: chaotic, reactive, stable and proactive. Your assessment report will provide your specific classification and breakdown across the five key dimensions.

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