Turn Data Into Decisions. Put AI To Work.
From fragmented data estates to AI-enabled applications, build the platforms, analytics and intelligence needed to make better decisions and create new ways of working with data and AI solutions designed for modern enterprises.
Data & Ai Capabilities Across The Value Chain
Build The Data Foundation
Make the Information Useful
AI & Machine Learning
Use AI solutions, machine learning solutions and predictive intelligence where they can address specific business or operational requirements — from prediction and classification to intelligent interactions and automation.
Machine Learning | AI/ML Models | Predictive & Prescriptive Analytics | Natural Language Processing | Computer Vision | Intelligent Applications
Apply Intelligence to the Work
Data Engineering & Modernization
Bring fragmented data into structured, governed environments designed for analytics and AI through data modernization services, data engineering services and enterprise data management.
Data Engineering | Data Management | Data Modernization | Data Lakes | Data Warehouses | Data Platforms
Analytics & Business Intelligence
Move from static reporting toward dashboards, analytics and models that help teams understand performance, identify patterns and make informed decisions through data analytics solutions and data analytics services.
Business Intelligence | Data Visualization | Predictive Analytics | Advanced Analytics | Real-Time Analytics
Move from Use Case to AI System
Generative AI & Agentic AI
Design AI-enabled experiences around enterprise data, applications and business processes through generative AI solutions, enterprise generative AI and emerging agentic architectures.
Generative AI | Agentic AI | AI Assistants | Intelligent Search | Conversational AI | AI-Powered Applications
Apply Data & AI To Specific Business Problems
We apply data and AI where it can create measurable business value—from understanding customers and predicting operational needs to automating decisions and transforming how work gets done.
Customer & Marketing Analytics →
Predictive Maintenance →
Application Services →
Recommendation Engines →
Document Intelligence →
Conversational AI →
Computer Vision →
Fraud & Risk Analytics →
Intelligent Automation →
Data & AI Requires More Than An AI Model
The same practice spans data engineering, analytics, machine learning and AI, bringing together data solutions, data management solutions and AI-powered solutions rather than treating the data foundation and AI layer as separate projects.
Data and AI capabilities sit alongside Noventiq's cloud, application, cybersecurity and infrastructure expertise — important when AI needs to operate within an existing enterprise environment through enterprise AI solutions and enterprise data solutions.
The Data & AI practice works across multiple technology vendors and open-source skill sets, rather than being tied to a single data or AI stack, supporting cloud AI solutions, cloud data solutions and flexible technology environments
Multi-Cloud Experience
Depth Beyond & Infrastructure
Proven at Scale
01
02
03
The Noventiq Advantage
100 +
40+
customer data & ai projects
data & ai experts
The Work Happens In Controlled Steps
❶
❷
❸
❹
Define the Decision
What decision, process or experience needs to improve?
Establish the Data
Determine whether analytics, machine learning, generative AI, automation or a combination of approaches fits the use case, including AI automation solutions, intelligent automation services and predictive AI solutions.
Choose the Intelligence
Connect the resulting capability to the applications, users and processes that need it through data integration services and enterprise data integration.
Put it into the Workflow
A meaningful technology strategy starts with the business. We work through the questions that determine where you should invest, what you should change and how you should move forward.
Identify the sources, quality, structure, governance and accessibility required to support it through data governance services, data architecture services and enterprise data architecture.
❺
Measure the Result
Track whether the solution is improving the business outcome it was designed to address.
Data & AI Doesn't Operate In Isolation
Need better data before AI?
Need to connect data sources and applications?
Need governance around AI and data?
Need to operate the resulting data and AI environment?
Have A Data Or AI Use Case In Mind?
Whether you're modernizing your data estate, building an analytics platform or evaluating an AI opportunity, start with the problem you're trying to solve through data and AI consulting services.
Got Questions? Start Here.
Q1. What does Noventiq's Data & AI practice cover?
It spans data engineering services, data modernization services, data analytics solutions, machine learning solutions, AI solutions, generative AI solutions and intelligent applications.
Q4. What types of AI solutions can you implement?
Capabilities include machine learning, predictive and prescriptive analytics, NLP, computer vision, generative AI, conversational AI and intelligent applications, subject to the specific use case and technology environment.
Q2. Do we need to modernize our data before implementing AI?
Not necessarily, but the quality, accessibility and governance of enterprise data can significantly affect what an AI solution can achieve. Data modernization and AI solutions can therefore be an important part of an AI program.
Q6. Can Data & AI Solutions work with our existing applications?
Yes. Integration with applications, APIs and identity systems can form part of AI implementation, making Integration Services a natural companion offering.
Q3. Can Noventiq work with our existing data environment?
Yes. The approach can involve modernizing existing environments, connecting data sources and building new data platforms depending on the use case through enterprise data management, data architecture services and data management solutions.
Have a Specific Challenge in Mind?
Talk to our experts for strategic guidance that connects technology decisions to business outcomes.
Q5. Can you build solutions using Microsoft Fabric?
Yes. Noventiq's reference material identifies Microsoft Fabric data modernization, data integration, engineering, warehousing, real-time analytics and BI among its capabilities.
Q7. How do you approach responsible AI?
Responsible AI solutions can be designed with appropriate governance, security and human oversight, particularly where they operate on sensitive enterprise data or influence business decisions. AI security solutions can also support secure AI adoption.
Q8. Can Noventiq manage the environment after implementation?
Yes. Data and AI implementations can transition into Managed Data & AI Services where ongoing monitoring, management and optimization are required.
Insights That Inform Better Decisions
IT Strategy
Digital Transformation Readiness
Cloud Strategy
Technology Roadmaps
Recommended Services
Cloud Optimization
Cybersecurity
Migration & Modernization
Managed Services
Integration Services
Business Continuity
Looking for The Right Way Forward?
We’re here to help you
assess your current environment, align technology
with business priorities and build
a practical roadmap for the future of work.
About Noventiq
Noventiq (Noventiq Holdings PLC) is a leading global solutions and services provider in digital transformation and cybersecurity, headquartered in London. The company enables, facilitates, and accelerates digital transformation for its customers’ businesses, connecting organizations across a comprehensive range of industries with best-in-class IT vendors, alongside its own services and proprietary solutions. The company’s rapid growth is underpinned by its three-dimensional strategy to expand its market penetration, product portfolio, and sales channels. This is supported by an active approach to M&A, positioning Noventiq to capitalize on the industry’s ongoing consolidation. With around 6,400 employees globally, Noventiq operates in approximately 60 countries with significant growth potential in multiple regions including India, APAC, EMEA, and Latin America.