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AI & Data Hub & Methodology

Engineering Intelligence. Activated Insight. Industrialised AI.

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Our Ethos

Proventeq’s AI & Data Hub fuses data science, analytics, platform engineering, and governance into a single strategic capability ready to transform how your business uses data to create value. The AI & Data Hub sits at the heart of your intelligent enterprise. Within the industry we unify:

  • Data Analysis: Insights, dashboards, KPIs, and business reporting
  • Data Science: Forecasting models, LLM prompts, AI service delivery
  • Engineering Foundations: Pipelines, governance, metadata strategy
  • Operational AI: Observability, trust, scalability, and ethical alignment

We deliver value across Microsoft, AWS, GCP, Databricks, Snowflake, and hybrid data estates with platform agnostic methods and vendor-neutral design.  A high-performance AI Centre of Excellence built to accelerate enterprise-wide adoption of intelligent systems. We provide outcomes delivered by AI strategists, data scientists, and machine learning engineers, the Hub delivers targeted experimentation, model development, and production grade deployment at scale. This is not commodity AI it is enterprise-grade Ai, Bi, orchestration of data, models, and governance tailored to your industry use cases. This COE’s strategic purpose is to convert fragmented AI ambition into integrated, scalable intelligence frameworks that deliver real-world business outcomes.

Client Outcomes

Our Digital Experience Hub is designed to deliver measurable impact from day one. By unifying systems, automating workflows, and embedding intelligence, we enable organizations to move faster, work smarter, and deliver better customer experiences. The result is reduced friction, accelerated service delivery, and a digital ecosystem that continuously adapts to business needs.

Accelerate AI Execution

While ensuring every deployment is governed, secure, and compliant. A vendor-neutral architecture avoids lock-in, optimises ROI, and embeds governance workflows that maintain operational integrity at scale.

Trusted Insights

Deliver trusted, bias-aware insights from governed, high-quality datasets, enriched with unified metadata and lineage tracking. Ethical AI principles and data stewardship policies ensure analytics outputs are transparent, explainable, and fit for decision-making.

Cohesive Integration

Integrate AI seamlessly into existing systems across Azure, AWS, GCP, or hybrid environments using a future-ready, modular platform. Built-in governance frameworks and ethics checks ensure innovations comply with global standards without slowing delivery.

Governed Risk Reduction

Reduce security, compliance, and reputational risks through embedded governance, automated policy enforcement, and real-time monitoring. Ethical AI controls prevent misuse, while consistent permissions and audit trails maintain trust with regulators and stakeholders.

Our ML & LLM Methodology

Trusted AI Delivery with MLOps & LLMOps. Our MLOps and LLMOps framework provides a structured, repeatable, and governance-ready lifecycle for deploying prediction models and large language models at scale including Copilot and Retrieval Augmented Generation (RAG) scenarios. Whether deploying prediction models or LLMs (e.g. for Copilot scenarios), our LLMOps framework ensures ethical, secure, and scalable delivery. We deploy AI solutions using a full-lifecycle model that ensures traceability, observability, and production-grade stability.

Create

Define business-aligned model and prompt objectives, prepare high-quality governed datasets, and select ML or LLM architectures with embedded bias mitigation and security controls.

Validate

Test and refine models for accuracy, fairness, and robustness while applying prompt validation, token privacy checks, and explainability audits to ensure ethical and compliant AI behaviour.

Package

Bundle validated models, prompts, and metadata into secure, version-controlled artifacts, integrating CI/CD pipelines and grounding prompts with Retrieval Augmented Generation (RAG) datasets for reliability.

Deploy

Roll out AI solutions using secure, policy-driven deployment frameworks that integrate seamlessly with enterprise platforms, applying encryption, access control, and governance mappings from day one.

Monitor

Continuously track telemetry, usage analytics, and model drift while enforcing compliance and ethical guardrails, with automated alerts to trigger retraining or prompt optimisation when needed.

 Improve

Retrain and fine-tune models based on monitored feedback, optimising prompts and governance alignment to enhance accuracy, transparency, and scalability over time.

Our Structured Data Insight  Methodology

Turning raw data into actionable insight requires more than just visualisation it demands a disciplined process that ensures every decision is based on accurate, relevant, and well governed information. Our 8-stage data analysis methodology guides organisations from problem definition through to continuous improvement, creating insight engines and dashboards that are trustworthy, reusable, and business ready. This approach blends data quality management, statistical rigour, and user focused design, ensuring analytics deliver measurable impact across the business.

Align on the Challenge

Collaborate with stakeholders to clearly frame the business challenge, define objectives, and establish success measures before any analysis begins.

Pinpoint Data

Identify and catalogue the relevant systems, tables, and repositories that hold the information required to address the problem, ensuring full visibility of available assets.

Clean the Data

Remove duplicates, resolve inconsistencies, and fill gaps, transforming raw datasets into accurate, reliable, and analysis-ready inputs.

Explore Variables

Apply statistical techniques to evaluate data structures, relevance, and relationships, uncovering patterns and identifying any critical gaps or anomalies.

Address the Problem

Translate business requirements into actionable analytics by defining the business logic, selecting the right modelling techniques, and preparing the insight framework.

Design Reports

Design Reports – Create clear, visually engaging dashboards or reports tailored to the audience, delivering the right level of detail and context for informed decision-making.

Deploy Regular Refresh

Implement automated, scheduled pipelines that keep dashboards and reports up to date, ensuring stakeholders always have the latest and most accurate information.

Monitor & Enhance

Continuously track usage, impact, and relevance, refining datasets, logic, and visualisation to adapt to evolving business needs and opportunities.

What Our Clients Say

“QUOTE.”

Gijs Boudens
Bionical Emas
Migration from IBM FileNet to SharePoint Online

How the Hub Delivers Impact

From raw data to enterprise-ready AI, our capabilities span the full lifecycle ensuring every insight, model, and integration delivers measurable business impact. We design and build resilient data foundations, enable decision-makers with automated analytics, and embed governance to ensure compliance at scale. Our delivery approach blends AI innovation with platform flexibility, integrating best-in-class tools such as Microsoft Fabric, Databricks, and Salesforce with operational excellence in MLOps and LLMOps so you can move from experimentation to production faster, with lower risk and higher return.

Data Engineering

Lakehouse design, metadata pipelines, structured + unstructured integration Creates a unified, scalable data foundation that reduces silos, accelerates time-to-insight, and enables AI-ready datasets across the enterprise.

Analytics Enablement

Role-based dashboards, Power BI/Tableau frameworks, insight automation Empowers decision-makers with relevant, real time insights tailored to their roles, driving faster and more informed strategic actions.

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Data Governance

Lineage (Purview / Collibra), RBAC, policy enforcement, audit-ready controls Ensures data is accurate, compliant, and trustworthy, reducing regulatory risk while enabling secure, enterprise-wide data sharing.

Ops & Observability MLOps

LLMOps, cost tracking, usage alerts, feature store tuning Maintains AI performance, cost efficiency, and governance in production through proactive monitoring, optimisation, and operational automation.

AI & ML Delivery

Forecasting, document AI, LLM search, prompt orchestration Accelerates AI adoption by delivering ready-to-use, high-value models and AI workflows that solve specific business problems.

Platform Integration

Microsoft Fabric, Databricks, Azure ML, Salesforce, Snowflake, AWS Sagemaker Maximises ROI by connecting best-in-class platforms into a cohesive ecosystem, enabling seamless data flow and cross-application intelligence.

The Value of the Digital Engineering Hub 

The Digital Engineering Hub is designed to maximise the value of your technology investments by unifying platforms, embedding intelligence, and enabling scalable, composable services. Each capability works in concert to break down silos, modernise experiences, and deliver measurable business outcomes. From AI-powered insights to seamlessly integrated workflows, the Hub ensures your organisation can adapt, scale, and lead in a digital first, compliance ready world.

Modernisation & Integration

Seamlessly integrate SharePoint, Dynamics 365, Salesforce, Power Platform, and existing portals into a coherent digital estate. Reduce cross-platform friction, accelerate user adoption, and eliminate duplicate systems cutting integration overheads by up to 30%.

Data-Driven Decision-Making

Leverage AI to augment decision-making, automate classification, surface actionable insights, and improve search through advanced language models. Increase decision accuracy and reduce manual data handling by up to 40%, while ensuring responsible AI use through built-in bias checks and explainability.

User Experience Evolution

Replace siloed apps and static portals with adaptive, intelligent interfaces that evolve alongside your business needs. Improve process agility, reduce change request cycles, and enable faster rollout of customer- or employee-facing services.

 Compliance & Contextual Intelligence

Design experiences where structured and unstructured data, customer records, and AI interfaces work together securely and contextually. Enhance content governance, maintain full audit trails, and deliver insights directly within the tools your teams already use — from CRM screens to productivity apps.

 Scalable Architecture

Build microservice-based content, workflow, and CRM experiences that can be reused, extended, and scaled across the business. Reduce delivery lead times for new capabilities by 25–40% while keeping governance and security policies consistent across services.

Unlock the Full Potential of Your Digital Estate

Transform how your organisation connects people, processes, and platforms. With the AI & Data Hub, you’ll integrate systems seamlessly, embed AI into every experience, and scale with confidence. From unifying data to delivering intelligent, adaptive services, we help you move faster, work smarter, and stay ahead in an evolving digital landscape.

We are always here to answer your questions.

Proventeq experts will be in touch shortly after your first communication to establish a consultation or demonstration of products and services.

UK & Europe
+44 118 907 9296
Reading Enterprise Centre, Reading, Berkshire,
RG6 6BU, UK
US & Canada
+1 949 403 3180
6500 River Place Blvd., Bldg. 7, Suite 250 Austin,
TX 78730 USA
Asia Pacific

+91 775 698 9979
Unit No 104, Tower S-4,
Cybercity,
Magarpatta City, Pune,
Maharashtra 411013, India

Middle East & Africa

+971 52 5960134
#3, PO Box 73000, Tecom, In5
Tech Innovation Center,
Dubai Internet City, Dubai,
UAE