SDG Group

sdggroup.com

Although SDG describes itself as a global management consulting firm, its documented specialization and customer work support classification as a technology consultancy. Buyers can engage it for advisory work, implementation or both: the evidence includes data architecture, governance, AI development and integration, analytics applications and performance-management systems. Its AI practice, branded Orbitae, explicitly separates strategy from solution development. Public lifecycle and operations terminology does not establish the contractual scope of ongoing managed services. ^[1] ^[2] ^[3] ^[4] ^[5]

Services and delivery

AI strategy advisory

Advisory. Translates business needs into AI initiatives, prioritizes use cases and advises on lifecycle and governance considerations. This is advisory work rather than a commitment to build or operate the resulting systems. ^[2]

Custom AI solution development

Implementation. Designs tailored AI solutions and develops use cases through experimentation, deployment and impact measurement. The practice describes reusable data-science patterns, internal accelerators and MLOps/LLMOps engineering methodologies. ^[2]

AI technology selection and system assessment

Advisory. Assesses AI technologies and vendors through benchmarks, and conducts technical and business audits of existing AI systems. The described scope includes identifying opportunities to integrate isolated machine-learning solutions. ^[6]

AI platform integration and foundation-model engineering

Implementation. Builds AI platform and AIOps foundations, deploys and integrates AI products, and develops or fine-tunes large language models and vision-language models. These are named engineering services, not merely commentary about AI adoption. ^[6]

AI agent and enterprise integration engineering

Implementation. Deploys agent-based architectures across workflows and moves AI prototypes into integrated enterprise systems. The portfolio also describes AI infrastructure design and migration of models, systems and data frameworks. ^[7]

Data engineering and custom data applications

Implementation. Implements warehouses, lakehouses and Data Mesh architectures, optimizes pipelines and develops custom data products. Deliverables include data models, dashboards and applications integrated with existing systems, handling structured and unstructured data. ^[3]

Data strategy advisory

Advisory. Defines data strategy and governance direction to guide how an organization manages and uses its data. Governance implementation is a separate delivery activity within the practice. ^[4]

Data governance implementation

Implementation. Implements governance systems as part of executing data strategy. The practice separately lists analytics literacy, change management and agile project management; those activities should not be confused with AI model engineering. ^[4]

Business intelligence and performance-management systems

Implementation. Delivers harmonized analytical models, visualizations, integrated planning and financial-consolidation automation. The practice also lists process mining. Its systems work addresses reporting and planning requirements rather than constituting general business-strategy consulting. ^[5]

Company details

Technology and platforms

An automotive case documents implementation of a business intelligence platform on AWS, including data-source integration, visual analytics and dealer KPIs. This supports AWS-based analytics delivery, not a blanket claim covering all AWS infrastructure or migration services. ^[8]

The AI portfolio identifies modular accelerators: GENA for assistants, INSIGHTGEN for conversational and narrative BI, DOCWORKS for document workflows, and YOURVOICE for customer-conversation analysis. Standalone licensing terms are not established. Their presence is distinct from the separately evidenced implementation services. ^[7]

Track record

For Aqualia, SDG reports leading a six-phase implementation integrating machine learning and other intelligent services into AqualiaLive. The use cases included water-consumption prediction and anomaly detection for potential leaks, breaks and abnormal consumption. SDG reports hydraulic-performance improvements of up to 8% in some municipalities; this is a case-specific result. ^[9]

For NeuronUP, SDG integrated AI-generated patient-progress narratives using NeuronUP Score metrics and its InsightsGen accelerator. Professionals review and refine the generated draft. SDG reports multilingual output and report-preparation time reductions of up to 70%. Future medical-history and recommendation features are described separately from the implemented reporting functionality. ^[10]

The Granarolo case describes an enterprise data warehouse and BI reporting infrastructure, integration of multiple data sources, distributed sales budgeting and forecasting, and enhancements to financial planning and consolidation. It provides delivery evidence for data and planning systems, but does not establish use of the Tableau software platform. ^[11]

Scope and limitations

The supplied public evidence does not establish pricing, minimum project sizes, detailed staffing, IP ownership, licensing terms or support SLAs.
MLOps, LLMOps and AI operations terminology does not establish round-the-clock managed operations or contractual responsibility for post-launch monitoring.
Case summaries were available, but fuller downloadable case documents were not retrieved. The main success-story directory returned unresolved fields and unavailable content.
The Aqualia summary does not identify algorithms, evaluation datasets, infrastructure vendors or maintenance arrangements. NeuronUP’s hallucination-related assertions are not accompanied by published evaluation evidence in the supplied notes.

Questions to ask

Which advisory, engineering and deployment deliverables will SDG own, and what are the acceptance criteria for each?
What model evaluations, human-review controls and monitoring are included for the proposed AI use case?
Which components require SDG accelerator licenses or third-party licenses, and who owns custom code and model adaptations?
Can SDG provide references using the proposed platform and a comparable operational or planning workflow?
What handover, remediation, maintenance and post-launch support obligations will be contractual?

Overview