SDG Group vs Transparity: full comparison for 2026
Last updated: July 2026
Quick verdict
SDG Group (3.7/5) edges ahead of Transparity (3.7/5) overall. SDG Group is the better choice for large enterprises wanting ML-driven analytics embedded within a broader business performance management programme. Transparity is the stronger option for uK enterprises fully standardized on Microsoft Azure wanting AI transformation through a certified Microsoft partner. The right choice depends on your project size, budget, and required tech stack.
SDG Group vs Transparity: head-to-head summary
| Criterion | SDG Group | Transparity |
|---|---|---|
| Founded | 1994 | 2015 |
| HQ | Milan, Italy | United Kingdom |
| Team size | 1000+ | 201–500 |
| Rating | 3.7 / 5 | 3.7 / 5 |
| Best for | Large enterprises wanting ML-driven analytics embedded within a broader business performance management programme | UK enterprises fully standardized on Microsoft Azure wanting AI transformation through a certified Microsoft partner |
| Pricing model | Retainer, dedicated team, fixed project | Retainer, fixed project, dedicated team |
| Min. engagement | $50K | $30K |
| Primary tech stack | Python, Power BI, Tableau | Azure ML, Azure OpenAI Service, Power BI |
| Industries served | Enterprise, Financial Services, Retail, Telecommunications | Insurance, Financial Services, Enterprise, Public Sector |
SDG Group vs Transparity: overview
SDG Group
SDG Group, founded in 1994 and headquartered in Milan, Italy, is a global management consulting firm with roughly 2,000 employees and offices spanning Milan, Barcelona, London, and beyond. SDG Group specializes in business performance management and analytical applications, with machine learning and AI delivered as part of its broader business intelligence and enterprise analytics consulting practice.
Transparity
Transparity, founded in 2015 by David Jobbins and Colin Macandrew, is a UK-headquartered Microsoft pureplay technology partner with around 289 employees. The company delivers AI and machine learning transformation primarily through Microsoft Azure and Copilot technologies via its proprietary AI Factory framework, as demonstrated in its Bordereaux Sync project built with Charles Taylor InsureTech.
Services and capabilities: SDG Group vs Transparity
| Capability | SDG Group | Transparity |
|---|---|---|
| ML model development | ✓ | ✓ |
| Computer vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Generative AI / LLM integration | ✗ | ✗ |
| MLOps | ✗ | ✓ |
| AI strategy consulting | ✓ | ✓ |
| Staff augmentation | ✗ | ✗ |
Tech stack comparison: SDG Group vs Transparity
| Framework / platform | SDG Group | Transparity |
|---|---|---|
| Python | ✓ | N/A |
| TensorFlow | N/A | N/A |
| PyTorch | N/A | N/A |
| AWS | ✓ | N/A |
| Azure | ✓ | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: SDG Group vs Transparity
| Criterion | SDG Group | Transparity |
|---|---|---|
| Minimum engagement | $50K | $30K |
| Engagement models | Retainer, Dedicated team, Fixed project | Retainer, Fixed project, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: SDG Group vs Transparity
| Dimension | SDG Group | Transparity |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Enterprise, Financial Services, Retail | Insurance, Financial Services, Enterprise |
| Best use cases | Enterprise business performance management with an ML component, Large-scale analytical applications for finance or retail clients | Azure-native AI transformation for an insurance or financial services client, Microsoft Copilot deployment across enterprise workflows |
| Typical project type | Retainer | Retainer |
SDG Group vs Transparity: pros and cons
| SDG Group | |
|---|---|
| + | Three decades of operating history since founding in 1994, as a global management consulting firm |
| + | Enterprise-scale delivery capacity of roughly 2,000 staff across multiple European and international offices |
| + | Deep business performance management heritage grounds AI work in measurable business outcomes |
| + | Established relationships with large enterprise clients across multiple industries |
| - | AI and ML is embedded within a much broader business intelligence and management consulting practice, not a dedicated specialization |
| - | High minimum engagement size, inaccessible for startups or small businesses |
| - | Management-consulting-led engagement model may add overhead versus lean engineering-only ML shops |
| Transparity | |
|---|---|
| + | Deep Microsoft pureplay partnership status with a proprietary AI Factory delivery framework |
| + | Demonstrated production case study, Bordereaux Sync, built with Charles Taylor InsureTech |
| + | A decade of operating history since founding in 2015, with a growing UK enterprise client base |
| + | Strong fit for insurance and financial services clients needing Azure-based compliance |
| - | Azure-exclusive positioning is a poor fit for clients on AWS, GCP, or open-source ML stacks |
| - | AI and ML transformation is delivered through a broader Microsoft cloud consulting practice rather than as a standalone ML specialization |
| - | Smaller named public case study base than larger, longer-established firms on this list |
Who should choose SDG Group?
SDG Group is the right choice for large enterprises wanting ML-driven analytics embedded within a broader business performance management programme.
Three decades of management consulting heritage applied to enterprise-scale analytics and AI programmes. Minimum engagement starts at $50K. Works best with clients in Enterprise, Financial Services, Retail, Telecommunications.
Who should choose Transparity?
Transparity is the right choice for uK enterprises fully standardized on Microsoft Azure wanting AI transformation through a certified Microsoft partner.
Proprietary AI Factory framework built specifically around Microsoft Azure and Copilot technologies. Minimum engagement starts at $30K. Works best with clients in Insurance, Financial Services, Enterprise, Public Sector.
Decision matrix: SDG Group vs Transparity
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | SDG Group |
| You need a large dedicated team for an ongoing programme | SDG Group |
| Your budget is at the lower end | Transparity |
| You need specialist depth in a specific vertical | SDG Group |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | SDG Group |
Use case fit: SDG Group vs Transparity
| Use case | SDG Group fit | Transparity fit | Winner |
|---|---|---|---|
| Enterprise business performance management with an ML component | Strong | Strong | Both equally |
| Large-scale analytical applications for finance or retail clients | Strong | Limited | SDG Group |
| Azure-native AI transformation for an insurance or financial services client | Limited | Strong | Transparity |
| Microsoft Copilot deployment across enterprise workflows | Limited | Strong | Transparity |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: SDG Group vs Transparity
SDG Group (3.7/5) is the stronger overall choice for most Machine Learning Development projects. Three decades of management consulting heritage applied to enterprise-scale analytics and AI programmes. It is best for large enterprises wanting ML-driven analytics embedded within a broader business performance management programme.
Transparity (3.7/5) is the better choice when uK enterprises fully standardized on Microsoft Azure wanting AI transformation through a certified Microsoft partner. If your situation matches those criteria, Transparity is a competitive option.
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SDG Group vs Transparity FAQ
Is SDG Group better than Transparity?
SDG Group (3.7/5) scores higher overall, but "better" depends on your use case. SDG Group is better for large enterprises wanting ML-driven analytics embedded within a broader business performance management programme. Transparity is better for uK enterprises fully standardized on Microsoft Azure wanting AI transformation through a certified Microsoft partner.
How do SDG Group and Transparity differ in pricing?
SDG Group uses retainer, dedicated team, fixed project pricing with a minimum engagement of $50K. Transparity uses retainer, fixed project, dedicated team pricing with a minimum engagement of $30K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: SDG Group or Transparity?
Transparity is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.
What are the main differences between SDG Group and Transparity?
SDG Group's primary differentiator is: three decades of management consulting heritage applied to enterprise-scale analytics and ai programmes. Transparity's primary differentiator is: proprietary ai factory framework built specifically around microsoft azure and copilot technologies. They also differ in team size (1000+ vs 201–500), minimum engagement ($50K vs $30K), and primary industries served (Enterprise, Financial Services vs Insurance, Financial Services).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.