Transparity
UK-based Microsoft pureplay partner delivering AI transformation through its AI Factory framework.
What is 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.
Transparity was founded in 2015 and is headquartered in United Kingdom. The firm employs 201–500 people and works primarily with clients in Insurance, Financial Services, Enterprise, Public Sector sectors. Its primary differentiator is: Proprietary AI Factory framework built specifically around Microsoft Azure and Copilot technologies.
Transparity tech stack and services
| Service area |
|---|
| AI Consulting |
| MLOps |
| Data Engineering |
| ML Development |
Transparity use cases
Short answer: Transparity is best suited for UK Azure enterprises, certified Microsoft AI partner.
| Use case |
|---|
| Azure-native AI transformation for an insurance or financial services client |
| Microsoft Copilot deployment across enterprise workflows |
| Bordereaux or regulatory data processing automation |
| UK public sector AI modernization on Microsoft infrastructure |
Transparity pricing
Short answer: Transparity uses a retainer, fixed project, dedicated team pricing approach. Minimum engagement starts at $30K.
| Engagement model | Typical range | Best for |
|---|---|---|
| Retainer | Monthly rate; not public | Ongoing AI engineering |
| Fixed project | From $30K | Well-defined scope |
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
Transparity pros and cons
| Advantages | Things to consider |
|---|---|
| +Deep Microsoft pureplay partnership status with a proprietary AI Factory delivery framework | -Azure-exclusive positioning is a poor fit for clients on AWS, GCP, or open-source ML stacks |
| +Demonstrated production case study, Bordereaux Sync, built with Charles Taylor InsureTech | -AI and ML transformation is delivered through a broader Microsoft cloud consulting practice rather than as a standalone ML specialization |
| +A decade of operating history since founding in 2015, with a growing UK enterprise client base | -Smaller named public case study base than larger, longer-established firms on this list |
| +Strong fit for insurance and financial services clients needing Azure-based compliance |
Transparity vs alternatives
How Transparity compares to the other top Machine Learning Development companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | Startups and mid-market, senior dedicated ML team. | a full-stack ML delivery team (data science, MLOps, QA) inherited from an established parent software company, at boutique-agency pricing. | 4.9 | Full comparison |
| ML6 | Enterprises, production MLOps at scale. | Official OpenAI Services Partner status combined with over a decade of pure-play ML engineering focus | 4.7 | Full comparison |
| Alexander Thamm | DACH manufacturers, AI strategy plus ML delivery. | Deep specialization in industrial and automotive ML use cases across the German Mittelstand | 4.6 | Full comparison |
| Kineo.ai | Mid-market EU businesses, lean AI consulting. | All-Germany team of AI consultants focused specifically on operational-efficiency ML use cases | 4.6 | Full comparison |
| DataRoot Labs | Startups and SMBs, lean ML team, competitive rates. | Founder-led, unfunded boutique with nearly a decade of focused custom ML delivery experience | 4.5 | Full comparison |
| Twistag | Growth-stage brands, senior-only AI agent builds. | Senior-only engineering team with a client roster including well-known global brands | 4.5 | Full comparison |
| Preste | EU companies, custom CV/NLP, French presence. | Dual Paris and Kyiv structure pairing French market presence with dedicated computer vision and NLP engineering delivery | 4.4 | Full comparison |
| STX Next | Companies wanting ML plus large-scale Python engineering. | One of Europe's largest dedicated Python engineering companies, with ML and data practices built on that scale | 4.3 | Full comparison |
| Neoteric | Mid-market companies, gen-AI PoC to production. | Two-decade-old Polish software house with a dedicated generative AI practice and a US-facing New York office | 4.3 | Full comparison |
| Tooploox | Hard ML/AI research-engineering problems. | Research-grade ML engineering with peer-reviewed academic recognition at ECCV 2024, alongside client delivery | 4.3 | Full comparison |
| Opinov8 | Enterprises and startups, AI across cloud engineering. | AI treated as a foundational layer across the entire engineering lifecycle, not a bolt-on service | 4.2 | Full comparison |
| FELD M | EU enterprises, long-established multi-country AI consulting. | Over two decades of operating history since founding in 2002, with organic growth into a five-office pan-European practice | 4.2 | Full comparison |
| WeAreBrain | Companies wanting AI within digital product builds. | Digital product agency DNA combined with a dedicated AI, ML, and intelligent automation practice | 4.2 | Full comparison |
| DATAFOREST | Small/mid-market, data engineering plus ML analytics. | Combined data engineering (ETL) and ML analytics practice with a growing review base | 4.1 | Full comparison |
| Probayes | Automotive, defense, finance — Bayesian modeling expertise. | Over two decades of specialization in Bayesian AI and predictive analytics, predating the current ML and AI boom | 4.1 | Full comparison |
| Digica | Regulated industries, ML plus embedded systems. | Combines ML model development with embedded systems and IoT engineering for regulated hardware-adjacent industries | 4.1 | Full comparison |
| Imaginary Cloud | Companies wanting ML plus strong product design. | Design-led software development studio with AI positioned as a first-class capability, not an afterthought | 4.0 | Full comparison |
| N-iX | Enterprises, ML bundled with large-scale engineering. | Over two decades of engineering scale, over 1,000 staff, with an EU-registered legal entity in Malta | 4.0 | Full comparison |
| Gemmo | Companies wanting a structured, staged AI engagement. | Structured three-phase engagement model of Pathfinder, Implementation, and Optimization, rather than an open-ended consulting retainer | 4.0 | Full comparison |
| Plain Concepts | Azure-standardized enterprises, certified Microsoft AI partner. | Deep Azure-native AI and ML delivery credentials as a Microsoft Gold and AI Partner, plus mixed reality expertise | 3.9 | Full comparison |
| Edvantis | Enterprises, EU-registered nearshore ML engineering. | EU legal registration in Poland combined with substantial delivery scale across Ukraine and Germany | 3.9 | Full comparison |
| CodeLeap | Early-stage startups, fast founder-friendly AI features. | Founder-friendly, speed-oriented delivery model built specifically for startup-stage product timelines | 3.9 | Full comparison |
| High-Tech Systems & Software | Healthcare orgs, AI bundled with healthcare software. | Deep healthcare-sector software specialization in supply chain and telemedicine, with AI and ML layered on top | 3.8 | Full comparison |
| DEPT | Large brands, ML-driven marketing personalization at scale. | Proprietary AI marketing platform, Ada, and global scale of over 4,000 specialists across 30-plus offices, unmatched by any other firm on this list | 4.0 | Full comparison |
| Software Mind | Enterprises, ML bundled with multi-region engineering. | Over 25 years of operating history and enterprise-scale delivery capacity across three continents | 3.8 | Full comparison |
| Innowise | Enterprises, low-cost nearshore staff augmentation with AI. | Very large delivery scale and broad geographic reach, positioned for volume staff augmentation over specialist ML depth | 3.8 | Full comparison |
| BJSS | UK public sector, enterprise-grade AI, proven consultancy. | Over three decades of operating history and deep specialization in regulated, complex enterprise environments | 3.8 | Full comparison |
| Siili Solutions | Nordic/EU enterprises, publicly listed IT consultancy. | Publicly traded on Nasdaq Helsinki, offering financial transparency uncommon among privately held ML firms | 3.7 | Full comparison |
| SDG Group | Large enterprises, ML analytics within BPM programmes. | Three decades of management consulting heritage applied to enterprise-scale analytics and AI programmes | 3.7 | Full comparison |
Transparity FAQ
What is 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.
How much does Transparity charge?
Transparity uses retainer, fixed project, dedicated team pricing. Minimum engagement starts at $30K. A discovery call is required to get project-specific quotes.
What tech stack does Transparity use?
Transparity works with Azure ML, Azure OpenAI Service, Power BI, Microsoft Copilot, .NET. Primary industries served include Insurance, Financial Services, Enterprise, Public Sector.
Is Transparity right for enterprise?
UK Azure enterprises, certified Microsoft AI partner. 201–500 team size. Key consideration: Azure-exclusive positioning is a poor fit for clients on AWS, GCP, or open-source ML stacks.
What are the best Transparity alternatives?
The best alternatives to Transparity depend on your use case. Top options are:
- Tensorway: a full-stack ml delivery team (data science, mlops, qa) inherited from an established parent software company, at boutique-agency pricing.
- ML6: official openai services partner status combined with over a decade of pure-play ml engineering focus
- Alexander Thamm: deep specialization in industrial and automotive ml use cases across the german mittelstand