CloudFactory Limited

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CloudFactory provides an enterprise AI platform and AI consulting, combining automation with a managed human-in-the-loop workforce to create high-quality AI datasets, train and align models, and validate/correct inference so AI can be trusted in production.

Reading, United Kingdom
Aerial Inspection
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Agriculture
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CloudFactory LimitedCloudFactory Limited

About CloudFactory Limited

About CloudFactory Limited

CloudFactory is an AI consulting and AI platform provider focused on helping organizations develop, deploy, and operate trusted AI in production. The company combines AI-powered technology, automation, and a managed human-in-the-loop workforce to turn messy, unstructured, or incomplete data into high-quality datasets; to fine-tune and validate models; and to provide inference evaluation, validation, and error handling where reliability matters. Founded in 2010 in Kathmandu, Nepal, CloudFactory was built on the belief that talent is equally distributed, but opportunity is not. Over time it developed a repeatable approach to hiring, training, and managing a global AI workforce and delivering accountable, high-quality outcomes for customers. CloudFactory states it has helped over 700 clients build high-quality datasets and high-performing models and launch AI solutions. Following its acquisition of Hasty (an inference-centric AI data platform), CloudFactory positions itself as expanding beyond data labeling to support the full AI lifecycle, including inference-centric operations and continuous improvement through human-in-the-loop feedback. The platform is organized into modular engines—Data Engine, Training Engine, Inference Engine, and AI Engine—paired with enterprise AI consulting services (advisory, discovery, design & build) to move AI from idea/pilot to scalable production with governance, monitoring, and oversight.

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Solution Details
Industries
Aerial InspectionAgricultureAgTech
Customer Regions
UKUS
Key Features
Active LearningAPI IntegrationClient Success Managers

Products

Showcase the products and solutions offered by CloudFactory Limited

AI Consulting

Consulting services spanning advisory/strategy, discovery (blueprint), and design & build to translate AI vision into scalable, secure, and compliant AI implementations.

AI strategy

Discovery workshops

Solution design

Best for:CIO

Pricing

Not listed

AI Engine

Operate AI in production with continuous monitoring, observability, risk/incident response, infrastructure optimization, and governance enforcement across cloud or on-prem environments.

Model monitoring

Observability

Risk management

Best for:CTO

Pricing

Not listed

AI Platform

Enterprise-ready platform that integrates data preparation, model lifecycle management, inference oversight, governance, and scalable deployment for AI applications.

Lifecycle management

Inference oversight

Governance

Best for:AI Leader

Pricing

Not listed

Data Engine

Data collection, curation, and annotation services to deliver AI-ready datasets with diversity, metadata enrichment, and AI-assisted pre-labeling.

Data collection

Data curation

Data annotation

Best for:Data Scientist

Pricing

Not listed

Inference Engine

Continuous inference validation, error handling, and evaluation to maintain trust, auditability, and performance in production AI predictions.

Inference validation

Error handling

Inference evaluation

Best for:MLOps Lead

Pricing

Not listed

Training Engine

Model training support including prompt engineering, supervised fine-tuning, red teaming, and reinforcement learning from expert feedback to improve safety and alignment for high-stakes AI.

Prompt engineering

Fine tuning

Red teaming

Best for:ML Engineer

Pricing

Not listed

Historical Performance

Tracking the performance of the solution based on what's most important to you
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Business Case

Achieved 137% EBITDA Increase and Reduced Nurse Turnover 44%

A healthcare-focused initiative sought to improve patient care while strengthening financial performance. The customer needed to better understand nurse experiences to address operational and staffing challenges. These issues had impacted both care delivery and financial outcomes. The customer learned from nurses and applied AI-powered insights to identify improvement opportunities. The initiative implemented operational and staffing changes based on those insights. The approach aligned workforce decisions with patient care and financial objectives. The initiative delivered measurable improvements in financial performance and workforce stability. EBITDA increased by 137%. Nurse turnover decreased by 44%. These results supported stronger operations and improved ability to maintain patient care quality.

Key Results
  • 137% EBITDA increase
  • 44% reduction in nurse turnover

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Feb 18, 2026
Self Reported
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Business Case

Achieved 50% Better Driver Retention

MV Transportation

MV Transportation faced significant driver turnover and needed measurable improvements across the operator lifecycle. The organization required a way to strengthen retention while maintaining a strong focus on safety. It needed results that could be tracked and sustained over time. MV Transportation implemented an AI-driven approach to optimize driver retention and safety. The solution was applied across the operator lifecycle to identify opportunities to improve outcomes. This approach helped convert turnover challenges into a more structured, data-informed strategy. MV Transportation achieved a 50% improvement in driver retention. The initiative also reduced safety incidents, though no specific incident reduction figure was provided. These outcomes helped turn turnover into a competitive advantage.

Key Results
  • 50% improved driver retention via AI-driven retention optimization

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Feb 18, 2026
Self Reported
Financial Services Company logo
Business Case

Reduced Turnaround from Days to Minutes with 99% Accuracy

Financial Services Company

A financial services company faced slow document transcription that took days to complete. They needed to speed up turnaround without sacrificing quality. The existing process could not meet the required pace and reliability. They implemented a managed workforce to accelerate document processing and verification. This approach increased the capacity to transcribe documents quickly while maintaining quality controls. Verification steps were used to ensure outputs met the required standards. Turnaround time improved from days to just minutes. The work was completed with 99% accuracy. Faster processing enabled the company to handle document transcription more efficiently while maintaining high quality.

Key Results
  • 99% accuracy via managed workforce
  • Reduced turnaround from days to minutes via accelerated processing and verification

Skills

Utilities
Industry

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Feb 18, 2026
Self Reported
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Business Case

Delivered 24,000 Labeled Images in 6 Months

Medical AI Company

A medical AI company needed to rapidly create labeled training data to stay ahead of the curve. They faced pressure to build a sizable dataset within a fixed timeline. They needed labeled data quickly to support their medical AI efforts. They scaled image annotation production to increase labeling capacity. They used this scaled approach to create the training dataset within the required timeframe. They implemented a process focused on producing labeled images efficiently. They labeled 24,000 images in 6 months. They built a sizable dataset on a fixed timeline. They met the timeline needed to support their training-data goals.

Key Results
  • 24,000 images labeled
  • 6 months timeline completed

Skills

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Feb 18, 2026
Self Reported
Bizly logo
Business Case

Achieved Expansion to Over 18,000 Venues

Bizly

Bizly needed more capacity to broaden coverage of its event planning platform. The existing setup was not sufficient to support the required data operations at the needed pace. This limited how quickly the platform could expand its venue listings. Bizly implemented a dedicated workforce to support its data operations. This added the operational capacity required to handle the work involved in expanding platform coverage. The approach focused on accelerating expansion by scaling execution through dedicated support. With the additional capacity in place, Bizly accelerated its expansion efforts. The platform scaled its coverage to over 18,000 venues. This outcome reflected the increased ability to execute data operations at scale.

Key Results
  • Over 18,000 venues expanded

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Project Details

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Feb 18, 2026
Self Reported
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Business Case

Achieved Annual Assets Advertised Growth from $2B to $5B

Tractor Zoom

Tractor Zoom sought to scale its agtech marketplace operations through better data enrichment. The company faced a need to improve data enrichment capacity to support growing marketplace demands. Without expanded enrichment capability, higher marketplace throughput was harder to sustain. Tractor Zoom implemented an expanded data enrichment capability to improve its marketplace operations. The enrichment work was used to better support listings and overall marketplace throughput. This approach increased the company’s ability to handle greater operational volume. With the expanded data enrichment capability in place, Tractor Zoom supported higher marketplace throughput. The company grew from advertising $2B in assets annually to $5B. This growth reflected the impact of improved data enrichment on marketplace scale.

Key Results
  • $2B to $5B annual assets advertised growth via expanded data enrichment capability

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Feb 18, 2026
Self Reported
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Business Case

Achieved 8x Faster Smart City GTM Mission

Allvision

Allvision needed to execute an ambitious smart city go-to-market plan on an accelerated timeline. They faced significant computer-vision data needs while working against a compressed schedule. They required a way to move faster without compromising their go-to-market objectives. Allvision implemented a flexible partnership to support their computer-vision data needs. The engagement was structured to adapt to changing requirements and timelines. This approach helped Allvision accelerate execution of their smart city go-to-market plan. Allvision sped up execution of their smart city go-to-market plan. They achieved their smart city GTM mission 8x faster. The partnership enabled the pace required to meet the accelerated timeline.

Key Results
  • 8x faster smart city GTM mission

Skills

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Feb 18, 2026
Self Reported
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Business Case

Achieved 89% Reduction in Unassisted Bed Exits

Ocuvera

Ocuvera aimed to advance its human-centric healthcare mission by reducing unassisted bed exits. Unassisted bed exits posed a challenge to patient safety outcomes. The organization needed a way to accelerate progress toward its mission. Ocuvera implemented a supported workflow to accelerate progress toward reducing unassisted bed exits. The approach focused on enabling the team to move faster toward its patient safety goals. The workflow provided support to advance the initiative. The engagement resulted in an 89% reduction in unassisted bed exits. This reduction improved patient safety outcomes. The results helped Ocuvera progress toward its human-centric healthcare mission.

Key Results
  • 89% reduction in unassisted bed exits

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Feb 18, 2026
Self Reported
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Business Case

Achieved 3.5x More Damage Identified and Saved 50%+ Workforce Costs

Heavy Equipment Rental

A heavy equipment rental client needed to detect more damage in its fleet while accelerating processing. Existing methods required significant labor and slowed turnaround. The client also needed to reduce the burden on its workforce without sacrificing detection quality. The client implemented custom AI with human-in-the-loop workflows. These workflows combined automated detection with human review to improve accuracy and speed. The approach streamlined how damage was identified and processed. The implementation delivered measurable improvements across identification, turnaround time, and labor costs. The client identified 3.5x more damage than before. Turnaround became 66% faster, and workforce costs were reduced by more than 50%.

Key Results
  • 3.5x more damage identified via custom AI plus human-in-the-loop workflows
  • 66% faster turnaround via custom AI plus human-in-the-loop workflows
  • 50%+ workforce cost savings via custom AI plus human-in-the-loop workflows

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Feb 18, 2026
Self Reported
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