Banking & FinanceA leading financial institution
AI-Powered eKYC for Digital Identity Verification
Faster customer onboarding and stronger compliance with a cross-platform eKYC system.
The challenge
Manual KYC checks were slow and error-prone. They delayed onboarding, raised compliance risk and frustrated customers on mobile and web.
What we built
An AI eKYC system that verifies identity automatically, securely and in real time.
- Facial recognitionMatches a live selfie with the ID photo.
- OCRReads key details from ID documents.
- Liveness detectionConfirms a real person is present.
- Real-time validationFlags mismatches instantly.
- End-to-end encryptionKeeps data handling compliant.
- Mobile and webWorks across devices.
The impact
- 70% reduction in verification time
- Drastic drop in human errors through automation
- Improved compliance and secure data practices
- Faster onboarding, lifting customer acquisition and satisfaction
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Human Behavioural ScienceGDRFA, Dubai Airport Terminal 3
Emotion Detection and Happiness Index at Dubai Airport
Real-time insight into how millions of travellers feel, without slowing the airport down.
The challenge
Surveys disrupted operations and gave no real-time insight into passenger satisfaction, while privacy ruled out conventional approaches.
What we built
An on-premises emotion detection system that reads passenger sentiment in real time across high-traffic areas.
- Emotion recognitionIdentifies eight core emotions from facial expressions.
- Multi-passenger trackingMonitors up to five passengers at once.
- Happiness indexInstant satisfaction metrics and reports.
- Insights dashboardTrends for proactive service.
- On-premisesAll processing stays inside airport infrastructure.
The impact
- 40% faster response to passenger concerns
- 25% improvement in passenger satisfaction scores
- 60% of potential complaints resolved before escalating
- Less wait stress through better staff deployment at peak times
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ManufacturingAutomotive, electronics and industrial manufacturers
Real-Time Defect Detection on the Production Line
Computer vision that catches defects in seconds across welding, casting and moulding.
The challenge
Manual inspection couldn’t keep pace with production. Sample checks missed defects, leading to complaints, recalls and delays.
What we built
A computer vision system that monitors quality continuously without slowing production.
- Deep learning visionTrained on thousands of defect patterns.
- Precise locationBounding boxes pinpoint and classify each defect.
- Live quality metricsTracks defect rates as they happen.
- Multi-processWelding, casting and moulding.
- Adaptive learningImproves as it sees new defects.
The impact
- 85% reduction in defects reaching customers
- 60% faster detection than manual inspection
- 40% increase in production efficiency
- Real-time corrective action before defective batches are made
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ManufacturingManufacturing company
Quality Control and RFP Automation for Manufacturing
One AI system for defect-free production and faster, more accurate bids.
The challenge
Slow RFP responses cost contracts, and imprecise manual inspections missed defects and delayed production.
What we built
AI automation covering both quality control on the floor and proposal generation for sales.
- Real-time defect detectionContinuous quality control during production.
- Automated RFQ processingExtracts key details and drafts precise bids.
- Predictive analyticsForecasts production issues and market trends.
- AI inspectionReplaces manual quality checks.
The impact
- 70% reduction in RFP response time
- 35% increase in proposal accuracy and consistency
- Streamlined sales cycles and stronger competitiveness
- Greater precision and speed through automation
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ManufacturingTeknovel, New Zealand
Honey Yield and Revenue Forecasting
Predictive analytics telling a premium Manuka Honey producer when to harvest and what to expect.
The challenge
Harvest timing was largely guesswork, costing quality and revenue. Volatile prices made forecasting hard and profitability was calculated by hand.
What we built
A predictive analytics application combining historical yields, weather and market prices.
- Harvest timingPredicts peak honey quality periods.
- Yield estimationForecasts yield from environment and hive conditions.
- Revenue forecastingLinks yield predictions to live market prices.
- Automatic profitabilityCosts, yields and prices calculated for you.
The impact
- 70% better forecasting precision for harvest timing
- Less variation in honey quality
- Significant reduction in product waste
- Streamlined operations with automated profitability
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DefenceDRDO and defence industry partners
Radar and Signal Simulation for Defence
Secure, real-time modelling of radar interactions with moving objects.
The challenge
Existing tools couldn’t simulate complex radar scenarios in real time, connect with Matlab and STK, or meet military-grade security.
What we built
A standalone, offline radar simulation application built around DRDO’s security requirements.
- Radar modellingSimulates moving objects across many scenarios.
- Tool integrationConnects with Matlab and STK via Python.
- Real-time engineInstant results for faster decisions.
- Military-grade securityStandalone and fully offline.
The impact
- Military-grade security keeping data confidential
- Seamless tool integration with no workflow bottlenecks
- Better radar evaluation across diverse scenarios
- Stronger readiness for routine and critical operations
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HealthcareHealthcare content platforms
Gidebot: AI Summaries for Medical Articles
A chatbot that summarises long medical articles and answers questions about them instantly.
The challenge
Readers struggled to find key information in lengthy medical articles, which slowed decisions and hurt engagement.
What we built
Gidebot, a RAG chatbot powered by Llama 3.1 that plugs into healthcare websites.
- Instant summariesInteractive summaries in real time.
- Ask questionsTargeted answers from the article.
- Key highlightsImportant sections highlighted and explained.
- Easy integrationFits into existing websites.
The impact
- 50% faster access to information
- Less time searching medical content
- Higher engagement through question-based exploration
- Clearer understanding with simple summaries
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HealthcareClinARA (Clinical Research Accelerator)
ClinARA: AI Accelerator for Clinical Trials
AI automation for patient recruitment, drug scheduling and research queries.
The challenge
Slow patient recruitment, inefficient drug scheduling and manual query handling kept researchers away from the science.
What we built
A clinical research platform with AI models trained on trial protocols.
- Predictive recruitmentForecasts recruitment success and strategy.
- Drug schedulingOptimises supply across trial sites.
- Query handlingInstant answers to protocol questions.
- Live trial insightsReal-time recruitment and performance metrics.
The impact
- Reduced recruitment delays with predictive modelling
- Faster handling of research queries
- Optimised supply chain with automated scheduling
- More researcher time for core science
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InsuranceMotor insurance company
Motor Insurance Claims Automation
Claims handled end to end, from identity check to fraud screening.
The challenge
Long claims processes frustrated customers, manual checks caused errors and disputes, and fraud increased losses.
What we built
An AI claims application that automates submission to approval and fits existing insurance systems.
- User verificationAutomatic checks from ID or driving licence.
- Car scanningComputer vision detects vehicle damage.
- Automatic submissionDamage data flows straight into claims.
- Fraud detectionSpots suspicious patterns in past claims.
The impact
- Faster claims with shorter verification and approval
- Fewer human errors through automation
- Better fraud prevention, reducing losses
- Smoother experience for customers
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DigitalDemokrato
Survey Form Generation and Validation
Survey forms created instantly from documents, with responses validated automatically.
The challenge
Converting DOC files into XML and Excel forms by hand, and validating responses manually, caused errors and delays as volumes grew.
What we built
AI automation for the whole survey workflow, from form creation to response validation.
- File conversionDOC files turned into XML and Excel forms.
- Instant formsSurveys generated straight from source documents.
- Parallel validationResponses checked and categorised automatically.
- End to endOne automated flow from creation to validation.
The impact
- Faster form creation and validation
- Far less manual work and fewer errors
- Scales to any number of surveys
- Real-time visibility into data collection
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CybersecurityInCyber
Insider Threat Detection for a Financial Institution
Machine learning that spots risky user behaviour before data is compromised.
The challenge
Insider threats went unnoticed until damage was done, such as users opening files outside their role or long-untouched files.
What we built
An insider threat solution that analyses user behaviour and file access in real time.
- Behavioural analysisDetects unusual access patterns.
- Real-time alertsSecurity teams notified immediately.
- Automated monitoringContinuous surveillance with less manual work.
- Easy integrationWorks with existing security tools.
The impact
- Early detection of insider risks
- Fewer false alerts through machine learning
- Smarter prioritisation for security teams
- Stronger security posture overall
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Oil & GasADNOC
BOP Pressure Chart Analysis for Oil Rigs
Reading blowout preventer pressure charts in 30 seconds instead of 40 minutes.
The challenge
Engineers spent up to 40 minutes reading each circular pressure chart by hand, slowing safety-critical work and risking errors.
What we built
A computer vision solution that reads circular charts automatically and converts them into clear linear graphs.
- Chart readingAI interprets circular pressure charts.
- Linear graphsConverts charts into an easy-to-read format.
- Instant extractionValues ready in 30 seconds.
- Built for rigsTailored to BOP monitoring.
The impact
- 98.75% reduction in chart reading time, from 40 minutes to 30 seconds
- Faster decisions with instant data access
- Lower risk of human error
- Higher productivity and accuracy
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Energy & UtilityEnergy and utility company
Offline Safety and Maintenance App for Remote Sites
A mobile AI app that keeps workers safe and equipment running, even without internet.
The challenge
Remote sites with poor connectivity needed strong safety checks and early warning of equipment failure, which traditional tools couldn’t deliver.
What we built
An offline-capable mobile app optimised with TensorFlow Lite.
- Facial recognitionOnly authorised staff enter sensitive areas.
- Safety gear detectionChecks protective equipment is worn.
- Switchgear monitoringSpots early signs of equipment failure.
- Thermal monitoringAlerts on overheating.
- Works offlineNo internet needed on site.
The impact
- Improved worker safety with gear monitoring
- Early detection of equipment issues, preventing downtime
- Faster response to maintenance issues
- Better long-term planning from maintenance history
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GamingBaren
Horse Health and Stability Analysis for Race Prediction
More accurate race predictions from horse health, agility and rider data.
The challenge
Traditional race models ignored horse health, agility and rider influence, which limited accuracy and user engagement.
What we built
A machine learning system that combines physical metrics from horse movement with rider attributes.
- Horse health assessmentAnalyses angles, length and agility.
- Rider attributesFactored in alongside the horse.
- Multi-variable analyticsCombines all factors in one model.
- Real-time predictionsUpdated as conditions change.
The impact
- More reliable race predictions
- Higher user engagement through real-time insights
- Automated, accurate race forecasts
- A more engaging gaming experience
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GamingOCS (Online Collectibles Services)
Collectibles Grading and Pricing in Under Four Seconds
AI that identifies, grades and prices gaming collectibles with expert-level accuracy.
The challenge
Manual grading was slow, inconsistent and couldn’t keep up with volume, while the market expected instant results.
What we built
Computer vision models combined with an LLM that analyse both sides of each collectible.
- Image analysisDetects and segments the front and back.
- LLM gradingCombines vision and language models.
- Instant pricingValuations from market and historical data.
- Under four secondsComplete assessment in real time.
The impact
- Under four seconds for grading and pricing
- Accuracy comparable to expert human graders
- Scales to large daily volumes
- Immediate results for customers
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FashionFashion retail client
Virtual Try-On for Outfits, Hairstyles and Makeup
Lifelike digital style transformations that let shoppers try looks instantly.
The challenge
Shoppers couldn’t picture new looks without trying them on, and existing tools weren’t interactive or realistic.
What we built
A deep learning and computer vision platform for fast, realistic virtual try-ons.
- Virtual style transferTry on outfits, hair and makeup.
- Facial point detectionAccurate makeup and hairstyle placement.
- Image segmentationPrecise clothing fit.
- Fast transformations3–5 styles in under 30 seconds.
The impact
- 3–5 styles tried in under 30 seconds
- Higher engagement with more items explored
- Faster decisions through personalisation
- No in-store fitting needed
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RetailRetailBox
Automated Stock Counting and Procurement
Shelf images turned into accurate stock counts, compliance checks and automatic reorders.
The challenge
Manual stock counting across many stores was slow, error-prone and hard to scale, hurting inventory and marketing compliance.
What we built
Retail Sense, a web and mobile AI solution that reads shelf photos and manages stock.
- Stock countingCounts product facings from shelf images.
- Marketing complianceTracks visibility and brand placement.
- Automatic reordersReplenishment triggered at set levels.
- Continuous learningAnnotation tools keep improving accuracy.
The impact
- Drastically less manual inventory work
- Real-time accuracy and fewer stockouts
- Consistent marketing compliance across stores
- Faster decisions from live stock data
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Human ResourcesFuture Look ITC, Riyadh
SmartHire: AI Hiring Platform in Arabic
Automated candidate evaluation with a fully Arabic interface.
The challenge
Screening candidates by hand was slow, and the team needed an Arabic interface while keeping resumes and interviews in English.
What we built
SmartHire, an AI hiring platform that parses resumes, runs psychometric assessments and scores candidates.
- Resume parsingExtracts and scores skills automatically.
- Video psychometricsAssesses behaviour and soft skills.
- Candidate scoringCombines all evaluations in one score.
- Arabic localisationFully localised for recruiters and candidates.
The impact
- Faster initial candidate screening
- More accurate assessment with psychometrics
- Higher recruiter productivity
- Better hiring decisions from AI insights
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