Hydrogen Digital Product Passport (H2DPP)
DeepCloudLabs delivers AI-powered DPP solutions that combine blockchain and data analytics for complete hydrogen traceability. Our platform provides end-to-end visibility for green and blue hydrogen with accurate carbon footprint assessment and real-time monitoring. Fully aligned with ESPR and EU standards, our solution ensures transparent, auditable data that prevents greenwashing while enabling regulatory compliance and verified sustainability achievements.
Textile Digital Product Passport (PassTEX)
PassTEX brings AI-powered, blockchain-backed traceability to the textile and apparel value chain. From fiber and yarn to dyeing, finishing, confection and retail, every step is recorded, verified and made auditable. PassTEX documents material composition, recycled content, chemical use, water and energy footprint, and durability and repairability data, delivering ESPR-ready product passports that substantiate circularity claims and prevent greenwashing.
Battery Digital Product Passport (BPP)
BPP delivers a complete digital identity for batteries across their entire lifecycle. Our platform records raw material provenance, cell and pack manufacturing data, carbon footprint, state of health and state of charge telemetry, and second-life and recycling records on a tamper-proof ledger. Fully aligned with the EU Battery Regulation and ESPR, BPP enables due diligence reporting, safe reuse and repurposing, and verifiable recovery of critical raw materials.
AI in Distance Education
We are glad to announce that we have just launched a new R&D project titled "Cloud-Native AI Platform for monitoring distance learning performance and exam security based on face biometry" in partnership with Bahçeşehir College. TÜBİTAK's (The Scientific and Technological Research Council of Turkey) TEYDEB (Technology and Innovation Grant Programs) supports the project.
Multi-factor Authentication Services (XFAS)
XFAS is DEEPCLOUDLABS' multi-factor authentication SaaS. Users enroll once with a password and their biometrics; each sign-in then combines two or more factors, from one-time codes to face, voice, fingerprint and iris recognition, or goes fully passwordless. XFAS guards against breaches from lost or stolen credentials, provides single sign-on to all applications from any device, re-verifies students throughout online exams, and integrates through SAML, JWT, OAuth2 and OpenID Connect.
AI in Healthcare: DEEPCLOUDLABS Launches CXR AI Suite to Detect Chest X-Ray Abnormalities
CXR-AI Suite is a CADx system that detects anomalies in X-Ray images using multi-layer deep networks. If you are looking for a partner for developing healthcare solutions using AI and ML, feel free to contact us. DCL-CXR Project is supported by The Scientific and Technological Research Council of Turkey (TUBITAK) with the project no 1190024.
Low Latency High Frequency Explainable AI Based Trading System
We have been delivering High Frequency (HFT) solutions and consultancy. Algorithmic trading aims to replace human trader with an algorithm running on a computer system. Our "Algorithmic Trading Platform for Cryptocurrency Exchange Markets" Project has been successfully completed.
Cloud-Native Application Development
We have expertise on Cloud-Native Application Development with Microservices Architecture. We help our customers to develop applications using modern architecture and to deploy to on-premise, private, or hybrid cloud platforms: Safir DEPO, Performance Testing as a Service (PTaaS), Test Automation as a Service (TAaaS).
RadiologyTrainer
AI-based personalized training platform for radiologists. Trainees locate and classify anomalies on real cases, get instant AI feedback against the ground truth, and practice on GAN-generated pathologies tailored to their skill level.
Machine Learning Bootcamp
From your first Python program to the research papers behind modern AI: a complete AI engineering pathway in 7 hands-on, instructor-led courses and 26 training days, with a capstone project planned around your team.
  1. Python foundations Python and advanced Python · 7 days
  2. Data & machine learning analytics and scikit-learn · 7 days
  3. Deep learning PyTorch 2, TensorFlow and Keras 3 · 8 days
  4. Research papers AlexNet to ViT, from scratch · 4 days
Services
DEEPCLOUDLABS Services provide access to the talent and systems you need to innovate faster and deliver real business value.

Software Development | Blockchain Implementation | Big Data Analytics | AI and Machine Learning
Consulting
DEEPCLOUDLABS provide advice, expertise, and consulting services for Blockchain Technology, AI-Machine Learning and Software Development.
Implementation
Agile implementation of advanced Big Data Analytics applications. Increase accuracy and productivity using cognitive technology to process data.
Research and Development
DEEPCLOUDLABS transforms your ideas into a product using agile methodologies, advanced technology, and a software development stack.
Corporate Training
DeepCloudLabs provides hands-on training and courses. We offer in-house and external corporate training and teaching seminars, workshops, and talks.
Big Data Analytics

Big data analytics turns large, fast-moving and varied data (records, logs, sensor streams, documents and images) into decisions you can act on. We design data platforms that ingest data in real time, store it at scale and serve it to dashboards, alerts and machine learning models, on premises or in the cloud.

  • Real-time ingestion and event streaming with Apache Kafka and RabbitMQ
  • Batch and stream processing pipelines, data lakes and data warehouses
  • Live dashboards and KPIs for decision makers
  • Anomaly detection and forecasting on operational and market data
  • Data quality, governance and secure data sharing with partners

From our work: anomaly detection for cryptocurrency exchange markets and ESG, LCA and 4R sustainability analytics in our Digital Product Passports.

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IoT sensors, transactions, logs, documents and images stream through Kafka into a data lake, feeding a live dashboard, anomaly detection and forecasts
Artificial Intelligence and Machine Learning

Machine learning lets systems learn patterns from data and improve with experience. Combined with perception, language and reasoning, it lets machines understand requests, connect data points and draw conclusions. Our Ph.D. and M.Sc. engineers take models from research to production: framing the problem, preparing the data, training and validating the model, and running it as a reliable service.

  • Deep learning with PyTorch and TensorFlow for images, signals, text and time series
  • Medical image analysis, from chest X-ray anomaly detection to radiology training
  • Explainable AI, so every prediction comes with the factors behind it
  • Model deployment and monitoring in the cloud or on edge devices
  • Feasibility studies and R&D projects, including TÜBİTAK-supported ones

From our work: an AI pipeline that analyzes about 1,400 X-ray images per second in HaaS, the RadiologyTrainer platform, and explainable models for algorithmic trading.

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A deep neural network inside the model lifecycle of data, training, evaluation, deployment and monitoring, with explainable feature importance and accuracy
Video Analytics

Video analytics applies computer vision and deep learning to live or recorded video, so cameras do more than record: they detect, track, count and raise alerts. We build pipelines that run on edge devices or in the cloud, process many camera streams in real time and send events to your security and business systems.

  • People counting, crowd density and occupancy at events and venues
  • Automatic license plate recognition for gates and parking
  • Smart parking with live free-space detection
  • Face detection and verification for identity and access
  • Real-time alerts and dashboards connected to your existing systems

From our work: face biometry for exam security and student attention monitoring in our distance-learning AI platform.

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People counted at an entrance camera, free and occupied parking slots, a license plate read at the gate, people on site over time and a live event feed
Generative AI and LLMs

Generative AI creates text, code and images, and large language models (LLMs) can answer questions from your own documents and data. We help organizations move from experiments to secure, measurable systems in production.

  • Retrieval-augmented generation (RAG) assistants that answer from enterprise documents and cite their sources
  • AI agents and multi-agent systems that work with your tools and APIs
  • LLMOps: evaluating, monitoring and operating AI systems in production
  • Secure and responsible AI: guardrails, privacy and access control
  • Generative models for synthetic data, such as GAN-generated pathologies
  • AI-assisted and agentic software engineering for development teams

From our work: GAN-based pathology generation in RadiologyTrainer, and 20 courses on deep learning, generative AI and AI-native engineering in our training catalog.

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An enterprise assistant answers a question with cited sources, retrieved through vector search and an LLM with agents, tools and guardrails, and measured with LLMOps scores
Cloud-Native Architecture

Cloud-native applications are built from small, independently deployable services that scale, recover and change quickly. We design new systems and modernize existing ones with microservices and event-driven architecture, and deploy them on premises or to private, hybrid or public clouds.

  • Microservice architecture and domain-driven design, including moving away from monoliths
  • Event-driven systems with Apache Kafka and RabbitMQ
  • Containers, CI/CD pipelines and DevOps practices
  • Deployments on AWS, Microsoft Azure and Google Cloud
  • Resilience, observability and performance testing

From our work: Safir DEPO, Performance Testing as a Service (PTaaS) and Test Automation as a Service (TAaaS).

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Clients reach microservices through an API gateway; services with their own databases talk over a Kafka and RabbitMQ event bus, ship through a CI/CD pipeline and run on premises or in private, hybrid or public clouds
Blockchain and Data Spaces

Blockchain gives partners who do not fully trust each other a shared, tamper-proof record. We use it to make supply chains traceable and sustainability claims verifiable, and combine it with data spaces so companies can share data without losing control of it.

  • Digital Product Passports with lifecycle records from raw material to recycling
  • Verifiable carbon footprint, recycled content and sustainability claims
  • GAIA-X/IDSA and UNTP-compliant data spaces with data sovereignty
  • Readiness for ESPR and the EU Battery Regulation
  • Cryptocurrency market analytics, arbitrage and anomaly detection

From our work: the H2DPP, PassTEX and BPP passports for hydrogen, textiles and batteries, and our cryptocurrency trading platform.

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Raw material, production, distribution and recycling records chained into hashed blocks, a verified battery product passport with a QR code, and companies sharing data in a GAIA-X, IDSA and UNTP data space
Training Courses

Instructor-led, hands-on courses delivered in-house, on-site or remotely. 67 courses across 11 technology domains, from one-day executive briefings to ten-day architecture programmes. New for 2027: a nine-course AI-native software engineering domain, with Java SE 27, Spring Boot 4 and Kafka 4 across the curriculum.

67 courses

  • DCL-500 3 days

    AWS Essentials

    Cloud
  • DCL-350 5 days

    Implementing Microservices Architecture using Spring Cloud

    Microservices & DevOps
  • DCL-200 3 days

    Java Performance Tuning and Optimization

    Java SE 27
  • DCL-168 3 days

    Kotlin Programming

    Spring & Kotlin
  • DCL-342 3 days

    Jakarta Persistence 3.2

    Jakarta EE 11
  • DCL-160 4 days

    Python Programming

    Data & ML
  • DCL-422 4 days

    Deep Learning for Computer Vision

    Deep Learning & GenAI
  • DCL-600 New 3 days

    AI-Assisted Software Engineering

    AI-Native Engineering
  • DCL-302 3 days

    Node.js Programming

    JavaScript & Web
  • DCL-100 3 days

    C Programming

    C/C++ & Linux
  • DCL-450 1 day

    Big Data and Artificial Intelligence for Executives

    Executive Programs
  • DCL-502 3 days

    Microsoft Azure Fundamentals

    Cloud
  • DCL-351 4 days

    Microservices Testing

    Microservices & DevOps
  • DCL-204 5 days

    Java SE 27 Programming

    Java SE 27
  • DCL-370 4 days

    Spring Framework 7

    Spring & Kotlin
  • DCL-364 3 days

    Best Practices in Jakarta EE 11

    Jakarta EE 11
  • DCL-162 3 days

    Advanced Python Programming

    Data & ML
  • DCL-424 4 days

    Deep Learning for Medical Image Analysis

    Deep Learning & GenAI
  • DCL-602 New 3 days

    Specification-Driven Development with AI Agents

    AI-Native Engineering
  • DCL-304 3 days

    Advanced JavaScript Programming

    JavaScript & Web
  • DCL-112 4 days

    Object-Oriented Programming in Modern C++ (C++23/26)

    C/C++ & Linux
  • DCL-452 1 day

    Cloud Computing and Microservice Architecture for Executives

    Executive Programs
  • DCL-504 10 days

    Azure Cloud for Architects

    Cloud
  • DCL-352 2 days

    Domain-Driven Design Essentials

    Microservices & DevOps
  • DCL-206 4 days

    Advanced Java Development with Modern Design and Programming Paradigms

    Java SE 27
  • DCL-374 3 days

    Developing Spring Boot 4 Applications

    Spring & Kotlin
  • DCL-390 4 days

    Developing Enterprise Applications on Jakarta EE 11

    Jakarta EE 11
  • DCL-400 3 days

    Big Data Essentials

    Data & ML
  • DCL-426 4 days

    Deep Learning with PyTorch

    Deep Learning & GenAI
  • DCL-604 New 4 days

    Agentic Software Engineering

    AI-Native Engineering
  • DCL-305 3 days

    Developing Angular Applications

    JavaScript & Web
  • DCL-113 2 days

    Functional Programming in Modern C++ (C++23/26)

    C/C++ & Linux
  • DCL-454 New 1 day

    AI-Native Software Delivery for Technology Leaders

    Executive Programs
  • DCL-506 3 days

    Google Cloud Platform Essentials

    Cloud
  • DCL-353 3 days

    DevOps Engineering

    Microservices & DevOps
  • DCL-208 3 days

    Clean Architecture and Code (Java SE and Spring Boot)

    Java SE 27
  • DCL-376 3 days

    Spring Data

    Spring & Kotlin
  • DCL-402 3 days

    Data Analytics using Python

    Data & ML
  • DCL-428 4 days

    Deep Learning with TensorFlow

    Deep Learning & GenAI
  • DCL-606 New 3 days

    AI-Assisted Software Testing and Quality Engineering

    AI-Native Engineering
  • DCL-306 3 days

    Developing React Applications

    JavaScript & Web
  • DCL-115 3 days

    Multi-Threaded Programming in Modern C++ (C++23/26)

    C/C++ & Linux
  • DCL-355 4 days

    Microservices Patterns with Examples in Spring Boot

    Microservices & DevOps
  • DCL-210 3 days

    Advanced Java Programming

    Java SE 27
  • DCL-410 4 days

    Practical Machine Learning using Python

    Data & ML
  • DCL-430 4 days

    Foundation of Deep Learning with Backbone Architecture Papers

    Deep Learning & GenAI
  • DCL-610 New 4 days

    Generative AI Application Development

    AI-Native Engineering
  • DCL-318 3 days

    Developing Vue 3 Applications

    JavaScript & Web
  • DCL-140 4 days

    Linux System Programming

    C/C++ & Linux
  • DCL-356 2 days

    Cloud Architecture Patterns

    Microservices & DevOps
  • DCL-215 3 days

    Test-Driven Development with JUnit 6

    Java SE 27
  • DCL-432 4 days

    Deep Learning with Backbone Learning Paradigm Papers

    Deep Learning & GenAI
  • DCL-612 New 3 days

    Retrieval-Augmented Generation for Enterprise Applications

    AI-Native Engineering
  • DCL-358 3 days

    Implementing Event-Driven Microservices Architecture using Spring Boot and Apache Kafka

    Microservices & DevOps
  • DCL-220 3 days

    Object-Oriented Programming Principles and Design Patterns with Java SE 27

    Java SE 27
  • DCL-434 3 days

    Introduction to Generative AI with Python

    Deep Learning & GenAI
  • DCL-614 New 4 days

    AI Agent and Multi-Agent Systems Engineering

    AI-Native Engineering
  • DCL-380 2 days

    Apache Kafka: Architecture and Development

    Microservices & DevOps
  • DCL-235 3 days

    Effective Java Programming

    Java SE 27
  • DCL-436 4 days

    Advanced Generative AI with Python

    Deep Learning & GenAI
  • DCL-616 New 3 days

    LLMOps: Evaluating and Operating Production AI Systems

    AI-Native Engineering
  • DCL-382 2 days

    RabbitMQ: Architecture and Administration

    Microservices & DevOps
  • DCL-252 2 days

    New Features in Java SE 8–27

    Java SE 27
  • DCL-438 2 days

    Introduction to ChatGPT

    Deep Learning & GenAI
  • DCL-618 New 3 days

    Secure and Responsible AI Application Engineering

    AI-Native Engineering
  • DCL-440 2 days

    Introduction to Image Generation with Stable Diffusion

    Deep Learning & GenAI
  • DCL-460 4 days

    Edge Computing: Deployment & Inference with NVIDIA Jetson

    Deep Learning & GenAI

Bootcamps

Multi-course programmes that take a team from fundamentals to production in one planned sequence.

Machine Learning Bootcamp

7 courses · 26 training days

  1. Python Programming
  2. Advanced Python Programming
  3. Data Analytics using Python
  4. Practical Machine Learning using Python
  5. Deep Learning with PyTorch
  6. Deep Learning with TensorFlow
  7. Foundation of Deep Learning with Backbone Architecture Papers

Full-stack Development Bootcamp

4 courses · 17 training days

  1. Java SE 27 Programming
  2. Spring Framework 7
  3. Developing React Applications
  4. Implementing Microservices Architecture using Spring Cloud
Who Are we?
DEEPCLOUDLABS is an innovation company with Research and Development teams that focus on all aspects of the following topics

Cloud Computing

Big Data

Artificial Intelligence and Machine Learning

Image and Video Analytics

Blockchain and crypto-currency

Algorithmic and High-Frequency Trading

Project Management and Software Process Enhancement

DEEPCLOUDLABS Services provide access to the talent and systems you need to innovate faster and deliver real business value. We offer a full range of professional services:

CONSULTING: DEEPCLOUDLABS provides advice, expertise, and consulting services for Blockchain Technology, AI-Machine Learning and Software Development.

CORPORATE TRAINING: DEEPCLOUDLABS provides hands-on real world courses/trainings. We offer in-house and external corporate training and teaching seminars, workshops and talks.

RESEARCH & DEVELOPMENT: DEEPCLOUDLABS can help you study new concepts around Data Analytics, AI-Machine Learning and Blockchain Technologies.

SOFTWARE DEVELOPMENT: Agile implementation of advanced Big Data analytic applications. Increase accuracy and productivity using cognitive technology to process data.

OUTSOURCED DEVELOPERS: Hire our talented developers for a certain time-period.

Our engineering team is made up of great individuals with Ph.D. and M.Sc. degrees and engineering experience, capable of making innovations and transforming these innovations into products.

Digital Product Passport for Green and Blue Hydrogen
The Digital Product Passport (DPP) for green and blue hydrogen delivers robust, end-to-end traceability throughout the entire lifecycle of hydrogen products. By leveraging advanced blockchain technology, every stage—from raw material sourcing and production to distribution and end-of-life—is securely recorded and verifiable. This approach ensures transparent tracking, supports comprehensive lifecycle assessments, and provides precise carbon footprint calculations, empowering organizations to validate sustainability claims and enhance environmental performance.
AI-Driven Circular Economy and Sustainability Analytics
DeepCloudLabs harnesses artificial intelligence to monitor and optimize key circular economy indicators, including ESG, LCA, and 4R (reduce, reuse, recycle, recover) metrics. Our DPP platform integrates these analytics, enabling enterprises to track resource efficiency, environmental impact, and compliance with circular economy principles. By transforming complex data into actionable insights, we help organizations achieve regulatory objectives and ambitious sustainability targets—driving measurable progress toward a circular and regenerative business model.
Interoperable Ecosystems, Compliance, and Greenwashing Prevention
We are committed to building secure, interoperable ecosystems that guarantee data sovereignty and traceability across supply chains. Our DPP solutions utilize GAIA-X/IDSA and UNTP-compliant dataspaces, ensuring compatibility with the latest European standards for data sharing and industrial digitalization. Designed for seamless integration with ERP systems and full support for ESPR and ICR frameworks, our platform streamlines regulatory reporting and accelerates market access. By providing verified, standardized, and transparent product data at every lifecycle stage, DeepCloudLabs enables organizations to substantiate their sustainability claims, effectively preventing greenwashing and fostering genuine trust among stakeholders.
Digital Product Passport for Textile and Apparel (PassTEX)
PassTEX is our Digital Product Passport platform for the textile and apparel industry, providing fiber-to-garment traceability across highly fragmented, multi-tier global supply chains. Every stage—fiber production, spinning, weaving and knitting, dyeing and finishing, confection, distribution, use and end-of-life—is securely recorded on blockchain and linked to the physical product through a QR code or digital identifier. The result is verifiable proof of origin, composition and sustainability performance that brands, regulators and consumers can trust.
Material Provenance, Recycled Content and Chemical Transparency
PassTEX captures verified data on fiber origin, material composition and recycled or bio-based content, together with chemical management, water and energy consumption at each processing step. AI-assisted validation cross-checks supplier declarations, test reports and certificates to detect inconsistencies before they reach the passport. Brands gain auditable evidence for recycled-content and low-impact claims, while manufacturers can benchmark and reduce the environmental footprint of every article they produce.
ESPR Compliance, Circularity and Durability Insights
Built on GAIA-X/IDSA and UNTP-compliant dataspaces, PassTEX keeps data sovereign while making it shareable across the value chain and integrable with ERP, PLM and PIM systems. The platform is designed for ESPR and the EU Strategy for Sustainable and Circular Textiles, covering durability, repairability, reusability and recyclability information as well as extended producer responsibility reporting. By turning lifecycle data into 4R and LCA analytics, PassTEX helps organizations extend product life, feed materials back into circular loops and substantiate sustainability claims with evidence rather than marketing.
Digital Product Passport for Batteries (BPP)
BPP gives every battery a secure digital identity that travels with it from raw material extraction through cell and pack manufacturing, first life in vehicles or storage systems, second-life repurposing and final recycling. Blockchain-anchored records combine static data—chemistry, capacity, materials and manufacturing origin—with dynamic telemetry collected in the field, producing a complete, tamper-proof lifecycle history for manufacturers, operators, recyclers and regulators.
State of Health Analytics and Second-Life Readiness
Our AI models turn charge and discharge telemetry, thermal history and usage patterns into reliable state-of-health, remaining-useful-life and degradation forecasts. These insights support predictive maintenance and warranty management during first life, and provide the objective grading needed to decide whether a retired pack should be reused, repurposed for stationary storage or sent to recycling. Residual value becomes measurable instead of assumed, unlocking safe and profitable second-life markets.
EU Battery Regulation Compliance and Responsible Sourcing
BPP is aligned with the EU Battery Regulation and ESPR, delivering the carbon footprint declaration, recycled content share, due diligence disclosure and end-of-life information that the battery passport mandate requires. Interoperable GAIA-X/IDSA and UNTP dataspaces ensure that suppliers, OEMs, service providers and recyclers exchange verified data without surrendering data sovereignty, while ERP integration automates regulatory reporting. The result is transparent, responsible sourcing of critical raw materials such as lithium, cobalt and nickel, and faster access to regulated markets.
Healthcare-As-A-Service (HaaS) Solutions of DEEPCLOUDLABS
DEEPCLOUDLABS has launched "Healthcare-As-A-Service Platform" to Manage Medical Information and Predictive/Personalized Medicine Applications. DCL developed the AI ​​analysis pipeline for health, which includes deep learning-based analysis models for processing large-scale health data. With the developed AI-pipeline, approximately 1400 X-Ray images can be processed (inference) per second and provide value-added inputs to CAD / CADx systems.
AI based Chest X-Ray Anomaly Detection
Vast amount of medical imaging techniques are widely used for diagnosis and treatment in medicine. Most pervasive and readily accessible imaging technique available today is X-Ray imaging according to World Health Organization’s reports.
AI diagnosis pipeline: X-Ray and CT images are enhanced and segmented, analysed by a multi-layer deep network and returned as anomaly scores for CAD/CADx, with radiologist feedback improving the model
AI based Healthcare SaaS Pipeline for Diagnosis
This platform is a computer aided diagnosis system to detect anomalies in medical images (X-Ray / CT) using multi-layer deep networks. The networks are trained using open data sets together with the data provided by the participant hospitals.
RadiologyTrainer learning loop: case library, locate and classify, AI evaluation against the ground truth, GAN-generated cases and skill growth
RadiologyTrainer: AI-Based Personalized Training Platform for Radiologists
Radiologists build their interpretation skills by seeing a large number of cases, yet traditional master-apprentice training offers limited exposure, and around 80% of diagnostic errors in radiology are perceptual. RadiologyTrainer is DEEPCLOUDLABS' AI-assisted, active-learning platform for medical students, radiology residents and radiologists: trainees locate and classify anomalies on annotated X-Ray and CT cases, AI evaluates every answer against the ground truth, and training content adapts to each learner's skill level. The platform is developed with the support of TÜBİTAK's 1501 Industrial R&D Grant Program.
How RadiologyTrainer works: case library, locate and classify, AI checks against ground truth, real-time feedback and GAN-made new cases, personalized to each learner
Learn by Locating and Classifying Anomalies
Trainees work through a diverse library of annotated real-world cases, marking and classifying the abnormalities on each image. AI algorithms compare every marking and label with the ground truth and return real-time feedback and performance analysis, with scoring based on more than 500,000 images balanced by disease. Anamnesis data is analyzed with NLP models, so each case is read in its clinical context.
GAN-based pathology generation: a healthy region of a chest X-ray becomes synthetic nodule/mass and pleural effusion cases through a generator checked by a discriminator
GAN-Based Pathology Generation
Rare findings are hard to practice on. RadiologyTrainer uses generative adversarial networks (DCGAN and CycleGAN) to synthesize realistic pathologies, such as lung nodules/masses and pleural effusion, on regions of interest taken from healthy chest X-rays. The synthetic cases expand the training library and let the platform generate personalized content for each learner's needs.
Cloud-Native AI Platform for monitoring distance learning performance and exam security based on face biometry
COVID19 has dramatically changed our lives and the most dramatic effect has happened in learning. Schools have been closed all across the world, and teaching is offered remotely and on digital platforms. The change means distinct experiences both for students, teachers, and parents. Hence it brings new challenges. Performance monitoring and reporting tools are needed to help students, teachers, and parents overcome the challenges. Another big challenge to address is exam security which includes verifying the student's identity when logging into the system and during the exam. The platform answers both: AI services that monitor and report learning performance, and DEEPCLOUDLABS' Multi-factor Authentication AI-Pipeline and Services (XFAS) for identity.
Online exam on a laptop with a face match, sign-in with username and password, face and voice, and the student's identity re-verified during the exam
Multi-Factor Authentication Service for Exam Security
Multi-factor authentication grants a user access only after they present two or more pieces of evidence: a pin code that a machine generates, or biometric data such as face, fingerprint, voice, or iris. Biometric authentication is mobile by its nature, and integrating it into Identity and Access Management systems raises the security level, at login and throughout the exam.
Online class dashboard with student attention levels, lecture speech-to-text split into subtopics, participation statistics and a personal exam with topic repetitions and explained solutions
AI Services to improve the performance of distance education
  • Monitoring student attention level
  • Converting teacher's speech to text and segmenting the online session into the segments labeled with subtopics defined in the course content
  • Measuring and reporting student's participation and involvement statistics in an online education session
  • Preparing personal exam sessions based on the student's performance reports and the previous exam results
  • Mentoring students on how to improve the exam performance through offering topic repetitions and explained exams solutions
Phone scanning a face for XFAS sign-in, face, voice, fingerprint and iris recognition, and the steps enroll once, verify each sign-in and go passwordless
Biometric Services for XFAS
Forgotten credentials, locked accounts, and time-consuming reset processes annoy users. XFAS simply enrolls a user using user name, password, and biometrics such as face and voice. Authentication system verifies user using provided user name, password, and biometrics. Passwordless authentication is also possible using only biometrics.
XFAS authentication pipeline: sign-in from any device passes multi-factor checks, a token gives single sign-on to all applications, a stolen password is blocked, and integration uses SAML, JWT, OAuth2 or OpenID Connect
XFAS Authentication Pipeline
XFAS helps secure your organization against breaches due to lost or stolen credentials. Users create a free account and multi-factor authentication service prompts users for additional verification. XFAS enables users access to all their applications securely and seamlessly with single sign-on from any location or device. XFAS can be easily integrated to your security infrastructure using SAML, JWT, OAuth2, or OpenID Connect.
ALGORITHMIC TRADING
We have been delivering HFT solutions and consultancy currently in Turkey. We have developed High Frequency Trading solution using FPGA technology to obtain sub-microsecond end-to-end market data processing. Our Algorithmic Trading Project ("Algorithmic Trading Platform for Cryptocurrency Exchange Markets) has been successfully completed. This project financially supported by TÜBİTAK (Turkish NSF).
Deep Learning and Blockchain Technologies for Algorithmic Trading and Anomaly Detection
We have developed a core machine learning technology that is based on a non-conventional quantitative finance approach and novel machine learning techniques. Our HFT system is actively used by a "real estate investment company/bank" in Istanbul Stock Exchange (BIST: https://www.borsaistanbul.com/en/).

Anomaly detection is the process of identifying unexpected events in data sets, which differ from the norm. We have developed anomaly detection model for CryptoCurrency exchange markets that produces anomaly signal using the historical trading information.
Low Latency High Frequency eXplainable AI Based Trading System
Algorithmic trading aims to replace human trader with an algorithm running on a computer system. Algorithmically generated trade, in theory, can generate profits at a speed that is impossible for a human trader. High frequency trading is a sub-class of algorithmic trading. HFT requires the lowest possible data latency to access market data the algorithm needs and to send the order that the algorithm decides. AI and Machine Learning based continuously learning market and trading models present promising solutions compared to fixed and hand crafted mathematical models.

Arbitrage is a common strategy used that involves the profiting from price discrepancies between exchanges. We have developed an arbitrage robot that runs arbitrage between multiple cryptocurrency exchange markets.
Our Team is Your Team
  • DEEPCLOUDLABS Services provide access to the talent and systems you need to innovate faster and deliver real business value. We offer a full range of professional services:
  • CONSULTING: DEEPCLOUDLABS provides advice, expertise, and consulting services for Blockchain Technology, AI-Machine Learning and Software Development
  • RESEARCH & DEVELOPMENT: DEEPCLOUDLABS can help you study new concepts around Data Analytics, AI-Machine Learning and Blockchain Technologies.
Your team and DEEPCLOUDLABS engineers working as one team on a shared backlog, supported by consulting, development, R&D and dedicated developers
  • SOFTWARE DEVELOPMENT: Agile implementation of advanced Big Data analytic applications. Increase accuracy and productivity using cognitive technology to process data
  • OUTSOURCED DEVELOPERS: Hire our talented developers for a certain time-period. Our engineering team is made up of great individuals with Ph.D. and M.Sc. degrees and engineering experience, capable of making innovations and transforming these innovations into products.
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Map of Zeytinburnu, İstanbul, with a pin on our Head Office and R&D Office at Biruni Teknopark
Biruni Teknopark
Head Office & R&D Office
Kazlıçeşme Mah. 245. Sk. No:5, Zeytinburnu, İstanbul

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