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Capability & Team Overview

Clinical research • CRO services • Data science • AI-enabled health innovation

Prepared for our prospective research partner | August 2026

One-Slide Narrative

Executive Summary

A quick orientation before the detailed review that follows.

Clinical depth. AI engineering speed.

1

Finding

Research depth plus AI engineering execution.

2

Evidence

21 peer-reviewed papers, deployed AI platforms.

3

Decision

Let's scope a pilot aligned to your priorities.

Key Message

Clinical research expertise plus in-house AI engineering, ready for a scoped pilot.

Navigation

Agenda / Talk Flow

A quick tour of who we are, what we've built, and how we can work together.

  1. 01Who We Are
  2. 02AI & Digital Health Solutions
  3. 03International Project Experience
  4. 04Core Team & Key Experts
  5. 05Collaboration Model & Next Steps
01Company Profile

Who We Are

We bring together clinical/biomedical research expertise and hands-on AI engineering to design, build, and evaluate technology for healthcare and applied research. Our work spans hardware and data security research, medical-imaging AI, and production automation for real-world clients.

What Makes Us Different

Research rigor meets shipped AI products.

  • 21 peer-reviewed journal papers (9 Q1, 3 Q2, 4 Q3) plus 26 conference publications
  • 3+ years delivering production RAG, LLM fine-tuning, and automation systems for business clients
  • Track record building AI/digital-health platforms end to end, from model to clinician-ready product

Source: team CVs and publication record, compiled 2026

02AI & Digital Health

Selected AI & Digital Health Work

What we have designed, built, and shipped.

Our AI engineering work concentrates on healthcare applications: diagnostic imaging, patient-facing monitoring tools, and clinician-ready reporting, built on modern deep learning and generative AI stacks.

Flagship Example

Vorra: AI-powered wound monitoring platform.

Do What works: Mental Health Development

  • Vorra AI wound monitoring system

    An AI-powered wound analysis platform that processes daily wound images to monitor healing progress, detect infection risks, and generate clinical insights.

  • AI wound healing progression analyzer

    Uses computer vision to compare sequential wound images and estimate healing stages with confidence scoring and trend analysis.

  • Carezon AI healthcare automation platform

    An intelligent healthcare workflow automation system integrating AI agents, patient communication, scheduling, and clinical data management.

  • Cliniko–GoHighLevel patient synchronization engine

    Automates patient creation, lookup, and synchronization between Cliniko and GoHighLevel CRM with error handling and status tagging.

  • AI medical appointment booking assistant

    A conversational AI assistant that books appointments, answers patient queries, and updates CRM records in real time.

  • Fundus retinal disease detection using deep learning

    A deep learning model for detecting retinal abnormalities from fundus images using convolutional neural networks and explainable AI.

  • Kidney CT scan pathology detection system

    Analyzes kidney CT images to identify abnormalities and assist in early diagnosis using medical image segmentation and classification.

  • Medical image classification with MobileNetV2

    An optimized lightweight deep learning model for classifying medical images with high accuracy and fast inference.

  • Explainable AI for medical diagnosis

    Integrates SHAP and LIME to provide interpretable predictions for healthcare professionals and improve diagnostic transparency.

  • Mental health disorder prediction using machine learning

    Predicts mental health conditions based on behavioral and clinical indicators using supervised machine learning algorithms.

  • Depression prevalence forecasting model

    Uses historical and demographic data to forecast depression prevalence trends for public health planning and intervention.

  • AI-powered clinical image assessment platform

    A centralized platform for uploading, analyzing, and reporting medical images with AI-generated diagnostic assistance.

  • Remote wound care monitoring dashboard

    A web-based dashboard that enables clinicians to remotely track wound healing, patient progress, and treatment effectiveness.

  • Healthcare conversational AI support agent

    A multilingual AI assistant for patient support, symptom guidance, appointment reminders, and healthcare information delivery.

  • Medical vision AI for infection risk assessment

    A computer vision system designed to identify visual indicators of infection and prioritize cases requiring urgent clinical attention.

03Project Portfolio

International Project Experience

Client and cross-border delivery across AI and software products.

Beyond healthcare AI, our team has delivered a range of client-facing platforms spanning automation, content generation, and customer engagement, giving us broad experience shipping production software under real deadlines.

Also On Record

EKKO Loop: AI receptionist & retention platform.

  • Vidora: AI content studio turning text prompts into video, voiceover, and talking-avatar output for creators
  • Do What Works: AI-guided personal development platform with belief assessment and habit tracking
  • Smart Outfit Try-On: real-time virtual try-on using the Gemini API and computer vision

Full project list available on request

04Core Team

Core Team & Key Experts

The people behind the research and the engineering.

Dr. Fakir Sharif Hossain

Dr. Fakir Sharif Hossain

Associate Professor, EEE, AUST

PhD, Electronics (NAIST, Japan)

19+ years in academic and research roles across four universities in Bangladesh and Japan, with deep expertise in hardware security, VLSI, and applied electronics research.

  • 21 peer-reviewed journal papers (Web of Science / Scopus indexed)
  • 26 international conference papers and multiple best-paper awards
  • Supervises M.Sc. and undergraduate research; active journal reviewer for IEEE, Elsevier, Springer, and MDPI

Role on this engagement: Clinical/technical research lead and academic quality oversight

Arif Mahmud Sisir

Arif Mahmud Sisir

AI Engineer, Sparktech Agency

B.Sc. CSE, Southeast University

AI Engineer with 3+ years building production AI systems: RAG pipelines, LLM fine-tuning, and automation for business clients, with a publication in AI-driven medical imaging.

  • AI Engineer, Sparktech Agency; former Jr. Project Manager & AI Engineer, Apcorn Innovation
  • Built AI/digital-health platforms: kidney disease detection, breast cancer detection, wound monitoring (Vorra)
  • Published in International Journal of Intelligent Systems and Applications in Engineering (IJISAE), 2024

Role on this engagement: AI/ML engineering, RAG systems, and platform delivery

Mamunur Rashid Alex

Mamunur Rashid Alex

AI Researcher & ML Engineer

M.Sc. in CSE, North South University

AI researcher and ML engineer working in machine learning, deep learning, explainable AI, medical image analysis, computer vision, and bioinformatics, with multiple journal and IEEE conference publications.

  • AI Researcher, USA-based (Remote); former Lab Assistant, Southeast University; former Junior App Developer, BS Technology
  • Research interests: Machine Learning, Deep Learning, XAI, Medical Image Analysis, Bioinformatics, Computer Vision, NLP, and Cybersecurity
  • Technical stack: Python, MATLAB, TensorFlow, PyTorch, Keras, OpenCV, MySQL, Flutter, and Dart
  • Publications include IJRTE journal article, Springer-accepted work, and IEEE papers at TENSYMP 2026, COMPAS 2025, ICCIT 2025, MPCON 2025, WIECON 2025, and QPAIN 2026
  • Leadership and service: Mentor at AI & Robotic Community (ARC), Coordinator at Excellence Bangladesh, and former President of Southeast Computer Club

Role on this engagement: AI research, machine learning, computer vision, and intelligent system development

Mehrab Hossain

Mehrab Hossain

Full-Stack Developer

Full-Stack Developer specializing in modern web and mobile applications, with experience building scalable products using React, Next.js, Node.js, NestJS, Flutter, and AI integrations.

  • Full-Stack Developer, Digitalbkk Co. Ltd.; working on production SaaS and web platforms
  • Built and contributed to products including MangoCV, Cheewaa Portal, LiveDocs, and DentaFlow
  • Experienced with React.js, Next.js, TypeScript, Tailwind CSS, Node.js, NestJS, PostgreSQL, MongoDB, Prisma, and Flutter
  • Integrated AI APIs, function calling, authentication, payments, and modern cloud-based services
  • Focused on scalable frontend architecture, performance optimization, and production-ready applications

Role on this engagement: Full-Stack Engineering, frontend architecture, AI integration, and platform delivery

05Partner-Facing Layout

Collaboration Model

How We Divide the Work

Partner brings

  • Clinical protocol
  • Patient / trial access
  • Domain sign-off

Innoclin brings

  • Trial ops support
  • Biostatistics
  • AI/ML platform build and validation

Joint output

  • Manuscript
  • Grant / registry submission
  • AI-based product evidence package

Engagement Path

  1. 01

    Scoping call

    30-45 min

    Align on research question or product goal.

  2. 02

    Pilot proposal

    Scope, timeline, deliverables, and cost estimate.

  3. 03

    Pilot execution

    Typically 4-8 weeks

    Depending on data availability.

  4. 04

    Review & decide

    Go / no-go on full engagement based on pilot results.

Pilot Engagements

Fixed-scope pilot proposals provided after a free scoping call — no cost to explore fit.

Thank You

Clinical Research • CRO Services • AI-enabled Healthcare Innovation

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