Development of the Medical AI Knowledge Base The first milestone establishes the core intelligence of DR ROBOT — a unified Medical AI Knowledge Base (MAIKB) designed to power accurate evidence-driven diagnosis reasoning and emotional understanding. This phase focuses on curating structuring and embedding large-scale verified medical and psychological data from trusted global sources such as WHO PubMed MedlinePlus and ICD-10. The MAIKB will integrate both clinical and mental health datasets covering diseases symptoms medications treatment pathways and emotional therapy models. Using Retrieval-Augmented Generation (RAG) BioBERT and ClinicalGPT embeddings the system will enable DR ROBOT to access real-time knowledge cross-reference medical evidence and generate human-understandable explanations. This milestone ensures DR ROBOT becomes a trusted explainable and compliant knowledge engine forming the backbone of its diagnostic counseling and multilingual reasoning capabilities — ready for fine-tuning in subsequent phases. Deliverables: RAG-based knowledge indexing and retrieval pipeline. Code base of the milestone Tested and optimized medical query-response AI

A fully trained Dr. Robot Medical AI Knowledge Base capable of understanding and responding to complex medical and mental health inquiries. An AI reasoning core equipped with advanced diagnostic logic for symptom interpretation disease correlation and treatment recommendation.

$10,000 USD

success_criteria_1

This milestone focuses on building Dr. Robot’s multilingual and multicultural intelligence enabling seamless communication and medical reasoning across global languages and dialects. The goal is to create an AI system that listens understands and responds with empathy and medical accuracy—no matter the user’s linguistic background or cultural context. Dr. Robot’s Multilingual Support layer will integrate advanced transformer-based language models fine-tuned for medical dialogue in English Hausa Igbo Yoruba Swahili Amharic and additional African and global languages. It will feature context-aware translation pipelines allowing real-time cross-lingual conversation between patients and the AI without loss of meaning or diagnostic accuracy.

Fully functional multilingual communication module with real-time translation and response generation. Fine-tuned medical language models for six core languages (English Hausa Igbo Yoruba Swahili Amharic).

$5,000 USD

success_criteria_1

This milestone focuses on developing Dr. Robot’s voice intelligence system empowering natural real-time verbal interaction between users and the AI. The goal is to make Dr. Robot a fully conversational medical companion capable of understanding human speech detecting emotional tones and responding with empathy and clinical accuracy through lifelike voice synthesis. The Speech-to-Text (STT) component will use state-of-the-art multilingual speech recognition models trained on diverse medical conversations and dialects. It will accurately transcribe patient speech even in noisy environments capturing nuances like stress hesitation or emotional strain—key indicators for mental health assessment. The Text-to-Speech (TTS) engine will generate human-like context-sensitive responses allowing Dr. Robot to speak naturally in multiple languages including English Hausa Igbo Yoruba Swahili and Amharic. Voice profiles will be adaptive—soft and reassuring for mental health contexts professional and precise for medical diagnostics.

Fully integrated multilingual STT system for accurate real-time transcription of patient speech. Advanced TTS engine generating natural context-aware responses in multiple voices and languages.

$5,000 USD

success_criteria_1

This milestone establishes Dr. Robot’s Computer Vision Intelligence enabling the AI to see analyze and interpret visual and behavioral cues just like a real medical professional. By integrating advanced vision-language models (VLMs) and deep neural networks Dr. Robot will gain the ability to visually assess both physical health conditions and emotional states during consultations. The system will leverage convolutional neural networks (CNNs) transformer-based vision models (e.g. ViT CLIP and SAM) and multimodal fusion techniques to process medical imagery webcam inputs and facial behavior patterns. This will allow Dr. Robot to detect skin anomalies rashes eye discolorations facial asymmetries and micro-expressions that signal emotional distress or early signs of mental health decline. By merging visual and textual understanding Dr. Robot will be able to correlate physical symptoms with spoken or written inputs forming a deeper and more holistic diagnostic reasoning process. The computer vision module will also adhere strictly to ethical privacy and medical safety standards ensuring that no visual data is stored or misused.

Fully trained computer vision model for detecting visual medical indicators and emotional expressions. Integrated multimodal reasoning engine combining visual data with text and speech inputs.

$5,000 USD

success_criteria_1

This milestone focuses on transforming Dr. Robot into an intelligent mobile-first medical companion accessible anytime and anywhere through an intuitive smartphone application. The goal is to deliver a seamless multilingual and multimodal experience combining voice text and visual interaction to make healthcare and mental wellness support universally available. The mobile app will integrate all core AI capabilities — Medical Knowledge Base Multilingual Support Speech-to-Text (STT) Text-to-Speech (TTS) and Computer Vision AI — into a single secure interface. Users will be able to speak directly with Dr. Robot upload or capture medical images receive diagnostic insights and access personalized mental health check-ins.

Fully functional mobile app (Android and iOS) integrating all Dr. Robot AI modules. Real-time voice text and visual interaction system. Cloud backend for AI reasoning model updates and data storage. Secure user authentication and encrypted communication framework. Multilingual and offline support for global accessibility. User experience testing and performance optimization for smooth real-world operation.

$5,000 USD

success_criteria_1