I just want to say that the support we received from you, your team, and Saddam during my time at Falcon 180B was exceptional. It was honestly hard for the internal team to believe that this level of work came from Pakistan.
Zia Ur Rahman
CTO Falcon 180B
Large Language Models (LLM) Case Studies
Project Category: LLM OpenAI
Client: Hugging Face Inc. & OpenAI (contract team)
Service Definition: Added custom vocabularies to the V3 model of Whisper with the OpenAI contract team
Summary: This is how we collaborated with Hugging Face — we added custom vocabularies to the V3 model of Whisper alongside the OpenAI contract team. Our team enhanced the Whisper V3 model by integrating custom vocabulary in collaboration with OpenAI. This project improved functionality and demonstrated our commitment to advancing open-source technologies alongside organizations like Hugging Face and OpenAI.
- Improved recognition accuracy by integrating custom vocabularies.
- Balanced performance across various use cases and languages.
- Provided a scalable solution in line with Hugging Face’s open-source principles.
- Adaptable model suitable for industries like healthcare, education, and customer service.
- Enhanced the Whisper V3 model through collaboration with Hugging Face and OpenAI, demonstrating innovative teamwork.
Extended Detail: Our partnership with Hugging Face Inc. aimed to enhance the Whisper V3 model, an advanced automatic speech recognition tool. Hugging Face provides an open-source ML platform for creating, training, and deploying models, featuring a library of solutions like Transformers. The project focused on integrating custom vocabularies into Whisper V3 to meet specific user needs and improve accuracy across various applications.
Client: The Technology Innovation Institute (TII), Falcon 180B
Service Definition: Developed advanced algorithmic design and deep learning architectural enhancements.
Summary: We developed an advanced optimization framework to transform Falcon 180B into a production-ready large language model. This approach tackled key challenges while preserving architectural integrity, ensuring consistent, efficient, and secure performance across computational environments.
- Reduced data redundancy by 90%, enhancing response precision by 70%.
- Achieved a 30% reduction in overhead, leading to a 40% increase in training speed.
- Cleansed dataset reduced bias-related errors by 35%, improving output diversity.
- Optimized Falcon 180B’s processing capacity by 50% to manage larger datasets and complex tasks.
Open Source Contributions
Project Category: Google’s Open Source Projects
Client: Google (Kubernetes and Fuchsia)
Service Definition: Provided patches, bug fixes, and novel feature requests.
Summary: Our software development team played a key role in advancing Google’s Kubernetes and Fuchsia projects. We provided deep technical contributions that enhanced system functionality, stability, and performance.
- Maintained a high approval rate for submitted patches and feature proposals.
- Implemented new features improving scalability and system usability.
- Contributed to critical bug fixes, elevating platform stability and runtime performance.
- Strengthened partnership with Google through our developer license and consistent contributions.
Detailed Description: Our case study illustrates how our dedicated team of technologists strategically enhanced two of Google’s flagship open-source platforms — Kubernetes and Fuchsia. Through precision coding, innovative feature integration, and rigorous quality control, we advanced the ecosystem of both platforms. Our work demonstrates technical leadership in scalable infrastructure (Kubernetes) and next-gen OS architecture (Fuchsia), reinforcing our team’s position at the forefront of global open-source innovation.
Healthcare Case Studies
Project Category: AI-Robotic Assisted Surgery, Healthcare
Client: Mayo Clinics, Florida
Service Definition: AI, Advanced NLP robotics, and medical imaging
Summary: We developed a cutting-edge AI-enabled robotic surgery software platform for Mayo Clinics, integrating NLP, imaging, and robotics to drive greater surgical precision and better outcomes.
- Enhanced surgical precision and efficiency through AI and imaging feedback.
- Reduced patient recovery time and improved clinical results.
- Streamlined integration of robotic systems into surgical environments.
- Reinforced Mayo Clinic’s global leadership in tech-driven healthcare innovation.
Detailed Description: Our team engineered a real-time intelligent platform combining AI algorithms, haptic feedback systems, and high-resolution medical imaging. This enabled surgeons to perform complex procedures with greater accuracy and control. The solution allowed intraoperative insights, minimized risk factors, and supported decision-making, creating a new benchmark for surgical care and robotics in medicine.
Project Category: Healthcare, AI Copilot
Client: Woebot Health
Service Definition: Cutting-edge Behavioral Health Copilot, Conversational AI
Summary: We aimed to enhance Woebot’s user experience by integrating advanced natural language processing for empathetic and accurate responses. Additionally, we developed a scalable backend infrastructure to handle high interaction volumes efficiently.
- Scalable support and evidence-based mental health interventions.
- Conversational AI with emotional recognition improves user engagement.
- Seamless integration into enterprise ecosystems for broader adoption.
- High compliance and data security standards to ensure trust.
Detailed Description: Woebot is an advanced behavioral health copilot that leverages conversational AI to deliver mental health support through scientifically grounded techniques. Our team focused on building a robust and adaptive platform that not only provides empathetic conversations but also scales effortlessly for high-demand environments. By prioritizing emotional intelligence, backend scalability, and privacy compliance, we enabled enterprises to adopt a trustworthy and transformative tool for digital mental healthcare delivery.
Project Category: Healthcare, Product
Client: OlaDoc
Service Definition: Development and Enhancement of OlaDoc’s Algorithm
Summary: We focused on developing a robust matchmaking algorithm that would accurately connect patients with the most suitable healthcare providers based on their specific needs and preferences. This involved leveraging machine learning models to analyze historical data, predict user behavior, and continuously refine the matchmaking process.
- More accurate and faster doctor recommendations improved user satisfaction for millions.
- Streamlined search and booking workflows increased efficiency for both users and healthcare providers.
- The algorithm supports OlaDoc’s expanding user base and growing geographic footprint.
Detailed Description: OlaDoc aimed to improve its platform’s efficiency, user satisfaction, and operational capabilities through advanced algorithmic solutions. The goal was to refine its doctor-patient matchmaking system using predictive analytics and machine learning. Our team designed a scalable, adaptive solution that continually improves recommendation accuracy based on real-world interaction data. The system was also optimized to ensure high responsiveness and smooth integration into OlaDoc’s infrastructure, supporting long-term growth and healthcare accessibility across Pakistan.
AI Security Case Studies
Project Category: AI, Security
Client: Key Technical International (KTC)
Service Definition: Deploy an AI-driven offensive language detection system
Summary: We partnered with KTC Qatar to deploy an AI-driven offensive language detection system at Hamad International Airport, achieving 95% accuracy and significantly enhancing security operations.
- 95% accuracy in detecting offensive language, reducing escalation risks.
- 30% reduction in false positives, increasing system trust and dependability.
- 60% reduction in manual monitoring effort through automation.
- 40% faster response time to flagged incidents.
- Adapted detection model to understand regional linguistic and cultural variations.
- Designed as a scalable solution suitable for deployment in other high-traffic KTC-managed environments.
Detailed Description: In partnership with KTC Qatar, we aimed to enhance security infrastructure at Hamad International Airport by implementing an automated offensive language detection system. Our solution used machine learning and NLP to identify threats in real-time, allowing airport security teams to intervene swiftly and appropriately. By significantly reducing false positives and supporting regional linguistic nuance, our system ensures a more respectful, responsive, and secure environment. The project reflects a broader commitment to applying AI to critical public safety infrastructure across the Gulf region.
Real Estate
Client: HouseCanary
Service Definition: Deployed Advanced Machine Learning Models
Summary: We used data-driven insights to enhance HouseCanary’s property valuation and forecasting models, increasing predictive accuracy and system responsiveness through advanced machine learning algorithms.
- Valuation accuracy improved to a median absolute percentage error (MAPE) of 2.8%.
- 12-month forecast models incorporated 200+ market signals, leading to 40% improved prediction reliability.
- Reduced model retraining time by 60% with automated pipelines.
- Improved usability for end-users with a new API-integrated frontend for faster client delivery.
Client: Divvy Homes
Service Definition: AI-powered virtual assistant using NLP
Summary: We implemented an AI virtual assistant to improve Divvy Homes’ customer experience and internal operations. The assistant adapts through learning, reducing manual workload and enhancing user satisfaction in the rent-to-own process.
- 45% reduction in average query resolution time, boosting user satisfaction.
- 30% increase in engagement rates—users rely on the assistant for end-to-end guidance.
- 70% of customer support queries automated, freeing human agents for complex tasks.
- 25% reduction in operational costs while maintaining service quality.
- AI assistant offers tailored credit improvement tips and savings plans.
- Increased confidence in the rent-to-own journey for prospective homeowners.
Client: ImmoPass
Service Definition: Development of advanced technical audit tools
Summary: We developed custom audit tools tailored to ImmoPass, a pioneering technical control firm in Luxembourg, to enhance real estate evaluations. The tools enable greater accuracy, speed, and consistency across property inspections.
- 50% reduction in audit processing time, increasing service capacity.
- Real-time data validation improved the precision of inspections.
- Automated, clear reports enhanced client decision-making.
- Supported informed investment and maintenance strategies.
FinTech & SaaS Case Studies
Project Category: Web & Mobile, Payment Solution, FinTech
Client: Azira Coperation
Service Definition: We developed AziraPay, which includes the Azira Payment Hub (APH) and tailored solutions for domestic and international payment systems.
Summary: We partnered with Azira Coperation to develop AziraPay—a unified, scalable payment solution that achieved $200M in annual revenue. The system addressed fragmented payment issues and expanded Azira’s market reach.
- Contributed to AziraPay’s evolution, reaching $200M in annual revenue.
- Unified payment systems simplified operations and workflows.
- Secure mobile apps improved user satisfaction.
- Platform built for market and payment channel expansion.
Detailed Description: AziraPay was designed to tackle fragmented payment processing that hindered merchants. With our development of the Azira Payment Hub (APH), AziraPay consolidated domestic and international systems into one streamlined platform. This significantly improved transaction efficiency and user experience. Our collaboration resulted in a secure, scalable solution that enabled Azira to capture greater market share, culminating in $200M in annual revenue.
- Delivered a multi-layered encryption framework that protects sensitive digital health data.
- Developed a customizable coin and token system tailored to WellTech’s unique ecosystem needs.
- Enabled secure and efficient peer-to-peer and business-level transactions.
- Built a system that is intuitive for both technical users and non-technical partners.
- Future-proofed the architecture to adapt with WellTech’s growing platform and user base.
Project Category: Sports, Computer Vision, SaaS Product
Client: Skillocity
Service Definition: Cutting-edge Hawkeye system leveraging state-of-the-art (SOTA) computer vision architecture and machine learning techniques.
Summary: Our team developed a high-precision Hawkeye system for Skillocity, initially deployed in professional tennis. The solution set a new industry benchmark and now operates worldwide, generating over $100M in revenue.
- Delivered sub-millimeter accuracy, setting new standards in sports object tracking.
- Used globally in international tennis matches for real-time analysis and decision-making.
- Modular design allows easy adaptation for other sports, boosting scalability.
- Enhanced broadcast quality with real-time analytics and engaging visual overlays.
Detailed Description: Skillocity aimed to revolutionize its sports analytics offerings by integrating advanced real-time data processing. We built a state-of-the-art Hawkeye system using cutting-edge computer vision and machine learning. The system tracks player and ball movement with extreme precision and reliability. Since its initial use in tennis, it has become a global standard in sports analytics and broadcasting, helping Skillocity surpass $100M in revenue.
Project Category: IT & SaaS Product
Client: Bright MLS
Service Definition: Developed and deployed a Machine-Learning-Enhanced MLS platform with integrated tool library.
Summary: Our team engineered a next-gen MLS platform for Bright MLS, leveraging machine learning to deliver predictive analytics and improve real estate decision-making. A custom tool library streamlined workflows and boosted user efficiency across the platform.
- Achieved 90% accuracy in predicting property trends and market shifts.
- Enabled accurate forecasting of property values and buyer demand using AI models.
- Reduced property discovery time by 70% through AI-driven search tools.
- Cut manual data analysis efforts by 60% through automation.
- Enhanced decision-making for over 100,000 real estate professionals across the Mid-Atlantic.
Detailed Description: Bright MLS supports over 100,000 real estate professionals with more than 500,000 transactions monthly. To elevate data intelligence, we developed a machine-learning-enhanced MLS platform equipped with predictive models for real-time insights. The complementary tool library simplified workflows, improved forecasting, and empowered users with faster, more accurate decision-making. This platform transformed how real estate data is interpreted and acted upon across the region.
Project Category: SaaS Product
Client: CrowdReviews
Service Definition: Algorithm development and implementation of feedback abuse prevention mechanisms.
Summary: Our team led a complete overhaul of CrowdReviews, delivering algorithmic enhancements to ensure ranking integrity and implementing abuse prevention systems. These updates significantly improved the platform’s trustworthiness and usability for users seeking genuine service feedback.
- Developed a bias-resistant algorithm to rank products and services with accuracy and fairness.
- Reduced fake reviews and manipulation, increasing platform credibility.
- Modernized the UI/UX design for a more intuitive and visually appealing experience.
- Optimized for seamless navigation and responsive performance across devices.
- Built a scalable backend infrastructure to handle growing user traffic and data complexity.
Detailed Description: CrowdReviews is a user-driven review platform that empowers consumers with insights on software and services. Competing with sites like G2 and Clutch, it required a full revamp to improve credibility and user experience. We redesigned the architecture, built a trustworthy algorithm, and implemented robust abuse controls. The result is a platform that provides more reliable, transparent, and user-friendly review experiences, giving consumers confidence in their purchasing decisions.