Makeintellix AI

Overview

A leading US-based beauty retailer sought an AI-driven solution to enhance customer engagement and provide personalised skincare recommendations. The goal was to create a mobile application that leverages facial recognition and intelligent analysis to tailor beauty routines, focusing on anti-aging treatments and skincare personalisation.

Solution

Our team developed a sophisticated mobile application powered by Computer Vision, advanced facial recognition, and AI-driven recommendation capabilities. Using Dlib-based detectors and deep learning algorithms, the system accurately identifies 126 facial feature points from user selfies. This biometric data enables precise skin analysis, assessing concerns such as wrinkles, dark circles, and skin texture. The app integrates ChatGPT to generate tailored product recommendations and expert beauty tips, delivering a seamless and interactive user experience.

Outcome

The AI-powered application transformed the customer journey by offering highly personalised skincare solutions. Within six months of deployment, the retailer saw a 32% increase in customer engagement, a 24% boost in conversion rates, and a 17% reduction in product return rates due to better-informed purchasing decisions. The solution positioned the client as a pioneer in AI-driven beauty personalisation, setting new industry standards for customer interaction and product recommendations.

Overview

A rapidly expanding real estate brokerage with 170+ agents across multiple markets was experiencing significant operational friction. Their agents lost 12-15 hours weekly to administrative tasks, paperwork, and client communication management. Meanwhile, their support staff struggled with an unmanageable volume of transaction coordination, leading to processing delays, compliance risks, and agent frustration.

Solution

We engineered an intelligent automation ecosystem that seamlessly integrates with their existing CRM and transaction management platforms. The system's cognitive processing engine automatically extracts critical data from emails, contract documents, and inspection reports with 99.3% accuracy. Our solution implements dynamic workflow orchestration that routes tasks based on transaction stage, deadline proximity, and agent preferences. The platform features contextually aware communication automation that handles routine client inquiries while recognizing complex scenarios requiring human intervention. We incorporated predictive analytics that anticipates documentation requirements based on transaction patterns, proactively preparing materials before they're requested.

Outcome

The automation platform dramatically transformed the brokerage's operational model, yielding immediate and sustained results. Agents reclaimed an average of 10.4 hours weekly, directly increasing showing appointments by 37% and signed listings by 22%. Transaction processing time decreased from 8.7 days to 2.1 days while compliance violations dropped by 91%. Client satisfaction scores improved by 33 percentage points, with particular gains in responsiveness and process transparency. The brokerage scaled operations by 43% without adding administrative headcount, resulting in $842,000 annual operational savings. Six months post-implementation, the firm reported a 26% increase in agent retention, attributing the improvement directly to the enhanced operational support.

Overview

A global investment firm managing over $8 billion in assets approached us with a critical challenge: their analysts were spending 20+ hours weekly manually monitoring financial news to detect market sentiment shifts that could impact stock performance. This labor-intensive process created unacceptable delays in responding to market-moving events and limited their ability to scale coverage across their diversified portfolio.

Solution

We developed a real-time financial news intelligence system that continuously monitors thousands of trusted sources across traditional media, financial publications, and social platforms. The technology employs advanced natural language processing algorithms to identify subtle sentiment indicators in news coverage of public companies. Our system detects linguistic patterns that correlate with subsequent market movements, distinguishing between routine coverage and potentially significant events. The platform automatically weighs source credibility, contextualizes information against historical patterns, and generates quantified sentiment scores that integrate directly with the firm's existing trading models.

Outcome

The implementation transformed the firm's market intelligence capabilities with measurable impact on performance. Their analysts now receive actionable insights 4.6 hours faster on average than competitors relying on traditional methods. The system has demonstrated 82% accuracy in predicting significant price movements following news events. The firm executed $42 million in profitable trades specifically attributed to early detection of sentiment shifts identified by our system. Portfolio managers expanded coverage from 120 to 470 companies without additional analyst headcount. The technology delivered a 311% ROI within the first year through combined cost reduction and enhanced trading performance.

Overview

We partnered with a digital health startup to develop a comprehensive physiotherapy application addressing the critical gap in accessible rehabilitation services. Their existing model relied on in-person therapy, limiting reach and scalability while patients struggled with treatment adherence between sessions. The client sought a technology solution that could deliver personalized rehabilitation programs remotely while maintaining clinical efficacy.

Solution

We engineered a sophisticated AI-driven physiotherapy platform that revolutionizes injury recovery through intelligent personalization. The system leverages computer vision algorithms to analyze patient movement patterns during exercise performance, providing real-time feedback on form and technique. Our proprietary rehabilitation engine synthesizes clinical protocols with individual progress data to dynamically adjust recovery pathways. The platform features an advanced conversational AI that simulates therapist interactions, answering questions and providing motivational support throughout the recovery journey. We implemented a comprehensive progress tracking system with visual analytics that reinforces patient adherence through behavioral psychology principles.

Outcome

The platform transformed our client's rehabilitation model, achieving remarkable clinical and business results. Patient adherence to prescribed exercise regimens increased by 78% compared to traditional take-home instructions. Users reported a 42% reduction in perceived pain levels within the first three weeks of program engagement. The application shortened average recovery timelines by 3.5 weeks while maintaining equivalent clinical outcomes to in-person therapy. Healthcare providers using the platform experienced a 67% increase in patient capacity without additional staffing. The client secured $3.2M in Series A funding within six months of launch, directly attributable to the platform's demonstrable efficacy and market potential.

Overview

Our client, a business brokerage firm, faced the challenge of efficiently identifying qualified acquisition targets and connecting with decision-makers. Their traditional lead generation process involved manual research across fragmented data sources, resulting in incomplete information and excessive time investment per prospect.

Solution

We engineered an advanced AI-driven lead acquisition system that transforms simple location and business category inputs into comprehensive, actionable lead databases. The technology employs sophisticated web crawling algorithms coupled with natural language processing to navigate business directories, corporate websites, and professional networks. Our system intelligently identifies organizational hierarchies, extracts primary decision-maker contact information, and defaults to verified company communications channels when individual contacts are unavailable. The architecture prioritizes data accuracy through cross-referencing multiple sources while maintaining compliance with relevant data privacy regulations.

Outcome

The implementation revolutionized our client's prospecting capabilities, reducing the lead generation cycle from weeks to mere hours. Their acquisition specialists now leverage datasets with 87% higher contact accuracy compared to previous methods. The firm realized a 4.2-fold increase in initial conversation rates and shortened their average deal development timeline by 36 days. Within the first two quarters of deployment, they attributed $1.2 million in additional transaction value to leads exclusively sourced through our system. Perhaps most significantly, the technology enabled a 68% reduction in prospecting labor costs while expanding their addressable market by an estimated 340%.

Overview

Our client, a mid-sized B2B services firm, struggled with scaling personalized outreach while maintaining high response rates. Their sales team spent 15+ hours weekly researching prospects and crafting individual emails, creating a significant bottleneck in their pipeline.

Solution

We developed an AI-powered cold email system with seamless HubSpot integration that:

• Performs automated deep research on target companies via website scraping and semantic analysis
• Extracts relevant professional insights from LinkedIn profiles using our proprietary engagement algorithm
• Generates hyper-personalized emails that reference specific company challenges, recent achievements, and leadership priorities
• Maintains brand voice and sales messaging consistency through our fine-tuned language model
• Scales to handle thousands of contacts while preserving the impression of individual attention

Outcome

The solution delivered measurable business impact within the first quarter:

• 43% increase in email open rates compared to previous templated approaches
• 67% reduction in time spent on prospect research and email composition
• 3.2x improvement in meeting conversion rate from cold outreach
• $230,000 in new pipeline opportunities attributed directly to AI-generated communications
• ROI of 411% on project investment within six months of deployment

Overview:

The Conversational AI Chatbot for a European bank is a refined digital assistant crafted to elevate customer service with human-like interaction. Designed to handle diverse banking queries, it leverages an expansive, integrated knowledge base to deliver precise answers and guidance—ensuring that customers feel heard and supported around the clock.

Solution:

Built with advanced natural language processing and machine learning, this chatbot taps into a dynamic knowledge base that continuously updates with the latest banking procedures, FAQs, and regulatory changes. It interacts seamlessly with the bank’s backend systems to provide personalized account assistance, transaction details, and troubleshooting support. The solution also features multilingual support and adaptive learning, which refine its responses over time. When complex issues arise, a smart escalation protocol ensures that customers are seamlessly transferred to human agents for further assistance.

Outcome:

Since implementation, the bank has seen a 40% reduction in call center traffic and a 25% boost in customer satisfaction. The chatbot now handles over 70% of routine inquiries, cutting response times by more than 30% and significantly enhancing overall operational efficiency—all while maintaining strict GDPR and data security standards.

Overview:

The AI Report Generation Software SaaS is an advanced, AI-driven solution designed to automate the creation of compliance reports. Tailored for sectors such as real estate, legal services, and accounting, the platform streamlines document processing, ensuring that every report is both accurate and consistent while meeting strict data security standards.

Solution:

Leveraging cutting-edge AI models (including GPT-4 variants) and on-premises NLP, the system ingests anonymized client documents and legislative files, dynamically fills industry-specific templates, and integrates picklist logic for nuanced content generation. Key features include automated data extraction, risk calculation based on predefined regulatory guidelines, dynamic variable insertion into macro-enabled Word templates, and real-time error detection with human handover protocols for quality assurance. This robust architecture is supported by a secure technology stack (Python, TypeScript, PostgreSQL, and React) that ensures scalability and compliance with global data protection standards.

Outcome:

The deployment of this solution reduced report generation time by up to 60%, while increasing output consistency by over 90%. Clients benefited from significantly enhanced regulatory compliance, a streamlined review process, and a scalable framework capable of adapting to future legislative changes, ultimately driving improved operational efficiency and reduced manual effort.