Check Our Awesome Portfolio

Financielle is a female-focused financial wellbeing app designed to help users take control of their money with confidence. Built on the foundation of a thriving community of over 40,000 women sharing their money journeys, the app goes beyond being just a budgeting tool. It’s a movement toward long-term financial wellness. Targeting the real struggles people face, such as impulsive spending, debt cycles, and inconsistent budgeting, the app empowers its users with tools, resources, and an encouraging community. With the success of the launch, Financielle has experienced 400,000+ downloads worldwide, secured recognition as 'App of the Day' in the Finance category, and won multiple prestigious awards in the UK fintech space.

The AI Knowledge Assistant App is an AI-powered chatbot that allows users to access company-specific information and documents.
Document formats that are supported include Text (TXT), Comma Separated Values (CSV), Portable Document Format (PDF), Microsoft PowerPoint (PPT), Microsoft Word (DOC), Microsoft Excel (EXL) as well as Links. Information can be organized in Knowledge Repositories and the AI chat can either access an entire Knowledge Repository or just a single document.
The AI Knowledge Assistant improves productivity and customer and employee satisfaction by allowing users (employees or customers) to find information faster, make informed decisions and reduce customer or second-level support costs.

Stork was created by parents who understood how stressful it can be to juggle school drop‑offs, practice runs, and changing schedules while still wanting to protect their children at every step. The product needed to feel like a trusted partner, simple enough for busy parents, but robust enough to handle real‑world transportation challenges. We worked closely with the client team to capture that vision in a unified platform: a Flutter app for iOS and Android, Node.js/Express APIs, a MongoDB‑powered data layer, and a web‑based admin panel for operations and support. The parent app focuses on booking and tracking rides, while the driver experience and admin tools handle route management, safety protocols, and customer support. Features like background‑checked drivers, live GPS tracking, OTP‑verified pickups, and detailed driver profiles are woven into the core flows so parents don’t have to compromise between convenience and safety. On the design side, we created a warm, reassuring visual language, clean layouts, friendly iconography, and clear status indicators, to make the app approachable while still communicating seriousness around safety and reliability.

Stork Driver was created to support a very sensitive transportation model: moving children safely and reliably, while making the driver experience smooth enough to work in real-world conditions. The app needed to be simple for drivers to use, but powerful enough to handle route updates, ride status changes, communication, and safety checks without confusion. Our team designed and developed a Flutter-based driver app backed by Node.js/Express APIs, MongoDB, AWS infrastructure, and an admin panel for operational oversight. The result is a platform where drivers can manage incoming requests, track trip details, and follow structured ride workflows that keep the experience consistent from pickup to drop-off. The interface was built with clarity in mind: clean screens, straightforward actions, visible trip states, and minimal friction during active rides. Since drivers often operate on the move, we focused on fast interactions and dependable performance so they can concentrate on the child’s safety and the quality of service.

Choosing a college and preparing for entrance exams can feel overwhelming—multiple websites, different deadlines, and scattered study resources. Unichoice was designed to cut through this confusion and act as a digital mentor for students and parents. Inside the app, students can browse and compare colleges, apply directly, join live exam coaching sessions, and access curated notes, PDFs, and preparation materials for key entrance exams. Real‑time updates keep them informed about admission news, application dates, and result‑based eligibility. From a product standpoint, our team delivered a cross‑platform Flutter app, Node.js/Express APIs, a MongoDB backend, and web‑based admin tools. These pieces work together to support features like college matching based on marks, personalized course suggestions, and content management for live classes and study resources. The UI/UX was crafted to feel supportive and distraction‑free, with clear flows for college search, exam prep, and notifications, so students can focus on their goals rather than fighting with the interface.

Traditional role‑plays and classroom trainings often struggle to feel realistic, repeatable, and scalable. The AI Conversation Coach app was created to solve that by giving employees a safe space to practice high‑stakes conversations with AI personas that respond dynamically, just like real customers or team members. Users log in through the mobile app or web app, select a scenario (for example, handling objections on a sales call or managing a difficult performance conversation), and then engage in a simulated dialogue with an AI counterpart. The AI adjusts its responses based on what the learner says, creating a natural flow instead of scripted Q&A. On the technology side, our team built Flutter apps for Android and iOS, backed by Node.js/Express APIs and a MySQL database, all deployed on AWS and integrated with a web front end built with HTML5, CSS3, Bootstrap, JavaScript, jQuery, and EJS. This stack supports real‑time chat, scenario configuration, role‑based access, reporting, and scalable AI usage through token‑based limits. The admin panel allows training managers to design their own conversation scenarios, define AI personas, assign modules to user groups, and review performance data, turning the app into a flexible training platform rather than a fixed set of lessons.

Motherhood can feel isolating, especially when you’re navigating pregnancy, newborn life, or toddler chaos without a local “village”. Kinship was created to solve exactly that: connect moms who are experiencing similar joys, challenges, and milestones, and give them a simple space to talk, share, and meet. Inside the app, moms and moms‑to‑be sign up, share a few details about their life stage, and get matched into small local chat groups based on due date or child’s age. These are not massive forums; they’re intimate circles where conversations feel personal and manageable. Our team used Swift for iOS, Jetpack Compose for Android, and Node.js/Express with MongoDB on AWS for the backend, with a responsive web app for broader access. This stack powers matching logic, group chats, notifications, and admin controls, while keeping data secure and performance smooth as Kinship expands to new cities.

College life is full of talented, creative, and social students, but many of them do not have a dedicated platform to showcase who they are. iKonic was created to give students a place where their personality, creativity, fashion, music, interests, and social presence can stand out. The app allows students from colleges and universities to connect, discover profiles, share content, and participate in a community built around student culture. Rather than functioning as another generic social media platform, iKonic focuses on campus life and gives users the chance to gain recognition for their creativity and social engagement. Our team developed the iOS experience using Swift, supported by Node.js and Express APIs, MongoDB, and AWS infrastructure. The admin panel provides centralized control over users, content, reports, categories, and community activity, helping the platform maintain a positive and engaging environment as it grows.

In blocks of flats, fire doors are critical for resident safety, but inspections are often scattered across spreadsheets, emails, and paper notes. Fire Risk Tracker was built to bring everything into one system: properties, flats, doors, inspections, findings, and reports. Managing agents upload flat‑specific details for each site, assign those sites to surveyors, and then rely on the mobile app for fieldwork. Surveyors log in, work flat by flat, and record information for every door, including photos and notes. Barcodes or QR tags are applied to doors to make follow‑up visits simple and to keep repeat‑visit history tied to each door. Once an inspection is completed and synced, surveyors and office teams can review the data through an online portal, generate reports, and share results with residents and contractors. Our team implemented this ecosystem using Swift and Kotlin for the mobile apps, PHP/Laravel and MySQL for the backend, and a responsive web app and marketing site hosted on AWS/GoDaddy.

Many important family stories disappear over time. Memories, traditions, achievements, personal experiences, and family history are often scattered across phones, social media platforms, old albums, and documents. Griot was created to bring these pieces together in one meaningful digital space. Users can capture moments as they happen through photos, videos, voice notes, written memories, and important documents. They can organise their stories, decide what remains private, and choose what they want to share with family members, friends, or future generations. The experience was designed to feel personal rather than overwhelming. Instead of encouraging users to post only polished highlights, Griot gives them the freedom to preserve ordinary moments, personal reflections, family milestones, and stories in their own words and voice. We developed the mobile applications using Kotlin for Android and Swift for iOS, supported by an HTML-based website. The platform was designed to make legacy-building simple, accessible, and emotionally meaningful across devices.

Managing weight and maintaining long-term health often requires more than a single consultation. Patients may need medical assessments, doctor reviews, dietary advice, treatment monitoring, and regular follow-ups. Medrev brings these steps together in one connected care experience. Through the app, patients can create their profile, provide relevant health information, book appointments, consult doctors, and access healthcare-related information. The platform helps patients stay connected with their care team while giving them a clearer understanding of their treatment journey. The app works alongside Medrev’s wider healthcare service, which includes patient assessment, doctor consultation, personalised treatment planning, and ongoing monitoring. Patients can also use the platform to track relevant progress information and share updates with their care team when required. The product was built with Kotlin for Android, Swift for iOS, and React.js for the web experience. The UI/UX focuses on clear navigation and easy-to-follow healthcare workflows, helping patients manage appointments and care without feeling overwhelmed.

Making plans with friends often sounds simple, but conversations can quickly become confusing. People suggest different dates, respond at different times, or leave messages unanswered. Eventually, the plan gets delayed or disappears completely. Planlark was designed to solve this familiar problem by giving users a structured way to move from discussion to decision. Users can create a plan, add the relevant details, invite friends, and receive clear yes-or-no responses. This removes the need to search through long message threads to understand who is interested, who is available, and what needs to happen next. The app was built with Kotlin for Android and Swift for iOS to provide a smooth native mobile experience. A React.js website supports the wider product ecosystem and gives the brand a flexible foundation for future social and planning features. From weekend outings and dinner plans to trips, celebrations, and group activities, Planlark helps people organise shared experiences without unnecessary back-and-forth.

AIServe was created as an early‑stage AI project with a very practical first step: make it effortless for people to order from a local restaurant without dealing with clunky websites or phone calls. The product starts with one partner restaurant and one delivery zone, proving the experience before scaling to more partners and features. In the app, users tap “Get Started” to view the curated menu, pick their items, and move through a streamlined checkout flow powered by secure Stripe integration. Once an order is placed, users can review their order history from inside the app, giving them a simple record of what they’ve ordered and when. Even users outside the current delivery zone can still explore the app and see how AIServe works, building familiarity for future expansion. Under the hood, the system is built in Flutter for a consistent Android and iOS experience, with a Node.js backend managing products, orders, users, and payment flows. The architecture is intentionally lightweight but structured to support the next phase: voice ordering with “Tria” (the AI assistant), scheduled orders, tipping, and multiple restaurants across larger service areas.

In textile and weaving businesses, costing is everything, but it’s often handled through manual formulas in notebooks or spreadsheets. That makes it easy to make mistakes and hard to respond quickly to price changes or new orders. TaanaBaana was created to solve this with a dedicated textile costing app that fits right into the daily workflow of mills and weaving units. Inside the app, users can enter details about warp and weft quality, yarn counts, densities, fabric width, and other key parameters. The app then calculates yarn consumption, weaving cost, fabric cost per unit, and estimated profit for a given order or design. Instead of re‑doing formulas each time, users can run multiple scenarios in seconds and save or export the results as professional‑looking reports. Built with Flutter and Dart, TaanaBaana offers a consistent experience across Android and future iOS deployment. A Node.js backend powers user accounts, saved calculations, and report management, while the admin panel allows the client to configure formulas, update defaults (like overheads or conversion factors), and support users as the product evolves.

Many people want to support local businesses but don’t always know who is nearby, what they offer, or whether they accept online orders. Golocal was built to solve that by acting as a digital bridge between customers and local shops, restaurants, home services, and other neighbourhood providers. With the Golocal customer app, users can create an account, set their location, and instantly see a list of nearby businesses inside the app. They can browse categories, view store or service profiles, explore products or service offerings, and place orders or service requests directly through the app. The experience is designed to feel like walking through a local market, only smarter, searchable, and available in your pocket. On the tech side, native Android (Kotlin) and iOS (Swift) apps handle the customer experience with smooth navigation and responsive design. A Laravel‑powered backend with a MySQL database manages user accounts, business listings, categories, orders, and ratings. The admin panel, built using HTML, CSS, Bootstrap, jQuery, and Laravel views, lets the Golocal team onboard new businesses, manage content, configure service areas, and track marketplace activity.

LesMeet was born from a simple need: there wasn’t a focused, safe, and modern space where lesbian women could connect with each other, discover events, and feel like the platform truly understood them. Instead of trying to be “for everyone”, the founders wanted an app built around one community, with features that make it easier to meet people both online and offline. In the app, users create profiles, share interests, and set preferences for how they want to connect: friendship, dating, networking, or events. A feed and discovery flow help them find other women nearby, chat through in‑app messaging, and see curated events hosted within the community. Built in Flutter, LesMeet runs smoothly on both Android and iOS, while a Node.js backend and EJS admin panel power user management, event listings, moderation, and content controls. The product intentionally feels more like “a community that happens to have dating” than “a dating app with a community bolt‑on”, with a focus on safety, warmth, and offline experiences such as meetups, parties, and local gatherings.

Traditional Assamese attire like Mekhla Chador has strong demand, but many aspiring resellers struggle with inventory costs, photography, and shipping operations. The client wanted a digital platform where they could handle stock and logistics centrally, while resellers focus purely on marketing and customer relationships. Inside the app, resellers browse an extensive catalogue of Mekhla Chador and Assamese sarees, organised by fabric, motifs, and design style, then share high‑quality product photos directly to WhatsApp, Facebook, Instagram, and other channels. When a customer confirms, the reseller places the order through the app and the product is shipped straight to the customer’s address in plain packaging that carries only the reseller’s name and phone number. Our team implemented the app in Flutter for both Android and iOS, with Node.js/Express APIs, MongoDB, and an admin panel on top of AWS and GoDaddy hosting. This stack powers catalogue management, stock visibility, orders, discounts, and tracking, giving Mekhla Chador Hub an end‑to‑end reselling engine while keeping the front‑end experience simple for resellers across Assam and beyond.

Where the core AI Job Interview Coach app focuses on accessible practice for everyone, the Pro version was designed for learners who want more intensive training—longer sessions, richer scenarios, and premium AI coaching. In AI Job Interview Coach Pro, users can access expanded question sets, advanced personas, and structured practice paths. Sessions are powered by the AI Coach Pro engine, which simulates realistic hiring managers and responds dynamically to user input, creating a lifelike interview environment. Our team implemented the product using Flutter (Dart) for cross‑platform mobile, Node.js/Express for the API layer, MySQL for data storage, and a responsive web app for browser‑based practice. Subscription and in‑app purchase flows are tied to tokens or coins that learners consume when attending interviews, aligning the business model with actual training usage. The admin panel gives Blue Elephants Solutions full control over pricing, tokens, scenarios, personas, and reporting, enabling them to run different Pro offerings for universities, bootcamps, and corporate clients.