Our client provides companies with passwordless authentication solutions. They consider passwords a significant security risk and the root cause of data breaches. Their goal was to eliminate this issue by introducing various mechanisms for user authentication without the need for passwords.
Line of business
Network Security
Founding year
2014
Size
100 > employees
Before engaging our services, HYPR faced challenges in finding the right talent to develop their innovative passwordless authentication solutions. The demand for skilled professionals in the United States, where HYPR is based, was high, and most candidates preferred working for large corporations rather than small companies.
To address the problem of eliminating passwords, HYPR sought to expand their engineering team. They aimed to hire skilled professionals who could contribute to the development of their authentication solutions. They approached our company to find the best talents.
HYPR approached us seeking the best talents for their project. During our discussion, it became clear that they would find those talents right here with us.
Our team consisted of five members: full-stack developers proficient in React and Kotlin, backend developers with Kotlin expertise, an Android developer, and an iOS developer. Initially, they brought on board a portion of the team (2 individuals). Once they were satisfied with our employees’ performance and the client had more substantial financial resources, they proceeded to hire the next members of the team.
HYPR primarily utilizes technologies such as React, Kotlin, Fido, and Fido2 for their passwordless authentication solutions. They also integrate with identity providers like Microsoft Azure and Google. Their product portfolio includes solutions for various platforms, including desktop, Windows, macOS, mobile applications, and server components.
Used Technologies.
Our team supported both cloud and on-premises installations of HYPR’s solutions. We maintained backward compatibility and ensured seamless version management for their various components.
We focused on implementing passwordless authentication mechanisms using Fido and Fido2 standards. Additionally, we integrated with major identity providers like Microsoft Azure and Google.
Our team also worked on creating virtual USB devices to facilitate authentication, a requirement of the Fido2 protocol. Moreover we take part in maintenance stories, and each of us has some maintenance shifts (weekly shifts) while we await incidents and resolve issues.
HYPR successfully expanded their engineering team, addressing their staffing and competence gaps. Their passwordless authentication solutions were enhanced and integrated with various platforms. They continued to serve some of the largest banks in the United States.
We take great pleasure in sharing our high level of satisfaction with the DAC’digital team. We have no plans for any changes in our collaboration and are enthusiastic about the prospect of continuing to work with our exceptionally talented team members.
The company is a leading global online travel agency focused on the hostel market. It enables travelers to experience new places and people in a fun, memorable and safe way.
The client was transforming their core product, implementing many new ideas and solutions. Due to the tight schedule, they’ve asked DAC.digital for help to support some features in parallel.
We’ve provided a FullStack developer supporting Social Cues as a part of the project. We developed a small microservice, a proxy, and a cache for their legacy API.
These numbers represent the value we provided to the business through new enhanced functionality.
Social network effect.
50% of their bookings were made by customers who had opted into the social network (social members).
Usability.
More than 80% of their social members used the features while traveling.
Engage.
In the first six weeks post-acquisition (new customers acquired April – September 2022), social members were 4x more likely to be recruited via the App.
Effect.
Travelers make 1.6x the number of bookings and are twice as likely to make these bookings via the App
The customer project’s goal was to develop a platform for solo travelers to socialize before and during a hostel stay. They were introducing several new features, including the “See Who’s Going” option. A visitor would receive information on other people who will stay at the same place at the same time a few days before a scheduled overnight arrival.
To accomplish this part of the project, they needed information on who was staying at the hostel and on what dates. The old implementation, however, was quite slow, and the API was incompatible.
Work began immediately after one meeting with Product Owners and developers, where they explained what was needed.
The team behind the project consists of 1 Fullstack Developer. Because a client has several teams and multiple Product Owners responsible for delivering projects, a developer on our side was coordinating work with their internal developer.
Progress of the project was presented during demos to the client’s PO, but most of the work was done independently.
Used Technologies.
Our part of the project was used to simplify access to the client’s API, transform responses, and cleverly cache them.
The client requested the development of a proxy that functions as an overlay capable of retrieving statistics from an endpoint. The proxy converts the data and returns it in the requested form.
Later, other microservices used it to display information about who else stays in the hostel you just ordered.
The client was very pleased with our work and our contribution to this part of the project. The project as a whole concluded successfully, which the client wrote about on the website and in a special report. Our customer emphasized the visible effectiveness of the “See Who’s Going” feature in the preliminary results announcement.
Amini is a purpose-built data infrastructure that addresses the lack of environmental information in Africa. In order to promote economic inclusion for farmers and supply chain resilience across Africa and beyond, they have built a comprehensive solution that collects, measures, and processes geospatial and soil parameters, such as soil moisture, air temperature, weather conditions, filtered satellite images, NDVI and NDII indexes, etc., to conclude if the land owner qualifies for insurance benefits in case of environmental factors that affected the faulty harvest or lack thereof.
Our challenge was to prepare an intelligent and scalable end-to-end system from scratch that could effectively process and integrate loads of data inputs, utilising DRF, FastAPI, and blockchain technologies in the form of a microservice for farmers and insurers.
The exponential data load posed a challenge to adjusting the architecture and fitting it to queue the data processing in the most efficient manner.
We supplement the client’s team with the missing skills and competencies based on the project’s needs (2 Backend Developers, 1 Front-end Developer and 1 DevOps Engineer) to become a major part of their core-team.
Our team translated business requirements into the architectural vision for the entire platform. As the most senior engineers, we also provide mentoring, conduct code reviews, and assist with establishing best practises. Additionally, we actively develop core elements of the ecosystem.
Preparing a prototype with MVP functionality (APIs, basic blockchain architecture, microservices architecture) to prove to investors and potential clients that Amini has the capability to collect and process the base data and integrate its system with the external API, as well as lay the foundation for integration with future components.
The prototype enables the user to input the farm’s geographical coordinates and returns details such as the relevant crop calendar for that land allotment and base soil parameters, enabling the user to understand and predict future events that may affect their harvest.
Translating the existing features into a business solution in the form of a microservice platform by adding authentication processes and deploying the system on AWS with the use of Kubernetes according to the best standards of security and scalability. Another important part of the phase was introducing the data queuing systems as well as preparing the frontend part of the project to provide the UX/UI for the end users.
As we supplemented the team with the missing competencies, our developers are currently working on the maintenance of existing features and the integration with the new components, working towards making the solution market-ready.
Implementation
– Key decisions.
The architecture deployment issues – we chose AWS as the most reliable cloud vendor because we are experienced working with vast scaling opportunities, and Kubernetes because of its autoscaling capabilities, error resistance, and auto-healing.
We decided to go with ArgoWorkflows, – the innovative processing solution that is cost-effective, extendable, scalable, and streamlines the deployment process.
By integrating authentication procedures and deploying the system on AWS via Kubernetes in accordance with the best practises for security and scalability, the current features have been transformed into a business solution in the form of a microservice platform. Data queuing technologies were also included during this phase, and the frontend of the project was ready to provide a user-friendly interface and experience.
DAC.digital played a crucial role in helping the customer bootstrap their engineering culture, fostering an environment that promotes collaboration, innovation, and best practices. Through our guidance and expertise, we supported the customer in establishing a strong foundation for their engineering team.
The naval transportation industry faces unique challenges. The distribution and validation of paper documents can face delays and other mistakes due to the nature of the industry. Digitisation of the records makes the processes much more efficient and quicker. However, delicate matters need an infallible level of security against
To ensure protection against data breaches, insider threats and cyber attacks, the security solutions must be free from a single point of failure that could eradicate it. The system would also have to ensure data manipulation is easily detected.
Despite being the backbone of global trade, the maritime industry needs to catch up to digitisation compared to other sectors. Nevertheless, several facets of the naval area have been modernised, and blockchain has found its place among the used solutions.
Therefore, the proposed solution must address multiple issues and stay a few steps ahead of possible cyber threats, unauthorised access, or undetectable data manipulation. Fortunately, we found one that works from various angles and helps to ensure proper authentication.
Rexs.io is an authentication and notarisation solution that bases its work on blockchain. Using blockchain – a modern distributed ledger – allows different parties to record information in a permanent, immutable, tamper-proof, and transparent manner. The data is stored on a decentralised ledger and in a distributed system without the aid of a central authority.
The integrity of the blockchain is secured by trustless consensus algorithms and guarded by cryptography, making it impossible to append or modify historical data illegally. Therefore, blockchain is a decentralised, tamper-proof, immutable, and constantly growing list of cryptographically linked records called blocks.
Digitising the documentation process will help save money, paper and human resources globally. Digitisation in the maritime sector has faced some hindrances on account of security and possible threat concerns. Our solution addresses those issues and reduces worries and vulnerabilities.
We developed the Rexs.io framework to help ensure the security of document flow and accelerate digitisation. It can be integrated into the existing IT infrastructures, which makes it easily adaptable across various industries, as it doesn’t require a complete tech stack overhaul. It registers the creation of a specific data stream to ensure that it wasn’t manipulated or altered by suspicious activity or a malicious actor.
Rexs.io has two key components: the Secretary and the Notary. The secretary is a proxy agent designed to emulate the target’s endpoint. The secretary uses the same API and technology as the original target, allowing to seamlessly plug into an existing data pipeline on the data consumer’s side. This proxy calculates the hash of the proxied data and seamlessly transfers the unmodified data to the original target endpoint.
The generated hash of the product is, at the same time, then transferred to a queue, where the notary component later handles it. The latter communicates directly with the blockchain infrastructure. It gets the information from the secretary containing the file hash and handles storing it on the blockchain.
Suppose the original data piece is later manipulated. In that case, its hash – or a digital fingerprint – will inevitably change, resulting in a new hash for this data, unknown to the blockchain, proving that it has been modified and is different from the original.
Since blockchain is a tamperproof solution, once the original fingerprint is stored, it can’t be deleted or modified afterwards.
Significant reduction of unnecessary costs
Blockchain adoption rate is closely related to its understanding by the end-uses
It is essential to lower the entry barrier for non-blockchain savvy end-users and organisations
To boost adoption, applications should be capable of seamless integration with the existing IT infrastructure
It is essential to raise awareness among maritime companies and stakeholders that it is possible to reap benefits from blockchain solutions such as Rexs.io without having the advanced technical know-how of blockchain/DLT
Client.
Thales
Problem.
Thales products comprise many components that the company buys from a large variety of partners. The goal was to develop a platform that stores all documentation of components, suppliers of individual components and replacements. The company was looking for a partner that has experience in the development of enterprise architecture. There were 3 main goals for the project implementation:
Solution.
The general concept of the DPF is the following: for every business process that handles product-related data, the DPF offers an access point (interface) for a human in charge of this business process. The product-centric DPF interface enables that human user to accomplish the necessary data-handling tasks if needed, reaching across the private data structures of different companies that are part of the supply network for that product. DPF provides a separate user interface for every processes or sub-process, which allows for a separation of concerns and provides a security measure. DPF architecture distinguishes between two types of companies in the supply network for a product: the OEM company, which is the company that owns the product that is the central object of the supply network, and the Manufacturer(s) companies that are the suppliers of parts for that product.
The first phase consisted of collecting the requirements, which was the responsibility of the Thales team. For this purpose, we talked with product-owners, procurement, SCM, and change management. The set of requirements was then discussed with the DAC to make the functional requirements.
The next stage is the analysis of available technologies, research and the first proof of concepts. Architecture development and selection of technological stack.
In the next stage, the time came for the development and testing of a developed solution. DAC developed an architecture to integrate cloud solutions, in which PLM partner systems were embedded. One of the assumptions was to use Arrowhead Framework, currently curated by Eclipse Foundation, Industrial IoT automation, and interoperability framework.
We are currently developing a Whitepaper in collaboration with DAC scientists and engineers to promote this innovative approach. The Whitepaper should be available in late 2019 and early 2020. We will present the solution at industry 4.0 conferences and trade fairs.
The main goal has been achieved: a working prototype that demonstrates the performance of Product Lifecycle Management. The development of a functional demonstrator was crucial for the further development of the project.
The DPF in Budapest at the Productive 4.0 conference related to Industry 4.0, digital production, etc., where the domain experts had the opportunity to review and give feedback on our tool.
A data-space-enabled collaborative product life cycle and supply chain management. Developed in cooperation with Thales, Digital Product Footprint integrates distributed PLM systems, operated by different parties in a multi-stakeholder ecosystem, to furnish visibility of product and component dependencies across the value chain. By encompassing all data items relevant for managing all aspects of a product, DPF supports the bidding process, product configuration, and change management.
DigiTrac is a system built on the concept of Digital Product Footprint (DPF) developed by the engineers at DAC.digital in collaboration with THALES, Netherlands. It is based on three core viewpoints: a product-centric, a business process-centric, and an end user-centric approach to product management, i.e., it considers business processes and the people in charge of them to be the essential parts of product management.
The DPF may be seen and explored using the system. It provides a graph description of all the pieces used to build an item (for example, a car) together with all the information such as the original manufacturer, manufacturing date, maintenance, repair history, and so on. It is already being used in the transportation industry.
DigiTrac is a functioning prototype that exhibits the effectiveness of Product Lifecycle Management and can be customised for use in various industries. DigiTrac was showcased at the Productive 4.0 Industry 4.0 conference, receiving an excellent response.
The concept of a Digital Product Footprint is the result of a problem-solving process in which the management of a product, as a primary business process for a product owner (who is not a customer/owner), is revisited because existing solutions in terms of process descriptions and underlying tools and methods have eroded and become less performant because of the following trends: Digital Transformation, Smart Industry, Smart Industry++, Realisation of Industrial Internet of Things.
As a result of adopting the view that the creation and use of a man-made product must be trackable and traceable, in all required detail, via data in the digital domain (or the virtual world of digital data, or however you want to describe it), we face the challenge of defining and implementing an all-inclusive set of digital data items that together and in part describe all aspects of a product over its entire lifecycle (i.e. from its conception to its decommissioning and destruction).
Thales products are made up of several components that the firm obtains from a wide range of suppliers. The purpose was to create a platform that keeps all component documentation, providers of individual components, and replacements. The organisation searched for a partner with experience in enterprise architecture development; this is where DAC.digital came in to expand the state-of-the-art.
Thales products comprise many components that the company buys from a large variety of partners. The goal was to develop a platform that stores all documentation of components, suppliers of individual components and replacements. The company was looking for a partner that has experience in the development of enterprise architecture. There were 3 main goals for the project implementation:
R&D, which was supposed to help in the choice of technology
Proof of concept activities
Development of Product Lifecycle Management
The DPF’s main principle is as follows: for any business process that handles product-related data, the DPF provides an access point (interface) for a human in charge of that business process. The product-centric DPF interface lets that human user do the essential data-handling operations, reaching across the proprietary data structures of multiple organisations that are part of the product’s supply network. DPF offers a different user interface for each process or sub-process, allowing for concern separation and security.
DigiTrac, facilitated by Data Space, enables a collaborative product life cycle and supply chain management. It connects distributed PLM systems run by many parties in a multi-stakeholder ecosystem to provide visibility of product and component interdependence across the value chain. DPF helps the bidding process, product configuration, and change management by incorporating all data items necessary to control all elements of a product.
DigiTrac provides access to an anonymised representation of an existing complex product involving a multi-stakeholder supply network and spanning as many lifecycle phases as possible, supplemented with other data items to cover another business process involved in DPF management, namely the Logistics process. As a result, the DPF will enable access to a wide range of data items, including design data (software, hardware, and mechanical parts), manufacturing data, supplier data, supply and logistics process and network data, and data on the product’s operating performance, maintenance, and support. This product’s change processes will comprise a variety of small and significant effect events, such as a mid-life update, ownership change, export limitations, obsolescence management, and supply network changes.
About the client
Problem overview
Swiftly, a Stockholm-based startup, grappled with two significant challenges within their job portal. Firstly, accurate categorization of job listings posed difficulties, leading to suboptimal user experiences and ineffective job matching. Secondly, the manual job application process was time-consuming and resource-intensive, restricting scalability.
Proposed solution
Our approach comprised two pivotal components:
Collaborative discussions between Swiftly’s leadership and DAC.digital’s technical team laid the groundwork for a productive partnership, aligning expectations and goals.
An 8-person team, comprising ML Engineers, Embedded Systems Engineers, Data Scientists, and Fullstack Developers, came together to tackle the project.
Daily stand-up meetings and ongoing communication facilitated iterative development and enhancements.
The project concluded with the creation of an advanced SOTA solution that effectively addressed Swiftly’s challenges. This solution improved job listing categorization precision and streamlined the application process. The SOTA also offered a proof-of-concept for refining job listing keywords and automating application field population.
Results
Swiftly’s collaboration with DAC.digital resulted in the successful resolution of their job portal challenges through the implementation of innovative automation solutions. The web scraping tool and the SOTA presentation highlighted the potential of technology to enhance processes, elevate user experiences, and pave the way for future enhancements.
Key numbers
Our Client
Challenge
The client noticed that the dairy industry was heavily reliant on traditional practices, leading to inefficiencies. Recognizing the opportunity for improvement, the client aimed to create a digital system that could streamline milk delivery management and procurement processes.
Solution
DAC.digital’s team collaborated closely with the client to create a comprehensive end-to-end product. We decided together on the features and improved the concept collaboratively.
The team comprised a Product Owner, 3 backend developers, 2 frontend developers, a UI/UX designer, and 1 tester. As the project required, the team size was adjusted accordingly, growing when new functionalities were needed and scaling down during lower business demand.
To accommodate the complex and evolving nature of the system, we opted to work in a Time and Materials model. This approach provided the necessary flexibility and responsiveness to adapt to the project’s changing needs over time.
As we continued to enhance the system, the client recognized the need to optimize the milk delivery process further. To achieve this, our team introduced automatic route planning algorithms, which revolutionized how routes were planned for the drivers. Instead of relying on manual decision-making, the system could generate the most efficient routes based on various factors like delivery locations, vehicle capacity, and traffic conditions. This saved time, reduced fuel consumption, and improved overall operational efficiency.
Additionally, we sought to digitize and simplify the process of documenting milk quantities at each farm. To accomplish this, we developed electronic devices called MuuBox. These devices were installed in milk tankers and are responsible for uploading data in real time to the MuuMap system.
Previously, the milk collection process involved a lot of manual work for the drivers. They either had to use handwritten protocols to record the quantity of milk collected at each farm or print bulk receipts from their route, which had to be manually entered into the computer. This manual data entry was a time-consuming and labor-intensive task. For instance, entering 3000 positions manually required significant effort.
However, with the implementation of our solution, this manual process was digitized and streamlined. The collected pick ups data is now automatically aggregated in our system and allows integration with others. This automation significantly reduced the need for manual data entry, resulting in fewer errors than the previous approach.
By automating the data entry process, MuuBox significantly reduced the administrative burden on both drivers and the milk collection department. Instead of being the source of mistakes, the department can now focus on correcting errors.
For those MuuMap clients who preferred not to use the MuuBox devices, we introduced a manual entry functionality directly on their tablets. With this option, they could input the milk quantities manually. The advantage of this approach was that it eliminated the need for paperwork while ensuring accurate data recording. Just like with the MuuBox integration, the collected data from the manual entries were uploaded in real-time to the MuuMap system, streamlining the process and ensuring seamless data management.
Thanks to the application, the client became a pioneer in the market by offering a tool specifically designed for the traditional dairy industry. The unique and efficient solution attracted the first customers, who loved it and spread positive reviews. As a result, the client’s reputation grew, and more and more people started using the application. Eventually, it captured a significant portion of the Polish dairy market, securing a dominant position with a 30% market share.
Our client
Bouncing back from a plot twist
The first challenge appeared unexpectedly with the outbreak of Covid-19, forcing the company to pivot from their original idea of creating a smart anti-smog mask to something more practical for everyday use, as outdoor activities decreased significantly.
After returning to the previous concept, after easing the restrictions, the key challenge was creating a mobile application to connect with the mask and collect data from the air pollution measurement system Airly in a very short time-to-market window resulting from the first pivot.
Fast-track solution
The team’s tasks needed a speedy process and included:
The three Urban’er founders had an innovative idea to create a smart sports face mask for active urbanites. They wanted to adapt Bluetooth connectivity with a dedicated mobile app to display the duration of the activity, the equivalent of unsmoked cigarettes in air filtered by the mask.
The goal was to help those who live in urban areas with uneven air pollution landscapes to have an opportunity for comfortable and safer physical activities wherever they are. However, an unexpected twist of fate made them pivot from the original idea.
A sudden outbreak of Covid-19 in 2020 significantly limited the possibilities of outdoor activities in Poland. Thus, the company has decided to move from creating a smart sports mask to making a regular face mask with an exchangeable filter to filter out the PM 2.5 and PM 10 harmful air particles for protection during everyday activities. They wanted to focus on a modern design appealing to the public, comfort and functionality.
However, once the restrictions had been lifted, the demand for everyday protection masks dropped, allowing our client to return to their original plan. The mask used two HEPA filter layers with an FFP2 filtering standard, considered one of the most effective, that could filter out up to 95,8% of harmful particles. Moreover, they used locally-sourced materials for the design and production.
The time and budget were scarce, so the time-to-market window was narrow. They needed a team of experts to create a solution quickly and effectively.
Our team of experts comprised a full-stack developer and an assisting frontend developer. They were responsible for the app development and integration with the Airly system. Airly is crowd-sourced air pollution measuring system, and collecting data from the sensor allows insight into the current pollution level in the immediate area of the closest sensor.
Integrating the platform into the application gave the user real-time access to information on the air quality in their vicinity. The team worked on the complete solution within their short window.
The team worked independently, collaborating with the UX/UI expert on the client’s side. It allowed the creation of a coherent and stable product we then supported during the launch in the respective app stores.
Adopting React Native allowed for creating a modular and intuitive environment that can be easily modified. The app offered stable performance within the mobile operating systems. It also offered high code reusability across the platforms.
Using Firebase BaaS helped to speed up the development and streamline the tasks to the frontend to ensure the fast time-to-market product release.
Integrating with Airly allowed for data collection on air pollution and displaying live updates within the app.
Providing ongoing post-launch support to ensure that all the post-launch polishes were applied as necessary.
The application was developed on time and worked precisely as intended. It also received a maximum rating in the Apple App Store. It measured the activity, average breath and the avoided pollution. It also displayed the mask battery and filter levels to indicate the necessity for charging or a replacement.
Line of business
E-commerce.
Challenge
In e-commerce, companies acknowledge the need to enhance communication between the company and its clients to improve response speed.
Solution
DAC.digital implemented a proof of concept (PoC) for an AI chatbot on its website. The primary objective was to assess how the chatbot could enhance communication, improve response times, and effectively handle customer queries and concerns.
The companies face challenges in effectively addressing customer queries, concerns, and feedback in a timely manner. Many users ask the same questions repeatedly, resulting in a need for a solution to handle such repetitive inquiries.
Implementing a chatbot was seen as a way to address these issues effectively. Currently, numerous employees are dedicated to answering live chat questions. Automating this process through a chatbot would reduce the need for human intervention and free up employees for more strategic tasks.
Moreover, training employees to handle the extensive information required for live chat responses is time-consuming. On the other hand, training a chatbot is much faster and more efficient, allowing for quicker implementation.
Due to the implemented chatbot, companies can work towards achieving complete automation of their customer support process. By utilizing a chatbot, they can streamline communication, reduce reliance on human resources, and provide rapid and accurate responses to customer inquiries.
Our team was composed of a diverse set of experts, including two UX/UI specialists, one front-end developer, one DevOps specialist, and four specialists in Natural Language Processing and backend development.
In the project, we employed a range of technologies for different aspects:
For design, we used Figma. React was utilized for frontend development. The backend consisted of Firebase as well as Python 3 with LangChain. FastAPI was implemented to handle requests efficiently. For service management, we employed Kubernetes.
We have started with research on the feasibility of using various LLMs as a backbone of our chatbot, and ultimately chose OpenAI to power our chatbot.
We carefully designed the chatbot, ensuring it aligned perfectly with our brandbook. Once the design was complete, we developed the backend. In just two weeks, we performed the integration with the frontend successfully.
Having a successful chatbot heavily depended on the data it received, as wrong context could lead to poor performance. So, we carefully curated the ideal dataset for fine-tuning to ensure its optimal functionality.
After successful deployment, we collected internal feedback to evaluate the chatbot’s performance in handling both simple and complex questions, and also run a set of automated tests to evaluate its performance.
Chatbots are a great solution that go beyond e-commerce, demonstrating their efficacy in a variety of industries like banking and healthcare. Users frequently grow impatient while waiting for simple question answers, and they eagerly look forward to prompt responses.
Chatbots in the banking industry provide a helpful solution to this frequent problem. Customers can get prompt answers to their questions by utilizing chatbot technology, which will reduce their dissatisfaction and improve their overall experience.
By giving doctors helpful support, chatbots can also have a big impact in the field of medicine. These intelligent systems can talk to patients, learn about their symptoms, and then transmit the information instantly to doctors.
Customer
Challenge
The client’s goal was to provide the generated data to developers in an open format. The openness of the data allows for the creation of various applications according to the expectations of each demanding user. Thanks to this, public transport passengers organized by ZTM in Gdansk could check the timetable in multiple ways, along with information about any delays of individual ZTM vehicles in Gdansk.
Solution
In 2016, we participated in a tender to create the “Open Data System of ZTM in Gdańsk” and were selected by ZTM in Gdańsk. Our domain knowledge and experience in backend architecture were crucial for the client.
Four specialists from DAC.digital worked on the project: the Chief Solution Architect, the Architect/DevOps Engineer, and two Senior Mobile Developers who provided the necessary expertise and experience in delivering the project. We worked as an independent team in close cooperation with the customer.
To make the information we wanted to share consumable by planners such as Google Maps, Jakdojade, BusLive or Time4BUS we had to prepare it properly. We worked on the data structure related to the timetable, which proved to be quite complicated due to its distribution across various databases and microservices.
We also had to consider the limited resources of the source system. We had to strike a balance between data collection speed and the load on the databases, which are simultaneously used by other ZTM Gdansk applications.
Sharing rapidly changing data (e.g., departure estimates from stops or vehicle positions) required a different approach due to CKAN system limitations. We needed to be able to update the data frequently enough to meet the quality requirements. We shared this data directly from our servers, and CKAN remained the place for its documentation.
We continue to work on open data for ZTM in Gdańsk, ensuring their timeliness and carefully controlling the downloading of data from the TRISTAR system.
In 2022, we handled 406,639,355 requests for open data in Gdańsk.
On the other hand, queries for static data (updated once a day) occur hundreds of thousands of times a month.
In the case of the map, which was made public less than two years ago, we recorded 3,827,046 visits. The promotional campaign and regularly introduced improvements contribute to the increasing interest in the product, as evidenced by the growing number of visits.
Customer
Challenge
As a result of acquiring several ecommerce companies, TB Auctions needed to integrate all systems into a unified platform, while also incorporating new functionalities to enhance the overall user experience.
Solution
To produce high-quality code and satisfy the customer’s requirements, we put together a team of Kotlin experts who were solely focused on working on this project.
The client contacted us through a referral from our trusted partner – Angry Nerds. At the outset, TB Auctions chose to assign us a smaller project in order to assess and confirm our technical expertise.
We’ve started with one person (Senior Fullstack Developer) working on the project on our side, whose remarkable technical skills were highly appreciated by the customer. That’s why the client requested adding 25 extra individuals, comprising mostly regular, mid and senior Kotlin specialists, a team of juniors and frontend experts (Angular and REACT), as well as DevOps, .NET and QA automation specialists. Our team worked as part of the customer’s larger team.
To ensure optimal efficiency, we formed multiple teams, each with a maximum of six members as the bigger groups made cooperation challenging. Our team shared innovative ideas with the customer and recommended strategic modifications to optimize their operations.
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Software development is essential to building technological innovations and driving the business to success. Finding the right talent to meet the project’s needs can be challenging.
84% of companies had trouble recruiting talent due to labor shortages. (Source: www.shrm.org)
Find out how to decrease the difficulty of building a dedicated team by applying the Time and Material method.
Client
Challenge
After a successful collaboration on the Spark surveying platform, the client came back to us with a new project for deepening the research with a more hands-on experience, adopting gaze estimation to track the user’s attention while browsing content on their smartphones. The key issue is that such an approach is still highly innovative and uncharted territory.
Solution
Our initial communication involved the company’s COO, Phillip Reiter, technical project managers – Garrit Güldenpfennig, Frederic Neitzel and Olaf Briese, and the CFO, Friedrich Jakobi. They outlined their expectations and needs for the project.
The company previously used several third-party solutions for laptop-related use cases, some of them required external HW. The main goal this time was to create a new solution that would be suitable for mobile phones. The initial agreements took approximately two weeks, after which the team started working on the Proof of Concept to ensure the visions were aligned before starting the subsequent phases of such a complex R&D project.
Our team comprises a Senior Computer Vision Engineer, Machine Learning Engineers, DevOps specialists, frontend developers and a project manager.
eye square supported us with three technical Project Managers (one of whom has become a project coordinator), the CFO and a developer to provide extra help. Moreover, an essential part of their contribution was coordinating the crowd-sourcing platform to acquire testers and data sets. The technical project managers Garrit, Frederic and Olaf also provided their expertise and help whenever needed.
To create a solution that exceeds the state-of-the-art technology, we had to use the available resources to the maximum. The crucial part of the process was to create a stable foundation that would allow the creation and development of new features that would bring it closer to the final project and what it should look like.
Due to its complexity and innovation, the project must be divided into multiple stages and requires extensive research, including the “trial and error” approach. The biggest challenges involve the dynamic environment, as we wanted to create a solution that would work “in the wild”, without the need for any specific HW and with minimum prerequisites from the user.
This raised several obstacles, including the complexity of calibrating the phone camera. Phone screens & cameras differ from model to model. Therefore, it’s hard to find a generic estimation method, especially since phone manufacturers don’t disclose the physical dimension of devices.
Since the user needs to have complete freedom to use their phone, there’s the challenge of making sure that the gaze estimation algorithm can be auto-calibrated in different models of smartphones. It is a difficult task given different angles, distances, and face detection capabilities. Our neural networks are trained on different faces and angles to get a result similar to regular use.
Due to the vast crowd-sourced data from the ClickWorker platform, the team needs to evaluate the data quality. An automatic framework was developed to filter out recordings that don’t satisfy basic quality metrics, like proper lighting, lack of blurring, etc.
Even though the innovation threshold is set high for that project, the results are satisfying on both sides. The initial aim was to prepare the Proof of Concept. However, our partner keeps extending our work, as the results are good and the prospects promising.
We are gathering and processing more training data to improve the algorithm’s accuracy. We already exceeded the technological state-of-the-art and are continuing to work on achieving better accuracy and taking the next steps towards creating a working product.
Several elements of the processing pipeline developed by DAC.digital are currently considered for patent submission.
Who’s our partner?
What did they need?
“We wanted to develop further our internal product called Spark. Spark Platform allows users to automate marketing surveys. It is the most powerful, implicit user testing platform we run, and we wanted it to be intuitive and self-serviced by the users.”
Michael Schießl, CEO and co-founder
What was our proposition?
eye square looked for a partner with the highest competencies and capability of connecting technologies to make a complete and reliable solution. After the initial meetings with the UX designer, we conducted workshop sessions with the client to consult the vision and address necessary questions and issues.
Initially, we met with Matthias Rothensee – the Product Owner. However, our collaboration also involved eye square’s COO, Philipp Reiter. We discussed the specific needs and requirements to get the final blessing from the company’s CEO – Michael Schießl.
After two weeks after the initial meeting, we had a good idea of what needed to be done. An intense working session gave us room to create necessary mockups and a working MVP. The work was divided into sprints, during which we received regular feedback on what was good and what needed improvement.
The team included a business coordinator to manage all the necessary documentation and agreement details (contract, NDAs and such), a technical project manager and a scrum master to translate the eye square’s needs into the backlog used by the UX/UI and development and QA team.
Additional touchpoints included a UX and UI expert and a cross-functional development team covering the DevOps part, backend and frontend, including testing. On eye square’s end, they had a product owner who helped with necessary coordination tasks.
We had:
The project had three iterations, after which the client could use the quarterly time for any extra work:
We could design the entire platform as requested, and the client was delighted with the results. We have designed the entire platform and were able to add extra features on top of what we already agreed on. It included adding a role management system that allowed granting the correct level of access based on the user’s role.
eye square was satisfied with the results and impressed with how much we could deliver in the fixed time, scope and budget. They were also happy with the professionalism and good communication the team displayed along the way. All this resulted in them requesting another collaboration on their new project.
The Spark platform was successful, and its current state is fully developed and usable. The company has some working hours from our team every quarter that they can use for necessary maintenance and extra work.
The platform has a varied user base, including big and small companies from different business sectors like banking, insurance or consumer goods.
To this day, eye square representatives consider the platform a huge success and are eager to show it off at public events.
To know more about our partner’s endeavours, see the Memex Poland 2022 presentation on AI and art at Memex Poland 2022.
Customer.
Prod eng and UI/UX design
Blockchain
Web3 wallet integration
Due to a short timeframe, we’ve immediately established an efficient a quick communication channel with the client.
The client has received the pricing estimation one week after the first conversation,
Our team has started with UX/UI based on the results of the workshop with the designer and the client.
We’ve introduced daily alignments with the client over Slack.
Our team worked in two weeks sprints.
We’ve run a dynamic multistage development and implementation to meet the deadline; the product went live as soon as possible and subsequent iterations were built atop of the MVP.
Customer
Data management
Software integration
IoT
The simple provision of chargers to tenants and billing of energy consumed in the administration system.
Optimal use of available power in the building.
Protection against network overload in an office building or parking lot.
Here we have used PostgreSQL algorithms (ltree) for representing labels of data stored in a hierarchical tree-like structure.
We have employed a PostGIS, a spatial database extender for PostgreSQL object-relational database. It supports geographic objects allowing location queries to be run in SQL.
We have deployed an open-source message broker, RabbitMQ, which can be deployed in distributed and federated configurations to meet high-scale, high-availability requirements.
The goal was to provide remote access to the status of the charger but also to allow users and end-users to control the charger, e.g., switch it on/off remotely. Both groups are using different apps to perform these activities. Our team accessed the chargers software backend and conducted the integration from that level.
DAC.digital software development team has been working together with the client’s team. The work has been aligned with the scrum methodology.
The system allows dividing the network into smaller operators, who will only have access to their devices. Charging Service Providers can check the status of the charging station. Thanks to the connection with the Enelink system, most of the maintenance activities will be performed remotely. Another feature was setting up a charging plan that will limit the station’s power at the right time if the Service provider chooses several Operators. All charging stations can be labeled. This makes it easier for Service Provider to manage the stations from a given label. Then, information about the stations’ availability can be easily shared with end-users in a few clicks.
Dynamic Tariff solution gives an attractive offer for each end-user, encourages them to charge in specific places, and introduces discount coupons and VIP programs. Entering tariffs helps Service Providers optimize earnings at charging stations.
