Enterprise Data Science and ML Solutions

BRONZE VERIFIED

Data tells a story. Appsilon helps some of the world's largest companies understand and interact with this story. We create powerful tools and end-to-end enterprise data solutions, from data acquisition to computer vision to responsive Shiny dashboards. Some of the many industries we work with include Finance, Healthcare, Logistics, Retail and Real Estate.

We are a proud RStudio Full Service Certified Partner. Appsilon delivers the world’s most advanced R Shiny apps, and we have the expertise to scale these apps up to hundreds of concurrent users. We provide data science consulting, managed services, and custom solutions with R Shiny and Python Dash technologies. We have a wealth of experience with machine learning in image recognition and predictive analytics. If you have a difficult data problem that requires strong analytical skills, or you think that your data is being underutilized, then you’ve found the right people.

Appsilon’s passion for data extends to open source. Our packages have been downloaded thousands of times by both commercial and open source developers. We inspire discussion and we love to teach others as much as we love to learn from others.

 
$10,000+
 
$100 - $149 / hr
 
10 - 49
 Founded
2013
Show all +
Warsaw, Poland
headquarters

Portfolio

Key clients: 
BCG, Index Ventures, Diversey, Canadian Forest Service, Triple A Risk Finance, Black Red White, and Fortune 500 Companies across the globe
R Shiny Port Analytics Application Image

R Shiny Port Analytics Application

We created an attractive and user-friendly decision support system based on R Shiny that uses Automatic Identification System (AIS). 

AIS is a real time system reporting position, speed, direction and other properties of vessels worldwide.

ML Image Classification to Analyze Wildlife Camera Trap Datasets

We worked with biodiversity conservationists at the National Parks Agency in Gabon in collaboration with experts from the University of Stirling to build an ML model that automatically identifies wildlife from camera trap images. We completed a fully functional Computer Vision ML model in two weeks. Our model was able to identify animals in images that human auditors frequently

missed. Our model can quickly and accurately process millions of camera trap images, saving thousands of human work hours. We received additional support for this project from the Google for Education fund.

Learn more about the project here.
  • ML Model to Identify Wildlife 
  • Significantly More Accurate Than Human Auditors
  • Part of our AI For Good Initiative
AI for Assisting Natural Disaster Recovery Image

AI for Assisting Natural Disaster Recovery

The Appsilon Data Science Machine Learning team recently took part in the xView2 competition organized by the Defense Innovation Unit (United States Department of Defense). Participants set out to utilize satellite imagery data to assist humanitarian efforts during natural disasters.

We were asked to build ML models using the novel xBD dataset provided by the organizers to

estimate damage to infrastructure with the goal of reducing the amount of human labour and time required to plan an appropriate response.

Read more about the project here.

Interact with a demo of the final app here.

R Shiny Natural Language Processing App Image

R Shiny Natural Language Processing App

We collaborated with the London School of Economics to create an intuitive R Shiny application that allows scientists and linguists to perform Natural Language Processing without the need for programming skills. The application is based on the R package Quanteda.

The app is commercially available to use here.

Computer Vision Defect Detection Image

Computer Vision Defect Detection

We were approached by a major manufacturer to build a Machine Learning model for automatically detecting defects in cast iron products. We were able to train a working model and package it within an app for using the model as a prototype within two working days.

We used fast.ai on PyTorch (kaggle and GCP) for training the model. The app was built in

Starlette.
  • 99.6% Test Accuracy for Identifying Defects
  • Two Days From Concept to Working Prototype
  • Reliable Solution for Quality Control

Reviews

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AI-Driven Software Dev for Ecological Scientist

"[They're able to] understand project needs and to develop innovative solutions that we had not previously envisioned."

Quality: 
5.0
Schedule: 
5.0
Cost: 
5.0
Willing to refer: 
5.0
The Project
 
$10,000 to $49,999
 
Jan. - June 2020
Project summary: 

Appsilon Data Science constructed high-accuracy machine learning models for an ecological scientist. They built an AI-driven platform to identify species in images, automating the client's data collection.

The Reviewer
 
1,001-5,000 Employees
 
Stirling, United Kingdom
Robin Whytock
Post Doctoral Research Fellow, University of Stirling
 
Verified
The Review
Feedback summary: 

Appsilon Data Science's solutions have succeeded in rapidly reducing the time between data collection and analysis. Their engineers documented all of their code on GitHub and tracked their progress meticulously. The team exhibited their exceptional ability to understand the client's unique needs.

The client submitted this review online.

BACKGROUND

Please describe your company and your position there.

I am a scientist working in Central Africa with the National Parks Agency of Gabon and University of Stirling, UK to understand how ecosystem change impacts on biodiversity. My research combines the latest hardware and software technologies to collect data on species' populations and their distribution in tropical forests.

OPPORTUNITY / CHALLENGE

For what projects/services did your company hire Appsilon Data Science?

I contacted Appsilon Data Science through their AI for Good Initiative to seek assistance with developing user-friendly, offline software tools to run machine learning models that identify species in 'camera-trap' images.

Our projects often collect millions of images of animals across remote landscapes to inform conservation and biodiversity policy but the datasets can take months or years to label manually, which causes a significant delay between detecting potential threats such as hunting pressure and subsequent conservation action.

What were your goals for this project?

We needed high-accuracy machine learning models that could be run offline using very simple, easily-installed software. It was also essential that we could add multi-language functionality.

SOLUTION

How did you select this vendor?

Appsilon Data Science regularly publish impressive blog posts and example code via LinkedIn and their website. I was using some of their R code to assist with my own R Shiny projects when I came across their AI for Good Initiative.

Describe the project and the services they provided in detail.

My inquiry to the AI for Good Initiative received a rapid and positive response from the project's lead (Tadeusz Bara-Slupski). Tadeusz worked with me to develop and design an MVP, and communicated all details of our project's needs to the Appsilon Directors, software engineers and data science teams.

Appsilon then allocated a dedicated team of engineers led by Marek Rogala and we used an iterative approach to refine the project's goals and expected deliverables. We also co-wrote a successful Google Cloud Education Grant to fund the computing resources required to train machine learning models.

Appsilon ran a week-long hackathon to initiate development of a MVP and I worked with data scientist Jedrzej Swiezewski to supply training data for the machine learning model, and to validate their output.

What was the team composition?

We had a dedicated lead for the full term of the project and I had direct contact with two senior data scientists/software engineers. At least five other members of Appsilon worked on the project in the background and we had at least two large group discussions during the early stages of development.

RESULTS & FEEDBACK

Can you share any information that demonstrates the impact that this project has had on your business?

The machine learning models are already rapidly reducing the time between data collection and analysis, for example we were recently able to extract over 1200 images of wild gorillas and chimpanzees from our database of over 50000 images and assess the prevalence and environmental drivers of a zoonotic disease in the population.

The MVP will be fully deployed in 2021 to become integrated into the standard biodiversity monitoring protocols used by the National Parks Agency of Gabon.

How was project management arranged and how effective was it?

We had a dedicated contact throughout the entire process who managed deadlines and tracked progress towards the project's goals. We received regular updates by email and regularly held discussions using Google meets. All code was documented on Github.

What did you find most impressive about this company?

I was extremely impressed by their ability to rapidly understand our project's needs and to develop innovative solutions that we had not previously envisioned. We have previously found it challenging to clearly communicate our objectives from an ecological perspective to pure data scientists, but this was not a problem at Appsilon.

Are there any areas for improvement?

This was my first experience working with an industry partner to develop software and machine learning products and I have been extremely impressed throughout the process.

5.0
Overall Score
  • 5.0 Scheduling
    ON TIME / DEADLINES
    All meetings and deadlines were met on time.
  • 5.0 Cost
    Value / within estimates
    This work was offered on a pro-bono basis but we have been developing funding bids for future work, and Appsilon's costs are very competitive.
  • 5.0 Quality
    Service & deliverables
    It exceeded my expectations using innovative solutions to solve our project's challenges.
  • 5.0 NPS
    Willing to refer

Custom Software Dev for Belgian University

"The collaboration felt natural and we had great confidence in the technical proficiency of the Appsilon team."

Quality: 
5.0
Schedule: 
4.5
Cost: 
5.0
Willing to refer: 
5.0
The Project
 
$10,000 to $49,999
 
Feb. - June 2020
Project summary: 

Appsilon Data Science was responsible for creating a cloud-based dashboard to be integrated with pre-existing internal software. They delivered wireframes and mockups for approval before launching into sprints.

The Reviewer
 
10,000+ Employees
 
Ghent, Belgium
Ruben Props
Postdoctoral Scientist, Ghent University
 
Verified
The Review
Feedback summary: 

While the project is still underway, Appsilon Data Science has made great progress with the project. They managed the project effectively by leveraging various tools. Their young, vibrant company culture rendered them an easy partner to work with. They've also boasted an impressive turnaround.

The client submitted this review online.

BACKGROUND

Please describe your company and your position there.

I am a postdoctoral scientist at Ghent University working on the valorisation of microbial management technologies. Ghent University is a top 100 university and one of the major universities in Belgium. Our 11 faculties offer more than 200 courses and conduct in-depth research within a wide range of scientific domains. Ghent University Global Campus is also the first European university in Songdo, South Korea.

OPPORTUNITY / CHALLENGE

For what projects/services did your company hire Appsilon Data Science?

We were in need of a cloud-based dashboard that could be integrated seamlessly with our custom software. We had no prior industry-grade experience with building such an application from scratch and needed expert support in building this application.

What were your goals for this project?

The application had to be compatible with our existing software architecture but at the same time be flexible enough for future developments/iterations. The primary goal was to reach a minimum viable product (MVP) on which we could further iterate either internally or in future development projects with Appsilon.

SOLUTION

How did you select this vendor?

We contacted several vendors but the decision for Appsilon was made based on cost-efficiency, expertise in Shiny prototyping, and the time needed to initiate the project.

Describe the project and the services they provided in detail.

The project started with a workshop held at Appsilon HQ during which we came to a mutual understanding of the scope, deliverables and milestones of the project. We approved a wireframe & mock-up. The actual development started approximately one month later.

The development consisted of 4 sprints. Functional versions of the application could be tested during spring 3 - 4. Improvements were made during each sprint at our weekly development meeting.

What was the team composition?

The project team consisted of two full-time developers (one full stack developer) and one graphical designer. Depending on the necessary skills additional developers were included during the sprints. There was some turnover of developers during the development (i.e. one fixed developer and several floating developers).

RESULTS & FEEDBACK

Can you share any information that demonstrates the impact that this project has had on your business?

Not yet.

How was project management arranged and how effective was it?

Project management was effective and direct through Slack communication. All milestones were reached on time and responsiveness of the Appsilon team to our feedback was fast and professional. Tools used for supervision/communication: Slack Github Google hangouts

What did you find most impressive about this company?

The culture as a vibrant young, flexible and creative company made it easy for us to work with them. The collaboration felt natural and we had great confidence in the technical proficiency of the Appsilon team to deliver on this project. In addition, the way they are able to operate internationally from different remote working locations is also impressive.

Are there any areas for improvement?

During our project there was some staff turnover that caused some confusion on our end and the testing of the application could be incorporated earlier in the sprints such that we could provide more feedback. The planning of the sprints did also change quite a lot during development which sometimes caused a mismatch with our timing for feedback. Overall however, given the speed at which this application was built, these are not significant issues.

5.0
Overall Score
  • 4.5 Scheduling
    ON TIME / DEADLINES
  • 5.0 Cost
    Value / within estimates
  • 5.0 Quality
    Service & deliverables
  • 5.0 NPS
    Willing to refer

RX Hours and Data

"They are a good team and their project management is outstanding."

Quality: 
5.0
Schedule: 
5.0
Cost: 
5.0
Willing to refer: 
5.0
The Project
 
$10,000 to $49,999
 
Apr. - July 2020
Project summary: 

Appsilon Data Science worked in sprints to refine an existing application to address key pain points and add flexibility for users. This included adding several new data widgets. 

The Reviewer
 
1-10 Employees
 
Denver, Colorado
Steven Seman
Project Manager, ResourceX
 
Verified
The Review
Feedback summary: 

As a result of Appsilon Data Science's work, the client has been able to increase the scale and value of the data their systems generate. The team at Appsilon was productive, professional, and engaged. 

The client submitted this review online.

BACKGROUND

Please describe your company and your position there.

Project Manager who supports client implementations and is working on our new software application.

OPPORTUNITY / CHALLENGE

For what projects/services did your company hire Appsilon Data Science?

We are looking to take some of our best practices and existing development and refine a new application that addresses key pain points and adds flexibility to engage new markers.

What were your goals for this project?

Develop the tools to setup clients for the app, add data entry widgets, and create a clear output that leads to shorter time to value for the customer.

SOLUTION

How did you select this vendor?

A representative from R Studio pointed us to their full service certified partners, https://rstudio.com/certified-partners/.

Describe the project and the services they provided in detail.

We worked in sprints of between 5-10 days, with pauses in between. The pauses were per our request, as this allowed our developer to absorb updates and new code with existing frameworks.

For a typical sprint, we discuss objectives and user stories throughout the work which helps us “sync” up on what we outlined in the beginning with the work as it unfolds. The customer response and service from Pedro and Maria has been excellent and we are able to meet ad hoc as needed to discuss changes or in response to development.

What was the team composition?

From our side, we had one developer and two project managers. On theirs they had 1 project manager, Maria, and 1-2 developers, typically Pedro.

RESULTS & FEEDBACK

Can you share any information that demonstrates the impact that this project has had on your business?

This project is a chance for us to increase scale and value in the data we generate while also reaching new markets. They have fueled new ideas and we are working toward a product we can show to customers. For our case, our interaction with Appsilon has allowed us engage in valuable “R&D” work to grow our company in the future. As is the nature of R&D we are still in the concept and proving phase.

How was project management arranged and how effective was it?

From our side, we gathered user stories for each sprint, provided context, and some direction toward the intended outputs and functionality. We revisited and course corrected when needed. Project Management by Appsilon has been very effective. Maria worked to ensure that objectives were reasonable, deliverables were tested, and documented.

They are a good team and their project management is outstanding. They never missed a meeting or deadline, and deliverables for success were always clearly communicated and agreed upon.

What did you find most impressive about this company?

They (Pedro and Maria) have been professional and productive, but most importantly, I have always felt like they are part of our team and have our customers in mind. This sense of a shared purpose and their willingness to contribute their ideas to our own to achieve the goal has been tremendously valuable.

Are there any areas for improvement?

We have not identified any at this time.

5.0
Overall Score I have always felt like they are part of our team and have our customers in mind
  • 5.0 Scheduling
    ON TIME / DEADLINES
    Despite a 6 hour time difference, we never had any issues with connecting
  • 5.0 Cost
    Value / within estimates
    the ability to engage with targeted sprints has given us flexibility to stretch our resources
  • 5.0 Quality
    Service & deliverables
    demonstrated to us key understanding of how the end user interacts with data visualizations
  • 5.0 NPS
    Willing to refer
    Maria and Pedro are a joy to work with, and I always look forward to our meetings

Web App Dev for Scientific Research Institute

"I always got an immediate response from Appsilon."

Quality: 
5.0
Schedule: 
5.0
Cost: 
5.0
Willing to refer: 
4.5
The Project
 
Less than $10,000
 
Apr. - May 2020
Project summary: 

Appsilon was hired to develop an interactive web platform to showcase changing COVID-19 stats in Europe. They team constructed a backend that allows administrators to update the maps with new information.

The Reviewer
 
201-500 Employees
 
Laxenburg, Austria
Asjad Naqvi, PhD
Research Scholar, Intl. Inst. for Applied Systems Analysis
 
Verified
The Review
Feedback summary: 

Appsilon delivered a module that affirmed the institute's informational leadership in the crisis. They managed to deploy the app in just a little over a week: an impressive turnaround. The team was accommodating of the client's requests and maintained excellent communication throughout the process.

The client submitted this review online.

BACKGROUND

Please describe your company and your position there.

The International Institute for Applied Systems Analysis (IIASA) is a scientific research institute located in Laxenburg, near Vienna, Austria. Founded in 1972, IIASA conducts policy-oriented research into problems of a global nature that are too large or too complex to be solved by a single country or academic discipline.

I am currently working at IIASA as a Research Scholar in the Advanced Systems Analysis program where I undertake research on environment-economy-finance interactions.

OPPORTUNITY / CHALLENGE

For what projects/services did your company hire Appsilon Data Science?

We hired Appsilon to develop a web application to showcase COVID-19 related socioeconomic, demographic, and heath indicators for regions within Europe. Since we don't have in-house capacity to develop such applications, we hired Appsilon to develop the web application. The website is currently available here: https://covid19.iiasa.ac.at/interactive

What were your goals for this project?

The primary goal of the project was to develop an interactive web platform to showcase various COVID-19 related indicators for regions within Europe. At the back-end, the aim of the application was to provide IIASA with a tool to regularly and independently update the maps as new data becomes available.

SOLUTION

How did you select this vendor?

A former colleague at IIASA had worked with Appsilon and highly recommended their services. After an initial online meeting, Appsilon showed a keen interest in the project. They also mentioned this project fits very well within their "AI for Good" initiative. Given the urgency of setting up the interactive website, Appsilon was also willing to put in additional hours at zero costs to have it up and running within a 7-10 day time frame.

Describe the project and the services they provided in detail.

Appsilon designed, developed, programmed the website application after several consultations with myself leading from IIASA.

Appsilon helped us configure the website on IIASA servers, deployed and optimized the website for fast previewing of maps, and gave us a backend to update the interactive maps regularly. The process of the website development was made transparent through a GitHub repository that is accessible by myself and the ICT team at IIASA.

What was the team composition?

The project was led by Damian Rodziewicz, one of the co-founders of Appsilon, who was personally interested in working on this web application. Damian was bringing people in as needed to optimize the deployment. During the various calls there were about 5-8 people present.

RESULTS & FEEDBACK

Can you share any information that demonstrates the impact that this project has had on your business?

IIASA has a huge outreach with a over 4000 alumini from around 100 countries. IIASA regularly interacts with policymakers, the scientific community, universities, think tanks, and scientific advisory boards through various activities. IIASA also has a very active social media presence.

The website was advertised extensively and is still promoted regularly on various social media platforms. The website has helped promote IIASA's work on COVID-19 related projects being done by various teams. Some projects will generate new indicators that will be showcased on the website as well.

How was project management arranged and how effective was it?

The project was fast-tracked including approving of Appsilon as the web developer, the budgets, and the deployment, all of which was completely in a 7 day time period with a couple of additional days for fine tuning the deployment.

An enabling factor in this was the personal interest of IIASA's directors and Appsilon's leadership. Additionally, almost regular one-on-one with Appsilon helped develop the website as a fast pace.

What did you find most impressive about this company?

Appsilon was very accommodating in our requests, especially in helping us deploy the website and giving us feedback on how to effectively process java and python scripts for deployment. I always got an immediate response from Appsilon and we usually ended up doing quick online chats to keep the process rolling.

Are there any areas for improvement?

It will be great if Appsilon can showcase the various projects they have developed on their own website. While we got previews of some projects during the presentations, just by being able to preview them online beforehand, helps tremendously with the decision-making process of selecting vendors.

5.0
Overall Score If we go for other web deployments, I would highly recommend Appsilon's service.
  • 5.0 Scheduling
    ON TIME / DEADLINES
    We were interacting almost on a daily basis.
  • 5.0 Cost
    Value / within estimates
    The costs were reasonable given the urgency of the project and the additional hours some of their team members put in to fast-track the deployment.
  • 5.0 Quality
    Service & deliverables
    Appsilon is very good at optimizing web deployments. They gave very good advice on which tools would work best for our application.
  • 4.5 NPS
    Willing to refer
    Highly likely but for mid- to large-scale projects given the size, scope, and expertise of the team.

Integrate Framework in Backend R for Data Science Platform

“They were highly organized throughout the entire process, and we were very impressed with that aspect of the work.”

Quality: 
5.0
Schedule: 
5.0
Cost: 
4.5
Willing to refer: 
5.0
The Project
 
$50,000 to $199,999
 
Nov. 2018 - Ongoing
Project summary: 

Appsilon Data Science worked from client-provided wireframes to build an integrated platform using JavaScript and an R server for the backend. They worked iteratively using agile scrum methodology.

The Reviewer
 
1-10 Employees
 
London, United Kingdom
Kenneth Benoit
Quanteda Initiative, Founder
 
Verified
The Review
Feedback summary: 

The final product and Appsilon Data Science’s technical work contributing to it are extremely high quality, satisfying all requirements for the project and exceeding stakeholder expectations. Their team is incredibly communicative, working hard to make sure everyone is always on the same page.

A Clutch analyst personally interviewed this client over the phone. Below is an edited transcript.

BACKGROUND

Introduce your business and what you do there.

I’m the founder and CEO of the Quanteda Initiative. We develop software and training for data science, specifically as it relates to text analysis and natural language processing.

OPPORTUNITY / CHALLENGE

What challenge were you trying to address with Appsilon Data Science?

Our software development involved a proof of concept where we had to demonstrate the feasibility of building a web application that’s built on a platform running R.

SOLUTION

What was the scope of their involvement?

Appsilon is a highly specialized company that deals with R in enterprise-level Shiny applications, which is a graphical framework that weds JavaScript with our backend R server. I wireframed the design of the web application, including the basic screens, menus, and functionality.

We put a team together, and we worked back and forth iteratively from sketching the design to building the different functionalities and eventually turning it into a prototype and eventually a fully deployed application on our website. They were able to take the concept to a finished project at every step of the way.

What is the team composition?

They usually provided a team of about four different people for each sprint, including three developers and a team lead who oversaw the day-to-day activities.

How did you come to work with Appsilon Data Science?

We had encountered them at a few different R conferences and were really impressed with their work, so after speaking to them and exchanging business cards one year, we followed up and they provided a really good pitch for what we needed so we decided to go ahead with them.

How much have you invested with them?

In total, we’ve spent about $150,000.

What is the status of this engagement?

The project started around November 2018, and we are continuing to work together.

RESULTS & FEEDBACK

What evidence can you share that demonstrates the impact of the engagement?

The quality of all of their work is excellent. We do regular monitoring and they’re always very responsive to feedback that we provide to them and continue to work till I’m satisfied. Technically, they’re one of the most skilled teams in their sphere that I’ve worked with.

How did Appsilon Data Science perform from a project management standpoint?

We communicated over Slack and used a GitHub repository to keep track of issues and milestones throughout the project. They work using Scrum methodology, including sprints and regular milestones, and we had daily meetings and weekday summaries and retrospectives. They were highly organized throughout the entire process, and we were very impressed with that aspect of the work.

What did you find most impressive about them?

Their skill and organization when it comes to communication make it unbelievably easy to understand each other and conduct back and forth about design issues, usability issues, or technical issues, no matter the capability differences of the teammates involved.

That combined with the broad range of skills that they offer which allowed us to accomplish all of our goals through one team in a consolidated way saved us a lot of time and money that we would have had to expend otherwise.

Are there any areas they could improve?

Honestly, there were no real downsides to the engagement. We didn’t encounter any significant problems throughout the entire thing, and they were a real pleasure to work with.

Do you have any advice for potential customers?

Don’t treat it like a kitchen remodeling where you move out of the house and come back in two weeks when it’s done. If you have someone who is there to communicate with them on a daily basis and attend the team meetings, you will have a much better collaboration than if you let things potentially drift in a different direction for a while without paying attention.

5.0
Overall Score
  • 5.0 Scheduling
    ON TIME / DEADLINES
  • 4.5 Cost
    Value / within estimates
  • 5.0 Quality
    Service & deliverables
  • 5.0 NPS
    Willing to refer
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BRONZE VERIFIED
Business Entity
Business Entity Name
Appsilon Sp. z o.o.
Status
Active
Jurisdiction of Formation
Poland
Id
0000483137
Date of Formation
Oct 28, 2013
Last updated
Jul 10, 2020
Client Reviews
VERIFIED CLIENT REVIEWS
5
OVERALL REVIEW RATING
5.0
Source
Clutch
LAST UPDATED
June 4, 2020