Appsilon | R Shiny | Machine Learning

BACKGROUND

Please describe your company and position.

I am the Senior Data Analyst of Boston Medical Center

Describe what your company does in a single sentence.

Boston Medical Center is an academic medical center and a national leader in cutting-edge research.

OPPORTUNITY / CHALLENGE

What specific goals or objectives did you hire Appsilon | R Shiny | Machine Learning to accomplish?

• Develop beautiful R Shiny application to combine clinical outcomes with place-based data.
• Enable users to build custom, dynamic logistic regression models.

SOLUTION

How did you find Appsilon | R Shiny | Machine Learning?

Online Search

Why did you select Appsilon | R Shiny | Machine Learning over others?

• High ratings
• Company values aligned

How many teammates from Appsilon | R Shiny | Machine Learning were assigned to this project?

2-5 Employees

Describe the scope of work in detail. Please include a summary of key deliverables.

Our goal was to take an existing R Shiny prototype and made dramatic improvements in functionality, usability, and scalability. Key deliverables were: a beautiful application that could run using data stored in many different kinds of databases. 

Application needed to include several specific displays, filtering capability, dynamic logistic regression models and ability to assess model performance, and ability to display geographic data about neighborhoods in Boston. The application also needed to include detailed documentation and informational displays, and be flexible for additional users to add additional outcomes and variables to display and analyze.

RESULTS & FEEDBACK

What were the measurable outcomes from the project that demonstrate progress or success?

We were able to validate that outcomes matched expected values. Appsilon also dramatically improved speed of application and reduced loading time and other usability barriers. Much of the improvements came from the UI design, so they were easy to see as the team made changes and improvements. Our later assessment of success will be to track user adoption, which the team at Appsilon also built in means of tracking.

Describe their project management. Did they deliver items on time? How did they respond to your needs?

Yes - they have been able to deliver all of the stated project goals on time. They communicated effectively, called out road blocks and risks very early, and made sure to address any concerns we had promptly. The development team was exceptional, and they were supported by an organized and effective delivery manager. I always felt like our project was in good hands.

What was your primary form of communication with Appsilon | R Shiny | Machine Learning?

Virtual Meeting

What did you find most impressive or unique about this company?

Their unique expertise with R Shiny, as demonstrated by their sample applications. Additionally, once we scoped the project with them, I felt like they had a great understanding of our goals, and were able to create a team who would effectively address our needs. The team was able to get up to speed with a very complex project quickly and make strategic and novel improvements - it was very impressive and reassuring as a customer!

Are there any areas for improvement or something Appsilon | R Shiny | Machine Learning could have done differently?

Not that I can think of. I was impressed with the process, and with the product. I am very glad we were able to work with them on this project.

BACKGROUND

Please describe your company and your position there.

I am a Data Analyst in one of the world's largest wind turbine manufacturers.

OPPORTUNITY / CHALLENGE

For what projects/services did your company hire Appsilon | R Shiny | Machine Learning, and what were your goals?

We needed software development services to standardize our development process of R/Shiny applications. We also needed software development services to improve our existing R/Shiny applications as well as to develop new ones. Appsilon helped us by providing software development and consultancy.

SOLUTION

How did you select this vendor and what were the deciding factors?

We were looking for R/Shiny consultancy when we discovered Appsilon’s various contributions to R/Shiny related topics in the R community. Their portfolio looked very impressive and caught our attention right away.

Describe the scope of work in detail, including the project steps, key deliverables, and technologies used.

Appsilon was responsible for reviewing and standardizing our internal development process and develop new applications. The developed applications cover a variety of topics. They range from applications for the evaluation of turbine failures in a monitoring system and viewing installed softwares and parameters on various asset types, to managing master data related topics.

How many people from the vendor's team worked with you, and what were their positions?

We worked with a team of up to three developers and a delivery manager.

RESULTS & FEEDBACK

Can you share any measurable outcomes of the project or general feedback about the deliverables?

Thanks to the implementation of a standardized development framework the time from creating a new application to a first viable product has dramatically decreased. Application-wise, the development of an evaluation application for a monitoring system allowed us to cut our manual review process in half.

Describe their project management style, including communication tools and timeliness.

We manage projects, Appsilon provides us with their knowledge and experience in development, consultancy and technologies. Weekly sprints and deliverables are planned and maintained in our internal Git infrastructure. Monthly meetings with a delivery manager from Appsilon allow us to adjust the team structure and requirements in a very dynamic way.

What did you find most impressive or unique about this company?

Their professionality and engagement. The team is always helpful and proactive. We have many open discussions, and the developers do not hesitate to share their own thoughts and ideas. They focus on established goals to meet our expectations. Their attitude and flexibility have been very valuable and thanks to that we could continue our cooperation over years.

Are there any areas for improvement or something they could have done differently?

None of the things are to improve.

BACKGROUND

Please describe your company and your position there.

I'm a professor in the Instutute of Dendrology, Polish Academy of Sciences, working on the effects of climate change on forests. Institute The Institute of Dendrology, Polish Academy of Sciences, in Kórnik is a scientific unit that carries out interdisciplinary research on the biology of woody plants at all levels of their organization. Research directions pursued at the Institute include: biogeography and systematics, physiology and ecophysiology, molecular biology, seed biology, biochemistry, genetics, proteomics, ecology, bioindication, phytoremediation, mycology and mycorrhiza, selection, breeding, and propagation of woody plants, entomology, and biology of invasive species.

OPPORTUNITY / CHALLENGE

For what projects/services did your company hire Appsilon | R Shiny | Machine Learning, and what were your goals?

We developed models of tree species distribution under current climate and we predicted their future ranges. We published our results in Global Change Biology (https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.13925) and it has quickly been widely recognized by scientists. We required a professional dissemination of results via a web app, allowing a wider audience to explore our results and look on the maps interactively.

This was required to communicate our outcome with not only scientists, but also professionals, decisionmakers and all people interested how climate change affects our life.

SOLUTION

How did you select this vendor and what were the deciding factors?

We found Appsilon's DATA for GOOD initative (https://appsilon.com/data-for-good/) that supports projects related to climate change impacts and we contacted Appsilon. After short discussion both sides decided that it is what we need.

Describe the scope of work in detail, including the project steps, key deliverables, and technologies used.

We started from a kick-off meeting to discuss our aims and possible solutions, and then Appsilon developed a draft version of Shiny application presenting our results. During next meetings we checked all functionalities (variants, visualisations, map options) and we decided to add additional layers. When the app was finished we met again to discuss dissemination of result and to provide descriptory part of application.

How many people from the vendor's team worked with you, and what were their positions?

3 people (2x R Shiny Dev, 1 Designer)

RESULTS & FEEDBACK

Can you share any measurable outcomes of the project or general feedback about the deliverables?

New visualisation of our results reached a wide audience in social media, and gained increased media attention (e.g. https://biqdata.wyborcza.pl/biqdata/7,159116,29163981,choinka-z-buka-i-… or https://www.eureporter.co/environment/climate-change/2022/11/17/what-wi…). Users higlighted accessibility and simplicity of design, reporting that they will use it in their lectures. It meet expectations,

Describe their project management style, including communication tools and timeliness.

We had google meet meetings and e-mail communication, presenting all steps of collaboration, presenting development of app and its stages.

What did you find most impressive or unique about this company?

Appsilon Data for Good (https://appsilon.com/data-for-good/) initiative allows delevelopers to involve developers in projects related to the most important threats to human and biodiversity. Their prioritization of focus on such initiative in the age of climatic crisis is an unique opportunity to employ advanced technology to support actions that can reverse or mitigate negative effects of climate change. Our collaboration within that initative is therefore a novel way of science-business interaction. Everything went in line with expectations.

Are there any areas for improvement or something they could have done differently?

none

BACKGROUND

Please describe your company and your position there.

I am the Sr. Manager for Data & Analytics serving the Commercial and Medical Affairs Community.

OPPORTUNITY / CHALLENGE

For what projects/services did your company hire Appsilon | R Shiny | Machine Learning?

Appsilon services were used to deploy the R environment in the cloud environment for Medical Affairs use in support of R-Shiny dashboards. The reporting application was hosted by an external vendor and was brought in-house.

SOLUTION

How did you select this vendor and what were the deciding factors?

Appsilon is used in Genmab by another department with expertise on R.

Describe the project in detail and walk through the stages of the project.

Data and Reporting R-Shiny dashboards used by Medical Affairs were hosted by an external vendor. These capabilities were brought in-house. This project involves various components and integration of these systems. In addition to building the server, the aspects that took the longest to resolve were those related to the authentication/permission to deliver a seamless user experience. Data was loaded in Snowflake database, R environment ( WB/Connect/Package Mgr) were deployed in the cloud. Jumphost server were provisioned as the entry point for application development team (with no company laptop/asset). R was configured to source data from Snowflake and R-Shiny Dashboards were deployed.

How many resources from the vendor's team worked with you, and what were their positions?

Unfortunately, the IT lead (Digital Strategy & Platform) who was responsible for engaging Appsilon from the start is no longer with the company. who can provide this level of information. In my participation in the project - we have about 2-3 resources who started out since Jan2022 and were in the role of platform and application admin.

RESULTS & FEEDBACK

Can you share any outcomes from the project that demonstrate progress or success?

Bringing the data and reporting dashboard in-house that can be leverage by other teams. Ability to perform analytics on both commercial and medical data to generate insights in a single platform.

How effective was the workflow between your team and theirs?

It was known the support hours will be in EU but the customer is in US. The time difference was a challenge, but we made it work. If there was a full overlap on hours, probably the duration of project could have been shortened.

What did you find most impressive or unique about this company?

Resources are committed to help resolve issue..

Are there any areas for improvement or something they could have done differently?

Improved user experience... integrate settings/config when servers and services were restarted as part of general building of the environment. Define best practice for platform maintenance

BACKGROUND

Introduce your business and what you do there.

I am the global head of data science for a very successful biopharmaceutical company. We rank in the top five and are a market leader in several indications. My role is to help the analytical scientists do their job more efficiently and ensure they get the most out of the data.

OPPORTUNITY / CHALLENGE

What challenge were you trying to address with Appsilon | R Shiny | Machine Learning? 

We had to ensure that our data quality was standardized so that even when people aren’t strong in statistics and mathematics, they can still get the best data assessment possible. We brought Appsilon on as a partner to standardize the process by helping to develop apps and programs that automate the data assessment and reporting steps.

SOLUTION

What was the scope of their involvement?

Appsilon helped us generate an extract, transform and load (ETL) process through software programming. This process converts data from one format to another and then organizes it within a database in a third format. They used tools such as R, SQL, Jenkins, Amazon S3, and Oracle Database to accomplish this.

What is the team composition?

I worked with five people: two developers, an engineering manager, a project manager, and an infrastructure engineer. 

How did you come to work with Appsilon | R Shiny | Machine Learning?

I asked RStudio for references, and they recommended two companies. I interviewed both of them, and Appsilon did a fantastic job during the interview, so we moved forward with the partnership.

How much have you invested with them?

We spent around €50,000 (approximately $51,000 USD).

What is the status of this engagement?

The project started in March 2022, and the original end date was set for May. This got postponed due to illnesses and vacation time, and the project was completed in June 2022.

RESULTS & FEEDBACK

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

Appsilon created the engine that we plan to reuse as the central core for bigger projects. We already used their work to build a demo app to show upper management that everything worked as expected.

How did Appsilon | R Shiny | Machine Learning perform from a project management standpoint?

They were very good, and I was satisfied with the overall project collaboration. In the beginning, I thought I could manage the project on my own. Ultimately, I was very happy to have help from the Appsilon project manager because I could focus on other tasks.

We used a Scrum process to keep things simple. As for tools, we worked with the onboarding tools within Microsoft Teams for the most part. There is a planning tool, and we also used OneNote, which was handy, easy to use, and had a fast learning curve for the team.

What did you find most impressive about them?

I had prepared for the interviews by laying out my requirements and questions. When I interviewed Filip (CEO), he led the discussion and answered my questions in the order I had written them down, without me asking. It was clear that they understood the project from the beginning and had thought it through. I was most impressed with how he read my mind. 

Are there any areas they could improve?

I think they could have improved the long-term planning for the project phase based on team members’ vacation time so that defined timelines could be met.

There was an interruption because one of the team members got married and had to travel, which restricted our meeting times. The process required two programmers to work together, which was fine; however, when one programmer goes on vacation, the construct breaks down. 

Do you have any advice for potential customers?

The general problem with Scrum mode is that you need a very clear vision of what you want. My advice would be to invest in clarifying the vision and ensuring that it’s very detailed. Otherwise, Scrum can completely ruin your process if you’re unsure about the answers to questions that arise throughout the project. 

BACKGROUND

Introduce your business and what you do there.

I’m a data scientist within a private equity firm. My role is to work with portfolio companies.

OPPORTUNITY / CHALLENGE

What challenge were you trying to address with Appsilon?

We engaged Appsilon to build an application that could combine the data and machine learning web apps of one of our portfolio companies.

SOLUTION

What was the scope of their involvement?

Appsilon produced a new prototype off of a version that had been previously made by someone on my team. We began the project with some rough documentation and narrowed down what refinements we wanted to be made on the web app. We also did wireframing at this stage.

The initial version of the app was developed and ran locally and was being used for inherently geospatial tasks. It could display several tabs, and each tab either displayed different map information or allowed the user to enter addresses and various location data. The app would then make a series of API calls and calculations in the background and then do some model inference and model scoring. Through that, it would display predictions as well as relevant contextual data. Appsilon redesigned some of these front- and backend components as well as improved the UX. 

What is the team composition?

On any given day, we are working with four people. Over the whole course of the project, however, we've interacted with about six engineers.

How did you come to work with Appsilon?

My colleague saw their previous work and was the one who found them. Once we put the numbers together, we found that Appsilon ticked all of our boxes, so it made sense to go with them. 

How much have you invested with them?

We have spent over $100,000 on the project.

What is the status of this engagement?

Our engagement started in November 2021. The first phase ran for 10 weeks, but we continue to work with them for ongoing maintenance.

RESULTS & FEEDBACK

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

I don't have any dollar amounts that I could share, but the engagement from our user base rapidly grew. We could see how many logins and how much time was being spent on the app. In just the first month, the average time per user was at around 10 hours, which surpassed our expectations.

How did Appsilon perform from a project management standpoint?

Appsilon has been great. They work in an agile format and always meet deadlines. We find them to be very collaborative and enjoy working with them. 

We use GitHub as a project management tool and we communicate through email and Slack. We also have daily standups. When we conduct sprint reviews, they showcase their progress not only to the stakeholders at the firm but also to the portfolio company.

What did you find most impressive about them?

They’re a very capable team of good builders, and with the project managers’ help, everything came together well. 

Are there any areas they could improve?

I have no complaints about their work. In fact, I would like to work with them again.

Do you have any advice for potential customers?

Communicating with the team frequently will be very helpful.

BACKGROUND

Introduce your business and what you do there.

We’re a Japanese-owned biotech company operating in the UK, where we have about 200 employees. My role is director of statistics.

OPPORTUNITY / CHALLENGE

What challenge were you trying to address with Appsilon?

We have various tools for predicting the dose needed for new drugs, but these tools were mostly Excel-based. We wanted to develop an app that could integrate all of our different calculations and give a better format for people who want to explore the data.

SOLUTION

What was the scope of their involvement?

Appsilon first set up a two-day workshop to go through the full breadth of our requirements. They also studied the profiles of the customers who would potentially be using the app. They then went into developing the application using the R Shiny framework. I provided the team with initial prototypes, and they used that code and developed it.

The team linked the product to a database and designed it for scientists who work in drug development and use in vitro and in vivo data. We asked them to introduce functionalities that could allow scientists to upload data, and that’s what Appsilon did. Once data is uploaded, the app could guide the user through various steps and calculations for an accurate prediction.

What is the team composition?

We were in daily contact with two developers. We also had a project manager and a UI/UX designer.

How did you come to work with Appsilon?

We initially found them through Google. Appsilon's bid demonstrated the best understanding of the project and the best approach to managing the project. 

How much have you invested with them?

The cost was £140,000 (approximately $185,000 USD). The workshop was paid for separately.

What is the status of this engagement?

We started working with Appsilon in October 2021, and the project was completed just this March 2022.

RESULTS & FEEDBACK

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

The app hasn’t been rolled out yet, so we have yet to get a hold of any metrics. Anecdotally, however, the software turned out well. We have various partners who are planning to use it, and we believe it will be a fantastic tool for new chemists. It will be very helpful in designing drugs, ensuring that the drugs have the right properties, and maintaining quality consistency across different departments. 

How did Appsilon perform from a project management standpoint?

We had 10 two-week periods of co-development included in the budget, and we held daily scrum meetings with the Appsilon team. They kept us on track and up to date throughout the engagement, enabling us to prioritize the work and finish the development on time.  

We used GitHub for progress-tracking, Google Meet for the daily calls, and Microsoft Teams for file sharing and instant communication.

What did you find most impressive about them?

Appsilon had a genuine interest in the science that powered the software. It was quite a technical project, but they maintained high standards throughout. They constantly gathered and incorporated our feedback into the product, ensuring that what they delivered was what the users needed. 

At the end of it, they also explained the entire code that they had developed so that I could easily make any changes to it if I wanted. That wasn’t really necessary, though, since they gave us a really good product.

Are there any areas they could improve?

No, there’s nothing they could’ve done better. We’re very happy with everything they delivered. 

Do you have any advice for potential customers?

The customer will have to be prepared to provide a lot of input and scientific data. Appsilon delivers fantastic products, but that requires the customer’s time and commitment as well to ensure that the team develops exactly what is needed.

BACKGROUND

Please describe your company and your position there.

I am an associate professor at Université Laval in Québec city, Canada. I am an oceanographer, specialist in the ecology of Arctic marine zooplankton that I study mainly via numerical modelling and in situ imagery.

OPPORTUNITY / CHALLENGE

For what projects/services did your company hire Appsilon, and what were your goals?

We had generated many thousands of individual images of the zooplankton group that dominates the ecology of the North Atlantic and Arctic oceans: the copepods. These critters are about the size of a grain of rice, but they are extremely lipid rich, so much so that the marine food web totally depends on it, from fish larvae to baleen whales. Hence we wanted to measure at the individual level their quantity of lipids to obtain an indicator of the ecosystems health and productivity.

However, we could not afford to employ humans specialists to examine all these images and measure the lipid content. As a result, we were looking for an efficient machine learning / computer vision solution to (1) revisit years of archived data and (2) expend the approach to the ever increasing flow of data coming from new sampling campaigns and devices deployed across the oceans.

SOLUTION

How did you select this vendor and what were the deciding factors?

Colleagues in France active in the development of machine learning solutions for marine ecology research problems brought to our attention that Appsilon advertised a program, "Data for good", that offered pro-bono professional services for projects that they think may have a positive impact on problems related to the current climate change crisis. We rapidly exchanged about our project, our needs, their possible solutions... and very rapidly we were able to start something and end up with an excellent solution for us within a few weeks!

Describe the scope of work in detail, including the project steps, key deliverables, and technologies used.

They received a link towards preliminary python code developed by a graduate student to train a neural network model to segment the "lipid sac", a visible organ that can be seen in transparency in individual pictures of copepods, as well as a batch of annotated and non-annotated images. From this, they rapidly developed their own solution that involved a u-net architecture for segmenting the lipid sac within the animal.

They performed an extensive analysis of their model's performance, for which they achieved a median intersection over union (IoU) > 0.8, a very significative improvement from a value of ~ 0.5 we had reached by ourselves. Their results analysis also allowed us to better understand the structure of our data and to relate good/bad performance of the model to fundamental biological properties of our sampled individuals.

How many people from the vendor's team worked with you, and what were their positions?

There were 2 people involved, one project manager with a scientific and software engineering background, and a dedicated software engineer, specialist in machine learning applied to computer vision problems.

RESULTS & FEEDBACK

Can you share any measurable outcomes of the project or general feedback about the deliverables?

We had relatively few experience ourselves in the domain of machine learning applied to images of organisms, and they managed to reach very satisfactory results in a few weeks only. We will present these results to scientific workshops in March, and publish these results in a high impact scientific journal in the spring. More importantly maybe, we will be able to start very soon the exploration of our trove archived data acquired since 2013, and new projects that are currently developed will already include this solution to generate groundbreaking results.

Describe their project management style, including communication tools and timeliness.

From the get go, the team was interested, interesting and vey committed. They responded very rapidly, and did not hesitate to put just the right level of gentle pressure to push researchers living in academia to be more responsive than they would usually ;-) We managed to have weekly meeting to discuss about the intermediate reports that arrived on time ahead of the meetings, each time taking into account the outcome of our previous discussions or email exchanges.

What did you find most impressive or unique about this company?

We developed a bound very rapidly, and I am convinced it is mostly owing to their transparency (in their objectives and methods). Their genuine curiosity and impressive ability to adapt to our needs were outstanding!

Are there any areas for improvement or something they could have done differently?

Sincerely, I would be happy if I could always deal with such level of professionalism and engagement.

BACKGROUND

Introduce your business and what you do there.

I’m the data science manager at a consumer electronics company.

OPPORTUNITY / CHALLENGE

What challenge were you trying to address with Appsilon?

We needed to have a way of building stable data products, but we didn’t have a team that specialized in infrastructure as code or Cloud deployments. We also wanted to be more efficient and reduce the amount of time between an idea and the deployment of a data product. Standing up the platform in itself is a challenge that no one on my team had the skills to do, so we decided to hire Appsilon to help us.

SOLUTION

What was the scope of their involvement?

We hired Appsilon to develop our infrastructure and document everything as infrastructure as code. This way, I can take the repository code and use the same tool they built it with to redeploy the platform in the future if I ever need to. They documented everything and provided explanations on how they set the infrastructure up, where a code goes within the code, and how they manage it.

Now that the infrastructure is up and running, we’ve started digging deeper into its optimization and testing. We’re currently focusing on the building component of the project, which involves maintaining the infrastructure and testing it to help us build it out and further improve it. I would probably extend our engagement once this is done to better understand the best maintenance processes for the platform.

What is the team composition?

We’re working with one full-time backend engineer, who works on building the infrastructure as code, a part-time supporting engineer, and a project manager, who is my main point of contact.

How did you come to work with Appsilon?

We initially reached out to the company that hosts the platform that we wanted to use, but they said that they didn’t offer the services that we needed and instead referred us to Appsilon.

How much have you invested with them?

We’ve spent around $100,000 so far, but we’re estimating that we’ll end up paying around $200,000 in total by the end of the engagement.

What is the status of this engagement?

We started working together in September 2021, and the engagement is ongoing.

RESULTS & FEEDBACK

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

We don’t have any quantitative data yet because we’re still working on the infrastructure, but I can definitely say that it works. We’re still ironing it out but I’m very happy with the results so far.

How did Appsilon perform from a project management standpoint?

Appsilon has performed very well in terms of project management — I really appreciate that they have their own project manager who helps coordinate between ourselves and some of the platform vendors. Every two weeks, they would give us an update on how things are going.

We primarily communicate through Slack and email. We also use GitHub and GitLab to file issues, track our tasks, and communicate with the backend engineers.

What did you find most impressive about them?

The best thing about working with Appsilon is that they seem to have a very well-established set of processes when it comes to managing a product. This dovetails into the fact that they are really great at documenting, which is something that we specifically wanted from them for this engagement.

We essentially asked them to document the project well enough so that we won’t need their services anymore in the future — and they’ve done exactly that. Overall, I’m very happy with the amazing work they’ve done so far.

Are there any areas they could improve?

I don’t think there’s anything they could improve on — if anything, I’d say that most of the shortcomings are on my side.

Do you have any advice for potential customers?

I’d say the best thing you can do is to loop them into the problem spaces that you’re trying to resolve. I think they would perform best if you give them all of the details you can about what problem you’re trying to resolve.

Another thing is to make sure to give them things that produce feedback, things that would feasibly put the products under strain. You need to do that sooner rather than later because you can only resolve problems when you surface them.

BACKGROUND

Introduce your business and what you do there.

I’m the CEO of Enginious, a virtual production studio.

OPPORTUNITY / CHALLENGE

What challenge were you trying to address with Appsilon?

We needed help building our virtual human platform.

SOLUTION

What was the scope of their involvement?

We provided them with the documentation, and the team was in charge of the development. Appsilon is responsible for everything related to machine learning (ML). They provide us with the algorithms we need for our R&D, and they’re in charge of coding. Our platform is an AI platform that creates virtual humans from sketches. To be specific, the system turns a 2D sketch into a 3D model.

What is the team composition?

We’re working with three developers from Appsilon.

How did you come to work with Appsilon?

They were recommended by another company we were working with.

How much have you invested with them?

We’ve spent $100,000.

What is the status of this engagement?

We started working together in June 2021, and we continue to collaborate.

RESULTS & FEEDBACK

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

Appsilon has been fantastic; they’re very smart, and they’ve been able to understand our 3D pipeline very quickly. Overall, I’m very happy with our engagement.

How did Appsilon perform from a project management standpoint?

Their project management is great. They meet deadlines, and they’re very responsive and organized. We use Slack and Google Docs.

What did you find most impressive about them?

We’re impressed that they are results-oriented and not process-oriented. They don’t just charge us for the hours. Instead, they try to deliver our business goals and we appreciate that.

Are there any areas they could improve?

They’re not very flexible on contract terms, and that’s one thing that could be better.

Do you have any advice for potential customers?

Give them a clear brief.