PoC

PoC

Amazinum’s specialists will help you define and understand the value, relevance, and challenges of a product, service, or service to make sure that it will meet the requirements and vision of the client.

Amazinum’s specialists will help you define and understand the value, relevance, and challenges of a product, service, or service to make sure that it will meet the requirements and vision of the client.

PoC main
PoC main
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PoC Essential (Discovery)

Stage of service

Week 1. Getting familiar with domain 

  • Discover business problems and opportunities
  • Clarify the business needs and opportunities
  • Investigate the available and potential data
  • Investigate the available and potential data sources
  • Execute EDA (exploratory data analysis)
  • Define the expected deliveries

Week 2. Investigating and adopting solutions

  • Define the metrics and evaluation of algorithms
  • Investigate the available models, solutions, approaches
  • Train models on domain data, evaluate, and compare.
Cost:4000$
Duration:2 weeks
Result:
  • One-pager rapport on how to utilize ML in your project
  • High-level Project Roadmap, with a breakdown into milestones
  • Ballpark estimate of each milestone
  • Ballpark time and cost estimation
  • Suggested team composition
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PoC PRO

Stage of service

Week 3. Improving results

  • Achieving better model(s) performance
  • Experiment with various datasets, tuning hyperparameters

Week 4. Finalizing research and preparing delivery

  • Preparing models and improvements overview
  • Preparing prototype demo
  • Wrapping in web service with exposed API
  • Dockerized solution ready to deploy on client’s infrastructure
  • Deploying dockerized solution
  • Preparing brief documentations
  • Describing further tasks and improvements
Cost:6000$
Duration:4 – 8 weeks
Result:
  • One-pager rapport on how to utilize ML in your project
  • High-level Project Roadmap, with a breakdown into milestones
  • Ballpark estimate of each milestone
  • Ballpark time and cost estimation
  • Suggested team composition
  • Prototype

How to determine if you need a proof of concept

Algorithm schema
Proof of concept

Why you need a POC

Projection of final cost, as well as assessment of efforts, investments, hidden costs, and savings measures.

Forecast of technical challenges, assessment of scale, and development of a work process plan, which will allow for making informed decisions.

Risk reduction by experimenting with a smaller project model.

Checking the viability of the project to assess the expected results and make changes to the current plan.

Attracting investments and gaining the trust of partners.

Improvement of development strategy, optimization of product functions, and improvement of interaction with the user based 
on testing.

Establishing a benchmark for performance measurement will allow the evaluation of actual and expected results. Thus, based on them, we can improve the decision-making process and product/service/service exit strategies.

FAQ

What happens in the case of a failed PoC?

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Not all proof of concepts yield success, and there can be various factors contributing to their failure:

  • Data may be disorganized and impractical.
  • The ETL (Extract, Transform, Load) workload can become prohibitively expensive when implemented at a larger scale.

In any case, the outcomes of failed proof of concepts should not be viewed as disappointments but rather as valuable learning experiences that can pave the way for future successful ideas.

Which companies used POC for their startups?

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Airbnb
Initially, the founders created a simple website that verified people’s requests for a vacant room or property. This allowed the company to attract investments and articles with a successful and revolutionary platform.

Slack
The beginning of Slack was the creation of an internal communication platform for a gaming company. This allowed the team to assess its potential in the market and become a leading tool for team communication around the world.

Tesla
Tesla has been conducting POCs for electric vehicles and energy storage systems. Their success in creating long-range electric vehicles and energy products such as the Powerwall and Powerpack has transformed the automotive and energy sectors.

Which industries used POC for their product?

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Self-Driving Cars: Companies like Waymo (formerly a project of Google) conducted POCs to demonstrate the feasibility of self-driving cars. These POCs eventually led to the development of autonomous vehicles and the emerging industry surrounding them.

IoT in Healthcare: POCs have been conducted to prove the effectiveness of Internet of Things (IoT) devices in healthcare. For instance, monitoring devices for patients with chronic conditions have shown how IoT can enhance patient care and reduce healthcare costs.

Artificial Intelligence in Healthcare: POCs using AI for diagnosing diseases and predicting patient outcomes have demonstrated significant success. IBM’s Watson for Oncology is a notable example.

Agricultural Technology: POCs for precision agriculture, using drones and data analytics to optimize farming, have proven to increase crop yields and reduce resource consumption.

Renewable Energy: Many renewable energy projects, such as solar and wind farms, began as POCs to prove the viability of clean energy sources, and they have since become major contributors to global energy production.

Food Delivery Apps: Companies like Uber Eats and DoorDash started as POCs in specific cities to prove the concept of app-based food delivery. Their success has reshaped the restaurant and food delivery industry.

Set Points

Data Analytics 

  • Descriptive Analytics
  • Diagnostic Analytics
  • Predictive Analytics
  • Prescriptive Analytics

Data Engineering

  • Data collection
  • Data cleaning
  • Data normalization and storing
  • Data pipeline management

Ml & AI

  • Computer Vision
  • NLP & LLM
  • Recommender Systems
  • Time Series Forecast

Requirements for the implementation of POC

Formation of clear goals and needs of the product.

Identifying unique features and details that will differentiate your project from others on the market.

Formation of success indicators of your POC – Any available data / data sources.

Any limitations to technologies.

Amazinum Portfolio

Check out a few of our recent projects

Smart Finance: Harnessing AI and ML for Document Digitization with OCR and NLP Technology

Smart Finance: Harnessing AI and ML for Document Digitization with OCR and NLP Technology

Advantages of engaging the Amazinum company

7

Years

We offer you our 
7 years of expertise in data science.

40+

ML Engineers

We have a large talent pool of 
highly-skilled ML engineers of Middle and Senior-level professionals.

16

Active Projects

Our team has successfully connected Machine Learning Engineers to technical departments in more than 19 companies.

Advantages of engaging the Amazinum company

7

Years

We offer you our 
7 years of expertise in data science.

40+

ML Engineers

We have a large talent pool of 
highly-skilled ML engineers of Middle and Senior-level professionals.

16

Active Projects

Our team has successfully connected Machine Learning Engineers to technical departments in more than 19 companies.

We develop unique solutions created for a specific project and client’s requirements.

The Amazinum team takes market features and micro and macro risks in the development of POCs in order to optimize your efforts and resources.

We take care of the qualifications of each specialist we offer for the project. Due to the presence of more than 40 specialists, we select a Data Scientist who has experience in a specific domain with specific technologies.

You may not worry about the employee if the case of termination or suspending of assignment, as well you don’t need to hire the specialist in advance in cases of uncertain project start

Our Industry Focus

Our industry knowledge and background give our clients and partners confidence that we understand their business. Here we highlighted a few top industries we are good at, penetrating to the smallest details and nuances of a certain branch.

SEO & Advertising icon

SEO & Marketing

Healthcare

Safety & Security

Sport icon

Sport

E-commerce & Retail icon

E-commerce & Retail

Gambling and Casino icon

Gambling and Casino

Manufacture icon

Manufacture

Ecology icon

Ecology

FinTech

Energy icon

Energy

Localisation icon

Localisation

IoT icon

IoT

Partners & Clients

We deeply appreciate our partners for cooperation. Every member of the Amazinum Team does their best to provide the highest quality of services and solutions. We satisfy all your needs and requirements.

byteant logo
sleepnumber logo
ushealth
wework
peiko
macys
softserve logo
aid genomics logo
startupsoft
Vimmi logo
PVH logo
sloboda studio logo
AstonUniversity logo
YellowMedia logo
byteant logo
sleepnumber logo
ushealth
wework
peiko
macys
softserve logo
aid genomics logo
startupsoft
Vimmi logo
PVH logo
sloboda studio logo
AstonUniversity logo
YellowMedia logo

Technologies

Learn about technology stack we use to implement data science:

Programming languages:

Python logo

for data analysis and processing:

OpenCV logo
NumPy logo
SciPy logo
Pandas logo

for creating solutions:

spaCy logo
Spark logo
PyTorch logo
TensorFlow logo
Keras logo
Scikit-Learn logo

for API development:

RabbitMQ logo
Flask logo
FastAPI logo
Django logo

for visualization:

ploty logo
matplotlib logo

Deploying solutions:

Docker logo
GitLab logo
TensorFlow logo
DVC logo
Vertex.ai logo
KubeFlow logo

Databases:

SQL:

PostgreSQL logo
ClickHouse logo
BigQuery logo
MySQL logo

NoSQL:

Bigtable logo
Elastic logo
Cassandra logo
mongo DB logo

Cloud Solutions:

Google Cloud logo
AWS logo

Technologies

Learn about technology stack we use to implement data science:

Programming languages:
python icon

for data analysis and processing:

Pandas icon
Numpy icon
SciPy logo

for creating solutions:

PyTorch icon
keras
spacy logo
spark icon
Tensorflow
scikit learn icon

for API development:

rabbitmq icon
fastapi logo
flask icon
Django logo

for visualization:

postgreSQL
clickhouse logo
mongodb logo
GoogleBigQuery
mysql logo
Deploying solutions:
Docker icon
dvc logo
gitlab logo
Vertex icon
Tensorflow
kubeflow logo
Databases:

SQL:

postgreSQL
clickhouse logo
mongodb logo
GoogleBigQuery
mysql logo

NoSQL:

elastic logo
Cloud Bigtable logo
Cassandra logo
Cloud Solutions:
Google cloud
aws logo

Vitaliy Fedorovych

CEO, Data Scientist at Amazinum

Vitaliy Fedorovych contact us photo

Hello there!

Amazinum Team assists you through all data science development processes:
from data collection to valuable insights generation.
Get in touch with our CEO and Data Scientist to figure out the next move together

Contact Us

Click or drag a file to this area to upload.

Contact Us

Click or drag a file to this area to upload.
Alina Bazarnitska contact us photo

Bazarnitska Alina

Client Partner

Ihor Khreptyk contact us photo

Ihor Khreptyk

Client Partner

Stopnyk Zoriana photo

Stopnyk Zoriana

Client Partner

Vitaliy Fedorovych contact us photo

Vitaliy Fedorovych

CEO, Data Scientist

Vitaliy Fedorovych

CEO, Data Scientist at Amazinum

Vitaliy Fedorovych contact us photo

Hello there!

Amazinum Team assists you through all data science development processes:
from data collection to valuable insights generation.
Get in touch with our CEO and Data Scientist to figure out the next move together

Contact Us

Click or drag a file to this area to upload.

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Book a FREE consultation today and get a 10% discount on your next project

You will receive:

  • A qualified specialist with experience in your field
  • High-quality and fast solution for your business
  • Convenient models of cooperation from POC to a full-fledged project

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No limits to solutions with Amazinum