Contact Us

Trusted by 900+ happy clients including these Fortune companies

Artificial intelligence development

Machine Learning

Build, implement, and deploy Machine Learning models and algorithms that process high volumes of data to make applications smarter.

Natural Language Processing

Extract information from the human language like - text, voice, figures, names, relationships. Speed up analysis and reporting.

Computer Vision

Develop custom solutions that understand digital images and videos. Process and analyse objects, classify them into groups, and track them.

AI-Driven Chatbots

Integrate your mobile app(s) with services you are already using and extend their use cases for your employees and users.

Data Science & Research

Our services include digging into unstructured datasets, data processing, building predictive models, and turning these into actionable information.

AI Product Development

Our competencies in commercial and open-source AI allow you to use tools and frameworks of your choice to rapidly develop AI products.

Benefits of working with

Build smart applications for smarter business

Simform provides AI software development to apply smarter solutions to business problems. Our AI consulting can help you spot AI opportunities and eliminate barriers to AI. Together we can open up new AI opportunities that can – in a very real way – change the future.

We use the tools and frameworks of your choice without lock-in. Developing models faster using automated machine learning. Our machine learning powered business applications enable faster decision making, increased productivity, business process automation, and faster anomaly detection.

Use-Case Model

Use-case model is ideal for identifying AI projects to drive the performance of existing activities. Our ML engineers analyze each use case and create highly-customized solutions, aligned with unique business goals.

Frameworks and technologies of your choice

We use all open source machine learning and big data frameworks (Tensor flow, OpenAI, Scikit-learn, Keras, Caffe, MLlib, Hadoop, Spark, etc) to ensure that AI technologies can be seamlessly adapted.

Quick POC (Proof-of-Concept)

We review your business and data well. Often times many vendors miss this part and go directly and try to build ML models. Build a small-scale system, proving the viability of the machine learningmodels for your problem.

Recent case studies

What our customers say

Here’s how we do it


Review your capabilities and define future goals to make recommendations for tools, technology, and architecture.

Data exploration

Demonstrate what is possible by analyzing datasets and building models using quick, efficient and iterative prototypes.

Model development

We run thousands of experiments in parallel to develop a machine learning model. A model is the core of a machine learning system.


Insert the ML system with a REST API or a front-end app, developing necessary features to access the model in a user-friendly way.

What are the use cases for artificial intelligence?

  • Logistics
  • Fintech
  • Healthcare
  • IoT
  • Media & Entertainment
  • Marketing
  • Security
  • Telecom

Supply chain optimization

Leverage machine learning to detect weak links and delays in your supply chain for cheaper and efficient logistics.

Fraud detection system

Build a self-taught custom system to detect that can analyze client behaviour anomalies with deep learning models.

Personalized healthcare system

Provide personalized and efficient healthcare by processing wearable data with the help of AI-powered analytics software.

Smart home management

Smart home management system built using artificial intelligence service with sensor data analytics and face recognition.

Content recommendation engine

Recommendation engine to engage subscribers, cross-sell with personalized promotional offers to increase per-user revenue.

Consumer analytics platform

Use predictive models to anticipate your customer's next move & make precise audience targeting for better ad impact.

Face recognition software

Implement smart security using machine learning models that execute face & pose detection, recognition and tracking.

Network monitoring system

Apply big data analysis and predictive models for real-time fault detection in cases of network issues.

Awards & Recognition

Video LeftVideo Right

Simform Guarantee

  • Flexible, efficient scaling
    Flexible, efficient scaling

    Expand or reduce your remote team size on demand.

  • Team of 1,000+ engineers
    Team of 1,000+ engineers

    Access vetted experts in the tech stack of your choice.

  • Long-term predictability
    Long-term predictability

    Simform’s average engagement duration is 2 years.

Work with us


Artificial Intelligence as a Service (AIaaS) can be defined as the outsourcing of artificial intelligence services. AI as a service allows startups and organizations alike to experiment, iterate, and develop various business processes without the requirement of any upfront investment and with lower risk.
One must understand that AI is not as coherent as the other services. It tends to be a distinct component in a larger application, hidden in the background that facilitates extended capabilities, optimization, and other user interface improvements. Some of the platforms that we work with are IBM Watson & Bluemix platform, Amazon Machine Learning, Google TensorFlow and Cloud Prediction API, and Azure Machine Learning Studio to name a few apart from niche-focused industries such as SalesForce’s Einstein.

AI is a set of algorithms and methods instead of a single monolithic service. We believe Artificial Intelligence solutions should be strongly targeted over specific applications. All these platforms allow us to develop AI services that are customized, integrated and combined according to the requirements of individual products.
There are no boundaries to where you can benefit from artificial intelligent services. We assist our clients in automating their business operations by building AI-based custom software, mobile, and web apps to name a few.

Artificial Neural Networks: Custom software built using neural network-based artificial intelligence makes use of a computing system that consists of granular elements, highly interconnected processing elements.

User Behavior Analytics: AI-powered systems collects inputs from various user touchpoints and store them in the data repository.

Automated Reasoning: It is indeed an art to get computers to apply logical reasoning to solve complex problems. Uber uses automated reasoning to provide faster routes to drivers by learning from the previous trips on the same route.

AI-Powered Chatbots: Build integrated or stand-alone chatbots that help in drive sales through personalized communication.

Recommendation Engines: Build personalized & self-taught recommendation engines to provide custom services based on each user's choices.
That is not an easy answer, and like many other answers related to software development, it depends. We follow the concept of Evolutionary Architectures.

We picture your project as a set of different modules, each module can vary in complexity and requirements. Therefore each module can have a proper architecture that best suits it. Despite that, we have to think about architecture as living beings, so they will adapt and change during the project.

Choose a design for the whole system upfront usually is not the best idea. We would recommend you to picture your system as this set of modules and start to choose a design that best addresses each module needs, always favoring simplicity.
Managing a remote team is not easy. There are critical mistakes you can make when trying to leverage the vast amounts of remote talent.

Simform team integrates into your team, participating in standup and scrum meetings, weekly demos, weekly retrospectives.

Daily stand-ups - We do daily stand-ups where everyone gets on a video chat and tells you what they are working on that day and the previous day.
Weekly demonstrations - This one is simple: get everybody on a video chat, share screens, have people show their work, and then talk about it.
Weekly Retrospectives - A weekly retrospective is where you all collectively review what went well and what could have been improved based on the demo.

Have more questions?

Let us know and our experts will get in touch with you ASAP.

Talk to our experts