What can
artificial intelligence do?

AI adds intelligence to existing applications and systems. AI automates repetitive learning through data. Through AI, machines and applications can analyze images, understand data, comprehend speech, and make predictions.

Trusted by 900+ happy clients including these Fortune companies

900+
Happy Clients

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 Simform

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.

Smart apps using AI

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.

Automation using AI

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.

ML models

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.

Frameworks and technologies for AI

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.

POC using Machine Learning

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.

Smart apps using AI

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.

Automation using AI

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.

ML models

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.

Frameworks and technologies for AI

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.

POC using Machine Learning

Recent case studies

What our customers say

Here’s how we do it

1
Team
Assessment

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

2
Sprint
Data exploration

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

3
Tech
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.

4
StandUps
Integration

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

FAQs

Custom application development is the development of software for the specific needs of a business process or group of users. Such applications serve the goals of a business by providing features and workflows generally not found in more traditional and widespread off-the-shelf software.

Artificial Intelligence as a Service (AIaaS) can be defined as 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.

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 up front 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 favouring simplicity.

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 the 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.

Since AI is a set of algorithms and methods instead of a single monolithic service. We believe AI 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. This system process information by their dynamic state response to external inputs which helps in efficient data management, sequence and pattern recognition.

- User Behavior Analytics: AI-powered systems collects inputs from various user touchpoints and store them in the data repository. This data is then analyzed to detect patterns, trends, errors and user behaviors. One of the most common examples is a fraud detection system for online systems.

- 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. This is especially useful for an organization who up-sells or cross-sells their content, for example, Netflix.

Freelance marketplaces like Upwork, Toptal, Gigster, Freelancer, etc can help you get in touch with thousands of developers. They provide transparent access to devs but you have to vet candidates and take care of everything. These platforms do not provide a guarantee of delivery and results.

Tech agencies and software consultancies follow outdated engagement and execution models. The teams and devs hired through them don't integrate with your team well. Transparency and collaboration are lacking.

We started Simform with the goal of bringing assurance, certainty, and transparency in the software development services space. Most of our competitors provide TRANSACTIONAL services. You post a gig, they match you up with a developer and you take it from there. We aren't a transactional service.

Whether your project is at the early ideation stage or you have all features drawn out, our tech consultation team works with you to prepare a detailed tech solution and execution plan. We are huge believers in high output management and everything we suggest from tech architecture to talent skill set will focus on getting results and speeding up the time to market.

Our detailed technical consultation (which is itself worth thousands of dollars in value) consists of things like tech challenges of the project, what tech stack to use to solve those challenges.

Project’s technological execution roadmap brings all the pieces together to show how your project will come to life. Based on your project goals we help you define processes and delivery roadmap that suits your needs. It also includes a detailed hiring plan that includes details on what skill set and experience your team needs to have.

Tech architecture solution includes things like how features will be implemented with what technology and framework. It will also include things like algorithms and cloud integrations will be required to build your IP and build the tech engine.

We can do this because we have experience in delivering 100s of large scale complex systems. We know that there are many moving pieces in terms of technical know-how, experience, tight deadlines, unforeseen risks, and development challenges.

This tech consultation and talent skillset specification are provided for free so even if you don't work with us you can take it forward and use it in the future.

Managing a remote team is not easy. There are critical mistakes you can make when trying to leverage the vast amounts of remote talent.

We hear frequently from prospective clients that it takes forever to release new features, that users aren't adopting products, and that finished work hasn't met their expectations.

The solution: Communication, lots of it. Constant communication makes sure there can be absolutely no surprise breaks in execution.

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. When you’ve got people working for you in multiple time zones, this can be challenging. But it is crucial to the success of your team.

The Agile methodology calls for each contributor to go around, talk about what they’ve been working on, what they will be working on, estimate how long it’s going to take them, whether there are any critical blockers that could cause delay, and what their bandwidth looks like. These stand-ups are rigorously tracked by the Tech Lead.

But we do not just rely on unstructured communication. Everyone at Simform uses PPP (progress, plans, problems) methodology which is used at companies like Facebook, Google,Ebay, Skype etc. PPP is used to detail progress, issues, thoughts and anything else pertaining to their tasks.

Weekly demonstrations

This one is simple: get everybody on a video chat, share screens, have people show their work, and then talk about it.

If something is exceptional, call it out and appreciate the work. So team stays motivated.

If something is buggy or substandard, ask why and figure out solutions. This meeting is usually way longer than a stand-up as it is designed to literally “demo” the work that has been promised during stand-ups.

Keep in mind that if there are any “semi-off-topic” follow-up questions then they should be saved for the later Retrospective meeting.

Weekly Retrospectives
A weekly retrospective is where you all collectively review what went well and what could have been improved based on the demo.

We use the lean method of holding a meeting. It is great because it gives everyone a voice—there’s an element of democracy in the development process now. You’re still “the boss” but everybody now has some skin in the game. This will also help to organically create a culture within your remote team—something we will cover at length in a future post.

We start a project with a “Discovery Phase”. One of the outcomes of this phase is a list of features that the software will have. Those features then get broken into stories, and we write each story from the perspective of a Stakeholder of the system. User stories are easily digestible user behaviour flows detailing how user will achieve goals.

Then, for each story, we work with the clients to discover examples of how that specific stakeholder or end user uses the tool we’re building. Not only do we look for examples of success, but also examples of failure. And finally, we ask if there are examples of different ways to do the same thing. These scenarios are a list of actions that deliver value to this stakeholder.

Goal here is to build ubiquitous language and shared understanding between, developers, team members, stakeholders, and customers.

We use ATDD + BDD approach to create these user stories. This format has worked wonderfully for us as it helps Development Team (developers, QA, designers, TL) understand the acceptance criteria and goals of functionalities and features. Not to mention it generates lots of conversations between Tech team and stakeholders which helps increase shared understanding amongst everyone.

A point that is sometimes understated around this common language, is that the developers are learning not only the words used by the business but what they mean when they interact with each other in different contexts of the software. This is a hard piece of learning to come by without a structured way of using concrete examples to uncover details about the business.

To explain the point of SHARED UNDERSTANDING AND BDD, we have to start by accepting this simple premise: A large part of the challenges faced by software development projects are communication problems. Behaviour Driven Development is a way to:

- Structure communication to describe examples of how to use the software, these are called “scenarios”.

- Capture scenarios from the perspective of the stakeholders of the system

- Learn and Use the language and terminology of the business

- Gather just enough details of the system to be able to set a preliminary estimate

- Leverage the scenarios as executable tests that drive the design of the software

- Developers and clients work together to agree on what the system will do by building concrete examples.

Have more questions?

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

Talk to our experts