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AI & ML Development Services

AI & ML Development Services

Redefine the edge of custom top-notch possibilities with our AI engineers.

Trusted by industry giants and innovative startups

BetterQA

"One of the best partners for our company — flexibility and commitment to success." — Tudor Brad, Owner

AdviNow, Inc

"A medical system with AI and NLP — very happy with Emphasoft's work throughout." — Jim Shelby, CTO

Lemniscate Labs

"An amazing experience — responded quickly to changing deliverables. 100% recommend." — Ayush Sood, CEO

Our top-notch AI solutions

AI-as-a-Service (AIaaS)

Supercharge your operations with our AI powerhouse, delivered to your doorstep.

AI product development

Customized AI products using cutting-edge algorithms and machine learning.

Smart assistants & chatbots

Enhance customer interactions with AI-backed assistants and chatbots.

Image classification

Turn visual data into actionable insights.

Object detection & face recognition

Superior detection and secure user recognition.

Predictive modeling & automation

Insightful decisions and maximum efficiency through automation.

15+years of experience
100+AI projects delivered
55+bespoke solutions

Case studies

Healthcare

Automated patient-doctor meetings using NLP (BERT, Keras) to diagnose diseases from symptoms and add telemedicine features. (BERT, Keras)

Face recognition

Custom recognition dashboard (Django) with video 2-factor authorization and an iOS check-in app. (Django, V2FA, iOS)

Video streaming

Rewrote a legacy C++ solution to Python with a custom AWS setup — real-time face detection and matching against a database. (C++, Python, AWS)

Virtual try-on

Real-time glasses try-on SDK with a CNN model in a white-label iOS app. (SDK, iOS)

Dive into the AI / ML process

01 — Review your capabilities and define future goals.

02 — Pre-process and store raw data.

03 — Perform exploratory data analysis.

04 — Sanitize and prepare data for modeling.

05 — Define the most appropriate machine learning model.

06 — Implement the model or use existing services.

07 — Deploy machine learning solutions.

Why AI & ML companies choose us

Customer focus

Our schedule adjusts to client time zones — someone helps you 24/7.

Scale fast

We integrate with your team and bring strong expertise and best practices.

Easy set up

Start as soon as contracts are signed — everything is ready to go.

From idea to market

We help you build from scratch, fine-tune processes and bring it to market.

We're here to help you level up

Let's talk

Feel free to book a discovery call — we'll get back to you in 24 hours.

Frequently asked questions

How do we know whether our problem is a good fit for AI?

We start by reviewing your capabilities and defining goals: which decision or task should improve, what data exists and how success will be measured. Some problems call for a custom model, some for existing AI services, and some do not need machine learning at all. We do this assessment before any modeling, so you do not pay for a model you do not need.

What data do we need to get started?

It depends on the task. Image classification and object detection need labeled examples; predictive modeling needs historical records that include the outcome you want to predict. Your data does not have to be perfect upfront, because our process includes pre-processing and storing raw data, exploratory analysis and cleaning it for modeling. The analysis also shows whether there is enough data to justify a model.

Do you build custom models or use existing AI services?

Both. Part of our process is deciding between a custom model and existing services, based on accuracy needs, cost, data privacy and time to market. Our cases include disease diagnosis from symptoms with NLP built on BERT and Keras, a CNN model for real-time virtual glasses try-on in an iOS SDK, and real-time face detection on a custom AWS setup.

Can AI features be added to our existing product?

Yes. We add chatbots, smart assistants, image recognition and predictive features to existing web and mobile products. In one case we rewrote a legacy C++ video streaming solution in Python on a custom AWS setup to support real-time face detection and matching against a database. We work alongside your team and draw on practices from more than 100 AI projects.

What does an AI project cost and how long does it take?

Both depend on how ready your data is, whether a pre-trained service is enough or you need a custom model, the accuracy targets and the deployment environment. A proof of concept on existing services takes far less effort than a custom model running in production. We quote once we understand these factors; book a discovery call and we reply within 24 hours.

What happens after a model is deployed?

Deployment is the last step of our process, but a model still needs attention afterwards: monitoring quality on real data, retraining when the data changes and keeping infrastructure costs under control. We can keep supporting the solution or hand it over to your team. Our schedule adjusts to client time zones, so someone at EmphaSoft is available 24/7.

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