Build custom ML solutions

with experts trusted by 500+ companies.

Looking for a partner with proven expertise? Our machine learning solutions power some of the world’s top companies. Work with us to build everything from custom ML models to scalable multi-model systems.

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500+ companies rely on our top 1% tech talent.

Custom AI Development Services

You’ve probably used products built by our AI engineers.

We’ve developed custom AI solutions across industries. Whether you’re building AI-powered platforms to enhance operational efficiency or using AI to supercharge data analysis, we can help.

iOS App Development

No matter what you’re building, we can help.

From data preparation to model deployment, our machine learning development services cover every stage of the ML lifecycle. Bring in our experts for projects involving natural language processing, computer vision, deep learning, and more.

Data Storage and Management

We design enterprise-grade data storage architectures that support versioning, lineage, access policies, and downstream reuse. From object storage to analytical warehouses, we give you data systems that support scale, transparency, and compliance.

Data Processing and ETLc

Our engineers design and manage ETL pipelines to convert raw data into clean, structured formats optimized for training. We process data in batches or in real time, depending on the business need, using distributed systems when necessary.

Model Development

Our team builds models using proven frameworks and supports experimentation in notebook environments or IDEs, depending on the project. We follow standard best practices for training, evaluation, and iteration.

Experiment Tracking and Model Versioning

We use powerful experiment tracking tools to log hyperparameters, model configurations, performance metrics, and artifacts. We also version datasets and models to support reproducibility and compliance across teams and environments.

Model Deployment and Serving

Our team deploys models as APIs, background services, or embedded components. We containerize and expose models through secure, scalable endpoints, with built-in monitoring and logging. Our deployment strategies are tailored to latency, throughput, and infrastructure requirements.

MLOps and Automation

To maintain velocity and consistency, we automate retraining, testing, deployment, and monitoring. We build full MLOps pipelines that integrate CI/CD workflows, data validation, and testing. We use containers and orchestration platforms to manage deployments across cloud or hybrid environments.

Smart Personalization

Dynamic Templates & Customization

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Machine Learning case studies

Hundreds of ML projects delivered.

From pilot to scale, we have the experience to build ML systems that deliver real value. It’s why 500+ clients choose us as their machine learning development company.

Vetted Senior Talent

We give you engineers who’ve already proven they can deliver. Our rigorous evaluation process includes technical tests, English assessments, soft skill screening, problem-solving simulations, and more. Out of over 2 million applicants who apply yearly, fewer than 1% get the chance to join our team. This is how we ensure you get highly qualified developers who are experts in their fields.

Vetted Senior Talent

Timezone Aligned

Our nearshore software engineers share your workday, answering Slack messages, joining daily stand-ups, and presenting demos in real time. Project management is streamlined, questions are answered quickly, blockers are resolved as they come up, and simple code reviews take minutes, not days.

Timezone Aligned

Full-stack Capabilities

We cover architecture, development, testing, DevOps, and everything in between—reducing hand-offs and creating better architecture decisions for a smoother path from concept to production.

Full-stack Capabilities

Scalable Teams

With 4,000+ engineers on staff and thousands more in our pipeline, we can spin up pods or scale multiple teams across your company in days—so you hit aggressive timelines without bottlenecks.

Scalable Teams

Flexible engagement models

Need machine learning expertise?
Plug us in where you need us most.

We customize every engagement to fit your workflow, priorities, and delivery needs.

Staff Augmentation

Get senior, production-ready developers who integrate directly into your internal team. They work your hours, join your standups, and follow your workflows—just like any full-time engineer.

Scale your lineup as needed
Get our devs on your team(s)
Manage the team yourself

Schedule a Call

Software Development Teams

Spin up focused, delivery-ready pods to handle full builds or workstreams. Together we align on priorities. Then our tech PMs lead the team and drive delivery to maintain velocity and consistency.

Scale your lineup as needed
Get an entire team working with/for you
Manage the team yourself

Schedule a Call

Software Development Outsourcing

Hand off the full project lifecycle, from planning to deployment. You define the outcomes. We take full ownership of the execution and keep you looped in every step of the way.

Scale your lineup as needed
Get an entire team working with/for you
Leave the project management to us

FAQs

Accelerate machine learning development and delivery with our top-rated nearshore teams.

Find quick answers or contact our support team.

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1. What types of ML projects do you typically support?

We’ve worked on a wide range of projects, including ML-powered predictive analytics, recommendation engines, natural language processing (NLP) engines, computer vision, intelligent automation of business processes, and more.

2. Can you build explainable or auditable machine learning models?

Yes. We implement explainability frameworks like SHAP, LIME, and Captum when transparency is required. We also provide documentation, version control, and traceability for every model we build.

3. Can you help us work with data like text, images, or video?

Absolutely. Our data engineers work with both structured and unstructured data. That means we can build machine learning solutions that process and extract insights from text, images, and other formats. For example, we built an AI tool for a client in the legal industry that processed up to 10,000 text transcripts a day, summarizing 200-300 pages every few seconds.

4. What kind of data do you need to build a model?

We typically start with a set of historical data that includes examples of the outcomes you want to predict. This training data can be structured (like rows in a database) or unstructured (like documents or images).

5. How do you prevent bias in machine learning models?

Our team runs fairness checks during data prep and model evaluation. We flag potential biases early and work with your stakeholders to align the model with ethical and operational standards.

Build custom ML solutions