Machine Learning Outsourcing: TOP 10 Leading Partners to Consider

Machine learning outsourcing is becoming a smart way for companies to handle advanced AI work without burning time or budget. Many teams want faster delivery, better accuracy, and access to experts, yet they struggle with hiring limits and rising costs in outsourcing machine learning. This MOR Software’s guide will help you choose the right partners and understand which services bring the most value.

What is Machine Learning Outsourcing?

Machine learning outsourcing refers to working with outside specialists who create and manage ml model. This helps companies access skilled support without forming a full internal team. It also brings lower costs, quicker delivery, and flexible resource scaling for different project needs. This fits a wider trend where the global IT services outsourcing market was USD 611.80 billion in 2024 and is projected to reach USD 1,345.48 billion by 2034.

When using machine learning outsource services, organizations can reach global experts who understand deep learning tasks, annotation work, and predictive systems. This setup lets teams handle their main business activities while trained engineers manage model building and improvement. It also supports cases where companies prefer outsourcing machine learning instead of hiring large in-house teams.

In situations that require custom machine learning algorithm or advanced neural network work, software development outsourcing models can support the entire process. These partners help businesses stay competitive in a data-focused market and keep their systems up to date with new practices in the field.

Why Do Companies Turn To Machine Learning Outsourcing Services?

The need for strong machine learning skills is higher than ever, yet many companies still struggle to find the right people. A recent McKinsey survey shows that AI growth is changing workforce needs and that machine learning engineers are among the hardest roles to hire. 

These points explain why many teams decide to outsource machine learning services.

• Cost reduction: Companies can work with skilled ML experts without paying the full cost of permanent staff.
• Faster project execution: Ready ML teams can begin work at once, which shortens delivery time.
• Flexibility and scalability: Teams can grow or shrink when needed so companies do not face long hiring cycles.
• Access to niche expertise: Businesses can reach specialists in areas like transfer learning, NLP, and predictive modeling. This is important when research from Reuters shows that AI spending is set to grow to over USD 550 billion in 2024 while there is still an expected AI talent gap of 50%.
• Reduced hiring burden: Teams avoid the slow and difficult process of searching for advanced ML engineers.

For many companies, forming an internal ML team is not always the best choice. High salaries and long recruitment steps make outside support more practical. Some organizations also need help with machine learning procurement operations outsourcing, especially when their projects have changing demands. In these cases, working with outside machine learning engineers becomes a flexible option that fits both short-term and long-term goals.

Top 10 Partners For Machine Learning Outsourcing

Finding the right partner can shape the success of your machine learning outsourcing plan. We’ve gathered ten trusted companies that deliver strong ML capabilities and real business results.

1. MOR Software

Company size: ~500 employees

Founding year: 2016

Website: https://morsoftware.com/

Headquarters: Ho Chi Minh City, Vietnam, with offices in Hanoi, Da Nang, Tokyo, Osaka, and Nagoya

MOR Software is a global Vietnam software group that works with companies that want reliable support in machine learning outsourcing. Our teams cover machine learning, AI development, and full digital product delivery. With more than 650 engineers across Vietnam and Japan, we help clients in healthcare, finance, retail, manufacturing, HR tech, logistics, and enterprise automation. Our work follows global standards and is backed by ISO 9001 and ISO 27001 to keep delivery stable, secure, and consistent.

Our presence in Ho Chi Minh City, Hanoi, Da Nang, Tokyo, Osaka, and Nagoya helps us stay close to clients in different regions. We mix strong technical skill with clear communication and flexible engagement models. This makes us a trusted long-term option for companies that want to work with experienced machine learning service providers.

We have completed many ML projects, including predictive models, NLP systems, computer vision tools, and cloud-based enterprise AI platforms. Our team supports businesses that need to turn raw information into smart products, improve automation, and run ML systems ready for real use.

One of our projects involved building an NLP spam detection tool for a healthcare review platform in Japan. The client needed a way to spot incorrect or low-quality reviews posted by medical staff. Our team built a custom ML setup, added monitoring tools, and deployed a scalable AWS environment. The system improved data quality and lowered manual review tasks.

Another project involved creating a motion-recognition ML SDK for a Japanese fitness brand. Our engineers trained models to track and count exercise movements through sensor signals, added Bluetooth and USB support, and designed an SDK that outside apps could use without difficulty. This raised accuracy and made the client’s product more engaging.

We also developed a computer vision solution for CCTV management. Our team added object detection, automated event tracking, and video analysis inside a C++ and QT application. This helped the client improve their monitoring processes and modernize security operations.

Key features:

• Full ML development from data work to model training, deployment, monitoring, and long-term support.
• Strong skills in NLP, computer vision, predictive modeling, and enterprise AI outsourcing​ solutions for real business needs.
• Certified development processes under ISO 9001 and ISO 27001 to protect data and keep delivery quality high.
• A proven record of ML projects in healthcare, fitness, finance, manufacturing, and eCommerce for both global companies and fast-growing startups.

2. DevsData

Company size: ~60 employees

Founding year: 2016

Website: https://devsdata.com/

Headquarters: Warsaw, Poland and Brooklyn, NY

DevsData LLC is a software engineering agency known for its work in machine learning and custom product development. The company builds tailored solutions for clients in many fields and keeps a strong focus on reliable delivery and clear client communication.

With more than 100 completed projects for over 80 clients, DevsData brings together senior engineers, contractors, and technical specialists from both the US and Europe. This setup helps them maintain competitive pricing while giving clients access to skilled talent. Their team has supported global companies and growing startups, holding a 5 out of 5 score on Clutch and Goodfirms along with strong public reviews.

A notable project involved creating an AI system for a pharmaceutical company to detect adverse drug reactions through social media data. The solution handled automated extraction and analysis, which improved monitoring speed, lowered operational costs, and gave the client stronger safety insights.

Key features:

• The company holds a 5 out of 5 rating on platforms like Clutch and Goodfirms, with strong testimonials that highlight its positive reputation.
• A clear track record of delivering high-quality machine learning work, with more than 100 completed projects for over 80 clients in different industries.
• Custom machine learning applications designed to match each client’s goals so business needs stay aligned throughout the process.

3. Dirox

Company size: ~130 employees

Founding year: 2003

Website: https://dirox.com/

Headquarters: Paris, France

Dirox Labs delivers a wide range of artificial intelligence outsourcing and machine learning outsourcing services that help companies use big data machine learning more effectively and improve daily operations. With more than twenty years of experience and a team of over 120 members, including consultants, data scientists, ML engineers, and software developers, the company builds tailored solutions for many different industries.

Working with Dirox helps organizations simplify workflows, lower error rates, limit downtime, and create stronger data-based forecasts for better decisions. Their team partners closely with clients to fit AI tools into current systems and deliver predictive models, automation setups, and solutions that raise overall performance.

With teams in Los Angeles, Paris, Saigon, Osaka, and Ottawa, Dirox has the reach needed to support large companies with complex technical demands.

Key features:

• A team of more than 120 specialists that includes consultants, data scientists, ML engineers, and software developers.
• Their solutions support informed, data-driven predictions that improve how companies make decisions.
• Their long experience and custom approach make them a strong match for large organizations that need help with complex AI projects.

4. InoXoft

Company size: ~150 employees

Founding year: 2014

Website: https://inoxoft.com/

Headquarters: Tallinn, Estonia

InoXoft is an international development company that supports both startups and established businesses with a wide range of engineering services, including strong capabilities in machine learning and AI-based service automation. With more than nine years of experience, the company works with clients in the US, Israel, the Netherlands, Norway, and Australia. Its work is shaped by four core values: Realize, Improve, Care, and Be Sharp, which guide daily decisions and team operations.

InoXoft’s machine learning outsourcing services are centered on building modern solutions for advertising and marketing teams. Their specialists help companies use AI to improve ad results and create targeted, engaging content. Through advanced AI as a service, the company helps clients refine campaigns with clear data insights, leading to better accuracy and smoother content delivery. Their focus on consistent quality has made them a trusted partner for organizations that want stronger marketing performance and clear, measurable outcomes.

Key features:

• Delivers targeted ML solutions to improve ad performance, refine content delivery, and raise engagement in marketing and advertising efforts.
• Builds tailored ML applications for ad targeting, customer grouping, and campaign automation based on each client's needs.
• Provides full-cycle AI and machine learning development, from early planning to deployment, to help teams integrate these tools into existing workflows.

5. BlueLabel

Company size: ~45 employees

Founding year: 2011

Website: https://www.bluelabel.ai/

Headquarters: New York, NY

BlueLabel provides machine learning development and generative AI consulting services, with a strong focus on machine learning outsourcing that keeps solutions clear, practical, and effective. Their goal is to create technology that feels approachable while still delivering solid value for business teams.

Their work centers on building easy-to-use applications that help companies raise productivity and simplify daily tasks. BlueLabel aims to make machine learning accessible so organizations of all sizes can apply AI in ways that support real improvement and meaningful outcomes.

The company is a strong choice for startups because it tailors machine learning and generative AI solutions to support smaller teams that need modern tools but may lack internal specialists. Many early-stage businesses want advanced AI but do not have the budget or staff to maintain complicated systems. BlueLabel addresses this need by creating simple, effective tools that fit startup demands.

As a full-service consultancy for generative AI strategy and implementation, BlueLabel works with clients to explore ideas, build prototypes, and deploy AI solutions that match business goals. Their support ranges from product creation to internal process improvement. They use generative AI to help clients unlock new opportunities for higher efficiency and smoother operations. Their experience covers product development and business transformation, helping companies integrate advanced AI into their workflows without friction.

Key features:

• Builds AI-powered applications that balance advanced capabilities with clear, simple design to support productivity and smoother operations.
• Uses machine learning models to strengthen data analysis so companies can make better strategic decisions.
• Focuses on intuitive, user-friendly AI tools that simplify complex tasks and support stronger operational performance for businesses of many sizes.

6. Sigmoidal

Company size: ~20 employees

Founding year: 2016

Website: https://sigmoidal.io/

Headquarters: São José dos Campos, Brazil

Sigmoidal is a reliable partner for companies that want to apply machine learning in practical ways. The team focuses on building ML solutions that help organizations adopt advanced technology and improve everyday operations. With a globally connected group of data scientists and consultants, Sigmoidal guides clients in choosing the right ML strategies that fit their real needs.

Their dedicated developers work with modern machine learning SDKs to build custom ML-driven applications that support better business performance. They use a proof-of-concept approach so clients can see real results early, which helps reduce risk and supports smoother adoption of machine learning outsourcing projects.

Key features:

• Skilled in using the latest machine learning SDKs to create modern applications that improve business processes.
• Focused on designing custom AI solutions that raise business performance and support stronger operational results.
• Uses a proof-of-concept model that helps clients measure early outcomes before moving to a larger rollout.

7. Relevant Software

Company size: ~80 employees

Founding year: 2013

Website: https://relevant.software/

Headquarters: Lviv, Ukraine

Relevant is an international outsourcing company that delivers high-quality digital products for Fortune 500 companies and fast-growing startups. With a global team of skilled engineers, Relevant blends strong technical knowledge with worldwide collaboration to create custom solutions for many industries.

The company provides machine learning and AI development services that help organizations build ML-driven applications and improve how they handle data. Their approach supports better value extraction from business information while keeping costs under control. Along with technical work, Relevant offers strategic direction and long-term support, helping clients achieve results that last.

Clear communication is a core part of their service. Relevant uses refined workflows that keep every project transparent and collaborative so businesses receive solutions that match their goals.

Key features:

• Creates flexible ML-powered applications that scale as companies grow, even when data volumes rise or technology needs change.
• Plans and manages resources wisely to balance new ideas with cost-effective delivery that supports strong business outcomes.
• Provides a smooth development journey from early planning to deployment and continuous support so solutions stay reliable and adaptable over time.

8. Eminenture

Company size: ~290 employees

Founding year: 2011

Website: http://www.eminenture.com/

Headquarters: New Delhi, India

Eminenture PLC is a multinational company based in India that focuses on research services, business process outsourcing, data management, online marketing, and technology solutions. The company supports clients across the United States, the United Kingdom, Europe, the Middle East, and the Asia-Pacific region. Eminenture builds custom solutions that help businesses strengthen operations and reach their goals across different sectors.

A key part of their work is their machine learning services, which help turn raw data into clear insights for better decision-making. Using advanced algorithms and AI automation tools, Eminenture enables companies to automate tasks, forecast trends, and increase efficiency. Their capabilities cover predictive analytics, natural language processing, and computer vision, giving clients strong support when applying machine learning outsourcing for real business needs.

Their ML solutions bring strong value to industries like eCommerce, healthcare, finance, and customer service, where accuracy and flexibility matter most. Through scalable models that fit each company’s requirements, Eminenture helps organizations adopt data-focused strategies and stay competitive in fast-changing markets.

Key features:

• Improves customer communication and information extraction through advanced language understanding, suitable for chatbots, sentiment analysis, and content sorting.
• Delivers flexible and scalable ML models that match specific business needs so solutions stay relevant and effective.
• Uses computer vision methods to process and analyze visual data, supporting areas like quality control, security, and media.

9. MindTitan

MindTitan Website Screenshot

Company size: ~50 employees

Founding year: 2016

Website: https://mindtitan.com/

Headquarters: Tallinn, Estonia

MindTitan is a focused machine learning and AI development company that helps enterprises turn difficult data problems into scalable solutions ready for real use. With strong experience in applied data science, the team works closely with government groups, telecom companies, fintech organizations, and large enterprises that need advanced ML systems.

MindTitan’s engineers and data scientists create custom models for forecasting, automation, fraud detection, NLP, and operational intelligence. Their strength in careful model refinement and full AI lifecycle management ensures clients receive high-performing solutions along with ongoing updates and long-term support.

The company’s past work includes national AI programs, smart automation setups, and enterprise-level ML deployments that demand reliability, safety, and stable performance.

Key features:

• Builds large predictive and automation systems for enterprises in telecom, finance, and public sectors.
• Provides full ML development services that cover data strategy, model building, deployment, and long-term support.
• Strong skills in NLP, forecasting, anomaly detection, and intelligent automation designed for complex organizational needs.

10. MobiDev

MobiDev Website Screenshot

Company size: ~350 employees

Founding year: 2009

Website: https://mobidev.biz/

Headquarters: Atlanta, Georgia

MobiDev is a full-cycle software development company that brings machine learning into real business products. With more than ten years of experience, the team helps organizations improve their platforms through embedded AI, predictive workforce analytics, computer vision tools, and smart automation features. Their solutions support companies that want practical, reliable results from machine learning outsourcing.

Their ML engineers create models that fit smoothly into mobile applications, enterprise platforms, IoT hardware, and cloud systems. MobiDev focuses on stability, clear workflows, and scalable design, making the company a strong option for teams that need AI functions added to current systems without disrupting existing operations.

MobiDev works with startups and global organizations across healthcare, retail, manufacturing, and cybersecurity. They deliver ML solutions that balance technical strength with easy user experience, ensuring that each product feels useful and natural for its intended audience.

Key features:

• Combines ML engineering with strong software development skills to support smooth system integration.
• Experienced in applied AI for mobile, IoT, and enterprise environments with a focus on computer vision, forecasting, and anomaly detection.
• Builds high-quality ML features that improve existing products without requiring complete system replacements.

What Machine Learning Services Can Be Outsourced?

There is no single method for machine learning outsourcing. Companies can hand off specific ML tasks, fill short-term skill gaps, or outsource entire projects when they need broader support. Each option gives you the flexibility to match outside help with your real business needs.

This level of choice lets you stay in control of key decisions while bringing in specialists for more complex or time-consuming work.

These are the ML services that organizations often outsource, either as individual requests or as part of a larger AI initiative:

• Data labeling and preprocessing: ML models need clean and accurate data. Tasks like cleaning, annotating, and structuring datasets take a lot of time. Outsourcing provides well-prepared data without shifting internal teams away from important responsibilities. This is also where services like AI data annotation outsourcing bring strong value.
• Predictive analytics: Companies use ML to forecast customer behavior, market changes, and future risks. Outside experts can improve these models so businesses receive faster insights and clearer forecasts without hiring a full in-house team.
• Computer vision: Self-checkout tools, medical imaging systems, and quality control tools rely heavily on computer vision. Building these models requires large datasets and deep technical skill, which makes external support a cost-friendly and efficient option.
• Natural Language Processing (NLP): Chatbots, voice interfaces, and sentiment tools rely on NLP. These systems need experts in language and data science. Outsourcing helps companies gain advanced natural language processing tools without maintaining their own research teams.
• Custom AI model development: Some projects require unique ML models and strong computational power. Outsourcing allows companies to build these tailored solutions without investing in costly hardware or large internal data science groups.

If you want to outsource machine learning tasks or larger AI development work, partnering with a full-service team can make the entire process simpler and more organized.

There is also another option.

You can bring in extra support with contract engineers or hire specialists offshore. Many companies choose to outsource machine learning engineer roles because it provides lower costs and keeps direct control over their ML roadmap.

The partners listed in the above section include both types of support, from full-service outsourcing firms to groups that help you recruit skilled ML professionals for your own internal team.

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How To Choose The Best Provider For Machine Learning Outsourcing?

When many options are available, choosing the right partner becomes a real challenge. If you plan to move forward with machine learning outsourcing, you need a clear view of who the potential partners are, the services they provide, their reputation, and whether they can deliver the results you expect.

Review Their Portfolio And ML Experience

Your first step is to reduce your list of possible partners using trusted rating sites like Clutch. Filter vendors based on their AI and ML skills as well as their scores. This helps you narrow your search to companies with proven ability instead of reviewing hundreds of options.

After you have a small group of strong candidates, look closely at their past AI and machine learning projects. Make sure each vendor has real experience handling ML work that matches your needs. This is also the stage where some teams decide whether they should outsource machine learning engineer roles to fill specific skill gaps.

Work With Midsize Or Large Teams

The scope of an ML project can shift over time. You may add new features or expand the system once you see early results. When the scope grows, the team often needs to grow as well, so it is important to work with a vendor that has a large enough talent pool to support those changes.

Smaller companies can make scaling difficult and slow because their resources are limited. Vendors with more than 250 specialists, however, can increase team size much faster. With a broader talent base, these partners can support your machine learning outsourcing needs and adjust the team whenever your project requires extra capacity.

Look For End To End Development Capabilities

Some vendors only handle a few parts of the development process. Others can manage the entire journey, starting from the first idea and continuing all the way to the market launch. Choosing a full-cycle partner is often easier because one team handles every stage of the work.

A full-cycle approach to machine learning outsourcing keeps all project activities in one place. This improves communication, lowers extra administrative tasks, and helps you control costs more effectively. It also provides smoother coordination between teams and clearer progress tracking. A strong partner can also support ensuring quality in outsourced machine learning models, which is important when you rely on outside specialists.

These partners also include long-term care after delivery. Support and maintenance help keep your ML product stable and ready for real use over time. Many companies also choose to hire machine learning engineers through these vendors when they need extra talent for future updates or new features.

Validate Security And Compliance Standards

When you work with an outsourcing partner, you will need to share certain sensitive business details. This makes security a top priority. Your vendor should follow strict industry standards such as PCI DSS and ISO 27001 so your information stays protected at all times.

A reliable partner will have clear security practices, controlled access to data, and strong compliance policies. This ensures your sensitive information remains safe throughout the entire project.

Conclusion

Choosing the right machine learning outsourcing partner can help your business move faster, reduce risks, and turn complex data into real results. You can work with full-service teams or specialists who support targeted ML tasks, from predictive models to NLP and computer vision. The key is finding a partner who understands your goals and can grow with your needs. If you want expert support for your next ML project, contact MOR Software and start planning your solution today.