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Machine Learning Services to Drive Productivity

Jumpstart your investment in machine learning by partnering with us to manage, deploy, secure every workflow, and tune modern ML models.

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Build and scale machine learning models with SHALIGRAM’s enterprise machine learning services

Machine Learning (ML) technology is an integral part of every business today. It is advancing so fast that businesses no longer debate whether to invest in it.  SHALIGRAM helps businesses across the globe integrate ML solutions for a range of operational and analytical tasks. 

Worldwide, machine learning adoption is accelerating. The global ML market is expected to reach $122.03 billion by 2035. Digital transformation and data explosion are driving demand for machine learning services. Both SMBs and large enterprises are investing in ML development services to enhance productivity and be future-ready.

Business challenges we address with our machine learning services

Limitations in scalability

Business bottlenecks, data silos, outdated systems, communication breakdowns, etc., limit a business's ability to scale.

Limitations in adaptability

Without forecasting and proactive capabilities, businesses fail to adapt to changing market conditions, demand, and shifts in customer preferences.

Lack of data structure

Data silos and low data reliability result in unstructured and disconnected operations.

Lack of business intelligence

With fragile logic, decisions are based on guesses and misguided choices.

Poor customer service

Customer service relying on manual inputs is difficult to manage, corelate, and resolve, which often results in poor service and support.

Competitive disadvantage

Without predictive capabilities, businesses will often fight to survive.

Explore our ecosystem of machine learning development services

Machine learning development

Machine learning development

Our machine learning development process involves end-to-end building and deployment of ML services. This includes everything from collecting data, training models, testing, and integrating them with your existing business operations. By professionally balancing model accuracy and business constraints, our development team finalizes the model architecture that supports measurable outcomes.
Machine learning consulting

Machine learning consulting

Startups and enterprises looking to innovate and grow with machine learning models should first discuss the possibilities, challenges, pitfalls, costs, and other considerations in detail before starting the development process. SHALIGRAM undertakes a comprehensive assessment of your current business and guides you through the entire process to formulate ML strategies tailored to your business goals and project requirements.
Recommendation engine development

Recommendation engine development

As a leading ML recommendation engine development company, SHALIGRAM offers a wide range of custom recommendation systems for content, search, product, visual search, social media, and more, delivering relevant suggestions to users, thereby boosting conversions, engagement, and retention through data-driven insights and personalization.
MLops model deployment

MLOps & model deployment

For businesses seeking the complete potential of Machine Learning services, our MLOps and model deployment offers an efficient path forward. Here, we combine machine learning, model deployment, data engineering, model optimizing, and model monitoring as a complete service.
Machine learning integration services

Machine learning integration services

Connecting trained machine learning models into existing business workflows is challenging, but reputable ML service providers like SHALIGRAM can help. Our enterprise ML integration services ensure that the model output performs at its maximum capacity in real-time business infrastructure.
Machine learning maintenance support

Machine learning maintenance & support

Machine learning models need to be continuously monitored, retrained, and detected for drift to achieve maximum performance and the desired outcome. Businesses that need models to perform at their best in context should opt for ML maintenance and support services.
ML model optimization

ML model optimization

To achieve maximum performance and the desired outcome, machine learning models need to be tuned and refined periodically. Optimized models deliver contextually relevant results. This process also helps find the optimal model capacity. At SHALIGRAM, we offer ML model optimization services with utmost diligence and expertise to adjust the model parameters.

Our numbers reflect our commitment

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Our modern machine learning solutions

Predictive analytics solutions

If you want to engage with your customers more effectively, predictive analytics solutions are the right choice for you. These solutions are built using machine learning, statistical modeling, and data mining processes. Predictive analytics enables businesses to forecast trends and make proactive business decisions.

Predictive analytics solution

Our Partnership with leading cloud machine learning services platforms

AWS

Our Machine Learning services with AWS enable us to combine our ML expertise with the power of AWS to build, deploy, and scale intelligent machine learning solutions. Using services such as Amazon SageMaker, AWS AI Services, and AWS analytics tools, we help businesses with custom ML models.

Modern ML Systems tailored for diverse industries

Our custom machine learning services are engineered to address the specific operational and analytical challenges of your industry. We focus on transforming complex data into actionable insights, optimizing core processes, and deploying scalable ML models right where they deliver maximum business value.

We design AI-powered ML systems to optimize routes, identify demands, patterns, and storage limitations. Our developers seamlessly integrate ML models into your existing system, ensuring minimal disruption.

  • Demand forecast
  • Automated inventory management
  • Dynamic warehouse operation
  • Integrated data
  • Reduced cost

Recent projects & case studies

From startups to enterprises – see how our expertise in software consulting and development in the USA has led to measurable impact across industries.

Transfer Connex

Custom CRM with live FX rates, telecoms & sales intelligence

Transfer Connex is a UK-based financial services/FinTech company that helps businesses manage international payments, foreign exchange (FX), multi-currency accounts, and business funding. 

Industry
Fintech
Technologies
.Net
Challenges
  • Limitations of off-the-shelf CRMs
  • Fragmented system operations
  • Manual data overhead
  • Lack of call-to-CRM linkage
Business impact
  • Improved call-to-CRM linkage
  • High-volume transaction capacity
  • Accelerated deal execution
  • Real-time leadership insights
View case study

ML model development processes at SHALIGRAM

01

Identify business objectives

This is the first step towards a strategic Machine learning service deployment. Here, our development team identifies business goals, evaluates technical requirements, and determines the feasibility of the machine learning initiative.
02

Data collection and preparation

Once we assess feasibility, the development process begins by gathering and structuring high-quality data to build a reliable foundation for model development.
03

ML feature engineering

By strategically constructing the algorithms, raw data is transformed into meaningful features. Our ML development engineers then select the most relevant variables to improve model performance.
04

ML model architecture design

The Machine Learning design and development team at SHALIGRAM identifies the most suitable machine learning algorithms to construct a model architecture aligned with the project requirements and business goals.
05

ML model training and validation

The ML models are then trained using the datasets, and we validate their performance to ensure accuracy and customization.
06

ML model testing

Once the ML model is validated, our development experts test it using relevant performance metrics and conduct rigorous testing to verify reliability and effectiveness.
07

ML deployment and integration

When the ML models pass the testing phase, they are ready to deploy. Our ML experts ensure a seamless integration of these models into existing applications and business systems.
08

Monitoring and optimization

Any custom Machine Learning development and deployment is successful only when it is continuously monitored and optimized. We at SHALIGRAM follow the same strategy by periodically monitoring the model performance to maintain accuracy and the desired outcome.

Unlock the business outcomes of machine learning

ML approach

Due to our consulting-first approach, implement scalable ML models and have a competitive advantage of delivering services with the ML approach.

Operate with confidence

With the full potential of Machine Learning technology, confidently conduct your business throughout the journey.

Future focused

With strategic foresight, balance today's demands and tomorrow's goals, integrating our ML development services.

Risk mitigation

By easily detecting fraud, and proactively managing security attacks, prevent risks before they even arise.

Personalized customer experience

Customized product recommendations, smart inventories, automated workflows, demand forecasting, and intelligent ticket routing result in exceptional customer experiences.

Cost efficiency

Automated workflows, reduced manual errors, structured data, and real-time business intelligence result in lower wastage, resources, and cost.

Why choose SHALIGRAM for machine learning services?

Salesforce migration visualization

Choose SHALIGRAM as your ML partner

By combining our decade-long experience, ML expertise, and industry knowledge, we deliver next-generation Machine Learning services and solutions that create measurable business value.

  • Consulting-first approach
  • Deliver maximum value
  • Powering what’s next
  • Approachable and transparent
  • Experience and expertise

Ready to start with machine learning services?

Try SHALIGRAM's ML services designed for every business size and type.

FAQs

Frequently asked questions about our machine learning services and solutions.

SHALIGRAM uses a combination of model quality metrics that include accuracy, precision, recall, F1 score, Root Mean Squared Error (RMSE), AUC (area under the receiver operating characteristic curve), mean squared error, and operational metrics like latency, uptime, drift, etc., to evaluate the deployed ML models comprehensively.