Data Analytics, AI and ML Solutions

Data Analytics – Power to Solve Real Business Problems

Our data & analytics expertise helps organizations solve real business problems. We deliver business value to software companies trying to infuse data science within products, and to enterprises attempting to uncover data-driven decisions. Our deep technology expertise across the complete data analytics process, multi-disciplinary teams and unique solution-based approach make us a preferred technology partner of choice for data analytics Services

Our Data Analytics based Solutions Approach

We believe the real power of data is appreciated when we move from data to insights to decisions and actions. Our solutions-based approach helps us focus on the problem we are trying to solve. The solution could be simple descriptive analytics where we present the data in an “easy to consume” format, or we could move a step further and add more intelligence through diagnostic, predictive or prescriptive capabilities built-in machines with automation. We find the best fit solution to the problem using underlying data, cloud and analytics technologies, and help organizations craft strategies that yield results.

Our Data Analytics Approach
GS Lab’s Data Science Approach

Data Analytics, AI and ML Services

Our data analytics, AI and ML services span across the complete data science process. Right from data acquisition to decision and automation, our services help organizations remove the technology and talent-barrier for our clients

Our Data Science consultants help you across the complete data science process. Right from data ingestion, processing, feature engineering, data visualization and Machine learning models. We help you set up your complete data engineering needed for the same. We also help you identify the right skills sets you need for your data science teams. We help you choose the right tools and techniques and provide guidance at each stage to get you going.
Data Architecture
Ensuring the data architecture is in place to support the business, involves end-end view from data acquisition, processing pipelines, ML models to model deployment and monitoring in production. Also, data governance aspects including auditing, lineage, and regulatory compliances need to be incorporated. Often tradeoffs are needed between the ease of adhoc data access that a data scientist needs vs governance. We can help identify and resolve these architectural issues in an evolutionary manner to improve the efficiency of operationalizing the data science team’s work.

Data Engineering
Our data engineering services help you manage Big Data with high throughput and low latency. We have a broad know-how of IT tools and techniques, including warehouses, NoSQL, stream-processing and distributed computing systems to help store and analyze data most efficiently and cost-effectively. We also work closely with our resident IoT experts to extract data from machines atop various protocols.
Our machine learning expertise include supervised, unsupervised, and deep learning capabilities. We understand practical issues in implementation. We will help you choose the right algorithms & realistic models best suited for your problem. Our inter-disciplinary mix of computer science experts and data scientists can help design and implement new algorithms in those cases where none of the existing libraries suffice.
Our product development experience and data analytics expertise make us an ideal technology partner for your AI and ML powered product development requirements. We help develop ML and AI tools right from scratch or implement off the shelf solutions and reduce the overall time to market for your products.
Putting your models in real life systems is not a simple task. This is where most ML prototypes fail to deliver. Our ML Ops services makes sure the ML models are rolled out smoothly in real life systems and help monitor them over a period of time.
Our data analytics teams have hands-on experience in weaving together complex systems of streaming frameworks, NoSQL data stores, and the Hadoop ecosystem to provide actionable intelligence on your real-time streaming data. Our expertise across Kafka, Spark, Storm, Flink, NoSQL Data stores like Cassandra, MongoDB, Redis, Elasticsearch, modern data stores like Hadoop, AWS S3 helps us process high throughput data and provide actionable intelligence even at sub-second levels.
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We help apply NLP concepts and build high conversational apps, both Voice and text-based, to help improve your customer experience. We have built AI chatbots that cater to various verticals and hence solve specific business problems using bots.
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Our Tools, Functional Expertise, and Techniques Makes Us Unique Multidisciplinary Functional Expertise

Latest at GS Lab

Case Study
25% Reduction In Peak Power Consumption With Predictive Insights

Our data science driven solution enabled a supply chain & logistic leader to make data backed decisions supported by real-time intelligence. Granular insight into energy usage generated online & offline recommendations to optimize storage and mixing of bulk liquids.

Case Study
Harnessing Voice Samples To Diagnose Health Issues Using Data Science

Our next-generation solution enabled a leading platform to diagnose medical conditions using a person’s voice as a biomarker. The ‘discovery time’ for creation of data science models which could screen newer ailments was reduced from months to weeks through automation.

Bridging The Gap Between Data Science And The Production Environment Through Inference Bridge

This eBook takes a look at the various approaches available to seamlessly integrate the modelling and engineering phases of MLOps. It also illustrates our innovative solution called the Inference Bridge which closes this gap for faster end-to-end iterations and greater return on investment..


Inference Bridge – Simplifying MLOps

Our Innovative solution in MLOps which helps bridge the gap between data science and production environment.