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Building data-driven products with Totemx Labs
- In last 4+ years, TotemX labs have engineered and deployed cutting-edge tech in NLP, Computer vision and Data Science.
- We were fortunate to work with many cross-functional startup teams as they contributed with their diverse knowledge-backgrounds and were backed by inspiring leaderships.
- We have been learning the challenges and roadblocks that we conquered, from conceptualizing till productionizing AI.
- We work not to deliver a project, but to solve a problem. Our focus is on building systems and services that are directly integrated in the client's workflow, with core goal of delivering the business value-based decision making tech.
- The key to success is our solid knowhow of the A-to-Z of AI product development cycle. We start strong with data engineering and deliver ever-evolving solutions with MLOps.
A. Know your data
Architecting data pipelines involve data acquisition, data source selection, data analysis and occasionally data synthesis, depending on the business usecase, privacy concerns and the domain.
Our experienced data engineers collaboratively work with your teams to attain best quality inputs. It is the fundamental 80% required for a 99.9999% successful ML pipe and an eventually scalable AI-driven tech business.
Z. Clear progress -> continuous improvement
Post the data pipes are in place and the careful selection of candidate ML models, a clear visibility and explainability of ML models performance is what we ensure.
We specialize in creating automated ML workflows with active learning i.e., continuous model life cycle monitoring and improvement in model performance metrics with new data streaming.
Trusted by
Exciting startups that solve real-world problems with sheer will, commitment and cutting-edge AI with us.






Services
Business goals achieved with clear strategic roadmaps and efficient execution.
Data Engineering, analysis and visualizations
Want to transform your business through Data science? Data engineering is the cornerstone of any data science project. We can help you design, build and scale multi-modal data (numbers-text-multimedia) pipelines as well as generate insightful business analytics.
Machine learning
Not every problem needs to be solved with neural networks. We employ and customise Machine Learning algorithms with keeping domain knowledge and business goals in mind. Essential is reproducability and minimizing hidden costs.
ML Lifecycle Management
Productionizing machine learning models is difficult. We can assist you with streamlining all the components of MLOPs cycle to ensure successful deployment and monitoring of your Machine Learning solution.
Timeseries analysis
World is changing at rapid pace and millions of sequential data points are being recorded. We specialise in making developing such time series data analytics and forecasting solutions.
Natural language processing
NLP is remoulding the ways of communication between humans as well as machines. We are here to enable your organisation be part of this next revolution of communication.
Automated manufacturing Q/C operations with computer vision.
Healthcare, manufacturing, automobile, surveillance, photography are few of the industries from the wide spectrum of CV applications. We employ and deploy SOTA vision solutions be it on web, mobile or edge-devices like on-premise cameras.
Testimonials
100% Job success score. More than 60% of our clients have worked with us for more than 1.5 years on an average.
Portfolio
Our approach and execution is based on working with real-world problems at scale. We have been trusted by startups that are pioneers and first movers. Businesses that are customer-centric and want to deliver value through.
- All
- Environment
- Social good
- Healthcare
- Finance
- Agriculture
- Marketing
- Manufacturing

Machine Learning Methods for Managing Parkinson’s Disease
Using AI for early detection and precision manangament of the untreatable neurological disorder

Collaborative problem solving journey with one of the largest environment tech startups
end-to-end Data science and ML deployment with ensured customer success.

Prototype: For a manufacturing automation startup based in Mexico.
With irregular lighting, misaligned images and small custom datasets. Delivered ready to deploy ML models for accurate and fast product classification, component localization, defect detection, object counting, OCR with computer vision and deep learning.

COVID-19 Care assistant - A goodwill project
A COVID care assistant we created in June-2020, in the early days of the pandemic with data mining and knowledge graphs to create an intelligent and engaging digital assistant.

Spot on Plant disease classification for an african Agriculture startup on edge devices
An early warning system at scale, helping the farmers maximize the harvest yield and minimize the treatment costs.

Predicting stock price movements in the near future with strong confidence intervals, for an Italian Fintech firm.
Implementing cuting edge Neural-net based research papers to achieve actionable results.

Emotion detection: US advertising startup.
Detecting user's engagement levels and sentiment levels live as they consume the content or interact in shared focus group sessions.

Deeper time-series analytics with industry leading flood alert startup in the US
Large datasets ranging to 500,000+ hours were compared and analysed in-depth to improve the Machine Learning algorithms to predict high water tides and flood probabilities alerts.
Contact
Want to discuss more? Great! Let`s connect!
Say goodbye to inefficient in-house workarounds and stopgap solutions that lack visibility.
TotemX enables you and your team to plan the AI transformation of your business step by step.
Who are you going to meet?
- A data science and ML consultant with relevent experience of solving real-world problems in your industry.
- A solutionist who can help you from data to deployment and monitoring afterwards.
Meeting agenda
- Your business objectives and your needs in the realm of data and goals you want to achieve with AI.
- Map your goals into usecases, outline the first steps, define and discuss the techniques that we would employ. No jargons, we start with simple tangible results for all stakeholders.
- Any questions you have specific to your data, infrastructure, or use case.