Data is the new Oil and AI is the greatest innovation mankind has seen after electricity.

— Maleotech is committed to reduce the cost of accurate prediction.

During our interactions with customers we observed that, earlier implementation of ML systems have faced with multiple issues. Some of the common issues are: not having enough knowledge about the capability of AI system across the management chain, not having enough data, requiring an expert team to label data, not having enough expertize in identifying all possible features, all data is in different systems thereby requiring to integrate the data. So a project on building a ML system was taking more than 90% of time to understand, and gather the data. Merely a 10% of the time is spent to model and train the system. And any change in feature or environment requires to follow same process again and again.

With the current dynamism in business world, calculating static features doesnt solve the purpose.

Thus from the begining Maleotech is focused and invested significantly on RL based systems. RL based systems gather the training information by evaluating the action taken. This evaluative feedback machanism proved significant in adding business value faster, more accurate, and adaptive to the changes in business environment. Maleotech has a strong team of RL engineers. We build algorithms for your business needs.

Industries which are reaping benefits using Maleotech’s RL systems are:

  • Retail
  • Healthcare
  • Banking
  • Manufacturing
  • Real Estate
  • Aerospace
  • Defence

Areas where Maleotech’s Industrial AI helped its clients achieve value:

  • Optiming Pricing Strategy for product using Re-Inforcement Learning
  • Q-Learning based optimum Route determination
  • Qality Management
  • Sales Forecasting
  • Condition Based Monitoring of Machines
  • Computer Vision – Image and Video classification
  • Language Processing
  • Recommendation Systems

How Maleotech is helping its clients take the first step into AI world:

  • Build Value Add Detailed Project Reports(DPR)
  • Dedicated workshops for leadership team to gain confidence on AI investments
  • Conduct strategic AI training for the leadership team
  • Outcome based pricing – Risk is Maleotech’s, pay only when you achieve results

If you would like to hear from Maleotech team, please reach out to us at

Artificial Intelligence(AI) is borrowing characteristics from human intelligence, and applying them as algorithms in a computer friendly way to find solutions to complex problems. AI makes it possible for machines to learn from data, adjust to new inputs and perform tasks such as recognizing speech, identifying images and making predictions.

AI has proved its value in various verticals such as cyber sccurity, face recognition, data analysis, logistics, markting & advertising etc. Popular uses today include:

Computer Vision and Image Recognition:
Maleotech’s CV based classification algorithm is used by industry to quality gradation of products. The product uses end-to-end deployment process, from image capturing(Hardware, Software and Integration) -> Classification(Algorithm) -> Conveyor belt(Downstreamprocess). So that only QA passed products are fed onto the down stream processes, thereby reducing the cost of down stream processing of defective products.

Our re-inforcement learning based product, uses online and offline learning method for improving the classification and matures over time. With this approach AFPD(available for production deployment) time is reduced and customer sees the results instantly.

Q-Learning Based Optimization:

Maleotech’s Q-Learning based optimization algorithm is used by industries to optimize the route, maximize the product pricing to market.

Speech Recognition
Both the business and academic worlds have embraced deep learning for speech recognition. Many organizations are employing deep learning technologies in their systems to recognize human speech and voice patterns. The common way to recognize speech is – we take a waveform, split it at utterances by silences and then try to recognize what is being said in each utterance. To do that, we want to take all possible combination of words and try to match them with the audio. We choose the best matching combination.

According to the speech structure, three models are used in speech recognition to do the match:

  • Acoustic Model contains acoustic properties for each senone.
  • Phonetic Dictionary contains a mapping from words to phones.
  • Language Model is used to restrict word search.

These three entities are combined together in an engine to recognize speech.

Natural Language Processing:
Neural networks, a central component of deep learning, have been used to process and analyze written text for many years. A specialization of text mining, this technique can be used to discover patterns in customer complaints, physician notes or news reports, to name a few.

Recommendation Systems:
Amazon and Netflix have pioneered the use of recommendation systems. Retails industry had reported a 26% increase in sales by deploying AI based recommendation systems. Deep learning is used to enhance recommendations in complex environments such as music interests and clothing preferences.