Todsys Technologies Private Limited

PRODUCTS

products

products

Applied Artificial Intelligence Platforms for Enterprise

  1. Applied AI Innovation and outcomes
  • Discovery
  • Predictions
  • Justifications
  • Action
  • Learning
  1. Platform- End to End solutions for the Analytics Journey to ROI
  • A comprehensive suite of industry-specific and functional offerings – Applied AI
  • Leading Algorithmic tools, methods and applications
  • Applied AI platforms that leverage infrastructure, applications and support
  1. Framework- Alliances for World Class Solutions
  • Industry specific Applied AI Frame works using the latest and greatest of Algorithms and Open source tools
  • Deep Learning work bench consists of all available open source tools and integration to Industry standard Deep learning tools.
  • Semantic and Knowledge Graph work bench
  • Smart Data Work Bench
  1. Products & Solutions with Experience and Authority
  • Health Care AI
  • Consumer AI – Cross Industry
  • Fin Tech AI

Todsys Applied AI platform – Cross Industry Deep Learning Work Bench

  • Deep Learning Frameworks
  • Supporting Libraries

Todsys Applied AI platform cross Industry Algorithmic work bench


· Adaboot · Classification and Regression Tree · Flexible discriminant analysis

 
· Bayesian Belief network · Conditional Decision Trees · Gaussian Naïve Bayes
· Bayesian Network · Convolutional Neural Network · Gradient boosted regression trees
· Boosting · Cubits · Hierarchical clustering
· Bootstrapped Aggregation · Decision Stump · Hopfield network
· C4.5 · Deep Belief Networks · K – Means
· C5.0 · Deep Boltsmann machine · K – Nearest Neighbor
· Chi – Squared Automatic Interaction Detection · Elastic net · Learning vector quantization
· Least absolute shrinkage and selection operator · Least angle regression · Linear discriment analysis
· Linear regression · Locally estimated scatterplot smoothing · Locally weighted learning
· Logistic regression · M5 · Multidimentsional scaling
· Multinomial naïve bayes · Multivairiate adaptive regression splines · Naïve bayes
· One rule · Ordinary least squares regression · Perception
· Principal component analysis · Principal component regression · Projection pursuit
· Random forest · Sammon mapping · Self-organizing map
· Stacked auto encoders · Stacked generalization · Stepwise regression

Applicability of applied AI – Our Thought Leadership


1.Health Care:

  • Continuous monitoring of post-hospitalization, chronic conditions and elderly care (e.g., Alzheimer’s)
  • Predictive maintenance to reduce down time of hospital equipment (e.g., MRI machine)
  • End-to-end supply chain tracking of body organs and blood to reduce contamination and mismanagement

2.Agriculture:

  • End-to-end supply chain tracking to reduce spoilage
  • Increase production by carefully monitoring external factors (e.g., weather, insects, etc.) and quickly mitigating the issues
  • Predictive maintenance to reduce down time of farming equipment and machineries

3.Environment:

  • Tracking and monitoring of hazardous materials
  • Reduce traffic congestion by monitoring of vehicles and pedestrian levels and optimizing driving and walking routes.
  • Early detection of spillage and environmental contamination (e., oil pipeline leakage)

4.Energy:

  • Reduce the overall production of energy by reducing peak usage through careful monitoring of energy consumption
  • Better forecasting of energy production through continuous monitoring of usage
  • Predictive maintenance to reduce down time of equipment (e.g., turbines, well drills)

The Applied AI that people expect :

Artificial Intelligence that need to learning about and get the best combination of Human Intelligence, Machine Leanring and aware thinking machines using the best of nterconnected devices, contextual data, and central orchestration combine to allow subtle yet rich push services

· Smart buildings · Health & Fitness
· Customer experience · Personal security
· Employee connections · Asset management
· Lighting systems · Energy conservation

Analytics Framework :

Big data analytics is the use of advanced analytic techniques against very large, diverse data sets that include different types such as structured/unstructured and streaming/batch, and different sizes from terabytes to zettabytes.

Need

• Have data quality

• Improved analytical capabilities

• Faster hardware

• Predict market trends and future needs

 

 Outcomes

• Reduced maintenance cost

• Understand patient history

• Discover new sources of revenue

 
Competitive Edge

• Smarter, Leaner organization

• Enables cross-channel conversations

• Better prepared for inevitable future

• Helps identify waste in the system

 

 Solutions

• Physician Performance Management

• Supply Chain Optimization

• Predictive Maintenance

• Operational Analytics

IOT and Analytics Architechture :


  1. Physical Devices – The things in IoT
  2. Connectivity – Communication and procession units
  3. Data element – analysis and transformation
  4. Data accumulation – Storage
  5. Data abstraction – Aggregation and access
  6. Application – reporting, analytics, control
  • Data Visualisation
  • Data analytics
  • Data storage
  • Data integration
  • Data source