Enterprise AI Platform
We design and build a custom-made AI Platform that best fit your data and use cases








DataOps
End-to-end DataOps life cycle

Data Integration and Ingestion
Connect your data fathom AI Platform can easily access a wide variety of data connectors (Built-in connectors, cloud, on-prem, modern and legacy systems and public APIs to build custom connectors

Data Preparation and Enrichment
Extract, transform, load (ETL) for Batch and streaming data low-code no-code ETL framework to create repeatable data transformation pipelines
Data Lineage/Data Versioning Supports Data Lineage/Data Versioning for data governance best practices specifically designed to successfully manage and deliver AI projects at scale
Data labeling and Annotation Supports Videos, Images, Text,Audio and Time series collaborative labeling and annotation for machine learning
GPU-Accelerated Supports GPU-acceleration for ultra-fast data processing speed

Exploratory Data Analysis and Visualization
The platform offers low-code and no-code Exploratory Data Analysis
Understand your data
Discover patterns
Investigate your data
Spot anomalies
Analyze and summarize your data
A Fully Executed Digital Strategy
The platform offers low-code and no-code Exploratory Data Analysis
Uncover the insights hiding in your high-dimensional data
Analyze, and visualize your data with speed, power, and flexibility Visualize your data quickly, easily, and beautifully
Flexible tools for representing geospatial, time series, and connected data
MLOps
End-to-end MLOps life cycle
Feature Engineering and Store
Our platform help Data Engineers with the process of Feature Engineering raw data including
Feature extraction
Feature selection
Feature construction
Automated feature engineering
Feature Reuse Across Organization
Feature Store lets teams organize the features in such a way that it can be reused in many projects
Streamline Model Training and Serving
Use the same feature definitions for training and serving. Feature Store is the fastest path to operationalizing analytic data for model training and online inference
Model Training
- No code environment to build Machine Learning workflows
Visual Programming Environment to make AI development more accessible (One visual environment to build, train, validate, and deploy models)
- Rich component library
AI Lab provides a comprehensive ecosystem of popular AI packages, Includes machine learning and deep learning (200+ algorithms). Includes supervised and unsupervised learning. Includes classification, regression, anomalies, time-series prediction and clustering algorithm
- Combine workflow with validation logic
Organize your workflow with ready-made components. Our unique framework lets you also control how the workflow is validated
- Customizable components
Control every aspect of your workflow, including specialized components for common industrial problems like predictive maintenance, anomaly detection, etc
Model Interpretation and Deployment
- Explainable AI (XAI) in low-code & no-code Visual environment
Interpret your machine learning and deep learning models via low-code & no-code environment. Investigate and explain the behaviour of trained your models in a visual way
- Accelerate your ML models into production
Deploy your trained models to production with a single click
Model Monitoring
Monitor your machine learning and deep learning models in Production via low-code & no-code environment
Ensure your model is performing well on the new data in production
Detect input changes in feature distribution (Data Drift)
Detect output changes in target and feature behavior (Target Drift)
Model Governance
Analyzes your model performance
Evaluate Model quality
Identify and prevent potential model risks
Engagement Process

Platform Services
Performance
Throughput, Latency, Capacity. · 28 million non-persistent and 6 million persistent messages/second per appliance· 1.75 million non-persistent and 235,000 persistent messages/second per software broker
Up to 200,000 concurrent IoT connections per device
Availability & Maintainability
Recovery process, mitigation plan, notifications of failure occurs
Recording all failures in a persisted environment (data must be relevant to the user and the support engineer, logging to enable timeline analysis and tracing of errors. Ability to snapshot the system state at failure so the condition is replayed in a dev. Environment, compliance with standards, best practices, reference architectures etc. Up to date documentation (including architecture diagrams, interfaces, coding guidelines etc), Technical debt management, System health check monitoring inc. smoke tests that the application runs correctly
Portability
Accessible via APIs for the most popular programming languages, and supports all of the latest open APIs and protocols so you can take a best-in-class approach to application development, avoid the hassle of protocol translation, and stay free of technology lock-in. Messaging APIs are available for C, C++, C#/.NET, Java, JavaScript, JMS/JCA, and Node.js
Scalability & Reusability
Number of users, Amount of data, CPU, Memory, I/O intensive operations, Concurrency, Asynchronous, Statelessness, Long running operations (batch scheduling on non-peak times)
Openness & Extensibility
High cohesion and low coupling, SOLID principles, modularize the user interface so different modules can become available with minimum impact, abstractions to design those system boundaries that are likely to be susceptible to change, pluggable architecture , make use of workflow engines with dynamic rules, expose functionality from layers, subsystems and modules through APIs, one-click deployment to allow for quick time to market, high test coverage to prove there are no side effects
Interoperability
Accessible via APIs for the most popular programming languages, and supports all of the latest open APIs and protocols so you can take a best-in-class approach to application development, avoid the hassle of protocol translation, and stay free of technology lock-in. Messaging APIs are available for C, C++, C#/.NET, Java, JavaScript, JMS/JCA, and Node.js
Cloud Native Architecture
Deployment Architecture, Application Host, How Is Application Isolation Organized, High Availability, Disaster Recovery, Auto-Recovery & Auto-Healing. a fully managed service that meet your exact needs in mere minutes, and scale on demand to any level
Available in public and virtual private cloud environments from Amazon Web Services, Google Cloud Platform, Microsoft Azure and Huawei and aliBaba Cloud. Managed “Ops” takes care of set-up, hosting, maintenance, upgrades, security and scaling of the messaging infrastructure. Web console, dedicated learning center and a REST API for CI/CD integration make it easy to manage
Runtime Architecture
Implement Stateless Architecture
Cloud Compatibility
Precocity was built to be deployed in the cloud. All Fathom applications are able to be deployed in Software As A Service environment due to Precocity. Precocity provides all the details for deploying a service in the cloud. It provides payment functionality, security functionality, authorization functionality and registration. User is able to register and start using any of the applications and Precocity handle the monthly subscription
Notifications
Any system has to have a way to notify the user. Fathom Precocity is no different. Configured alarms and events will notify the user once they have been triggered. Notifications will be through SMS, email, and/or badges on the screen
Audit Trail
Audit trail is an important information that provides detailed uses of Precocity. It provides detailed information to track problems. It also provides logs to track who has modified the system
Security
Precocity has a comprehensive security model. Because of the cloud nature of Fathom applications, security plays a big role in Precocity. It provides user registration. It confirms user’s email. It does not allow login bots to take control of the system. It allows two factor authentication and with its authorization technology, it limits the user from accessing data and/or functionality that has been disabled
Enterprise Architecture Development
Build the software diagram model that specifies how the software system should work earlier than the code development of the software. After approval and testing, it will be deployed
A complete event streaming and management platform for the event-driven enterprise
Events Provisioning (Deployment & Operations) and Monitoring (Alerts and dashboards)It helps enterprises design, deploy and manage event-driven architectures across hybrid cloud, multi-cloud and IoT environments, so they can be more integrated and event-driven
Microservices, Containers & Deployment Standardization
Efficiently streams events and information across cloud, on-premises and IoT environments. It supports a wide range of message exchange patterns including publish/subscribe, request/reply, streaming and replay, and qualities of service such as best effort and guaranteed delivery