Eureka AI platform
The Eureka AI platform powers all SymphonyAI applications, seamlessly integrating generative and predictive capabilities. Eureka enables the rapid creation of tailored AI solutions and intelligent copilots for every industry, setting a new standard in enterprise AI.
Eureka AI architecture
The best AI platform in the industry
The Eureka Gen AI platform is the foundation of SymphonyAI applications, with a generative AI framework to deliver copilots and AI applications fast, state-of-the-art ML for large scale AI model training and serving a lakehouse architecture for petabyte scale data management and governance.
Centralized UI/UX design system standardizes usability and user experience across the portfolio, with natural language-based interaction.
State-of-the-art data infrastructure
– Lakehouse architecture
– Enables petabyte scale data management and governance
– Single source of data for ML
Generative AI skills and agents framework
– Enables verticals to rapidly build LLM powered copilots and AI apps
– Pluggable skills and agents
– LLM-based orchestration
State-of-the-art ML infrastructure
– Large scale generative and predictive AI model training
– Fast inference capabilities
– Vertical specific LLMs
Common UI/UX framework
– Centralized design system
– Standardizes usability and product experience across verticals
– Natural language-based interaction
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100
Data engineers, ML engineers, data scientists
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3 years
Platform development
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30+
Patents
SymphonyAI CTO Raj Shukla on the Eureka AI platform
Critical AI capabilities
Employ predictive + generative AI
Interact with AI copilots customized for each business user.
Understand challenges and opportunities to plan for what’s next with consolidated insights fueled by predictive and descriptive AI models.
Benefit from dynamic UX
Ensure teams and users can work quickly and efficiently with low code and natural language interfaces. Help workers make effective decisions and power productivity with elegant integrations seamlessly built into your existing tools.
Effective AI lifecycle management
Optimize ML lifecycles for vertical applications and tasks with all the tools, APIs, and SDKs needed for data exploration, feature engineering, model building, experimentation, and deployment.
Enrich lakehouse architecture and data
Equip data scientists and business users with access to secure structured and unstructured data, at scale, that’s required for AI pipelines and applications in production environments.
Built with vertical LLMs
Get relevant contextualization for user queries with refined vertical and task-specific LLMs for each industry and individual use case.
Access relevant data and ensure security
Cloud scale and security
Ensure data security at rest and on the network with native support for cloud, hybrid, or on-prem operations and seamless integration with Microsoft Azure, AWS, and Google Cloud platforms.
Data connectors
Easily access all relevant data sources and formats across retail, CPG, financial services, manufacturing, media, and ITSM with industry-specific data connectors.
Precise deployment
The Eureka ML platform supports the most popular ML frameworks and libraries and a python SDK to help ML engineers and data scientists quickly fine-tune, train, deploy and monitor models as needed. The platform runs training and inference loads, using both CPUs and GPUs as needed. The platform’s purpose-built MLOps tools manage ML algorithms and models, so applications are as accurate and powerful as the day they went live, and learn over time.
Automatic feedback
Built-in tools help tune ML models to make sure they are operating within set constraints
Dynamic learning
Use historical data or fresh, real-time data to unearth new elements that should be incorporated
Predictive and generative AI capabilities
Generative AI and LLM ops
Gain industry knowledge
Enable a deeper understanding of industry concepts, metrics, and terminology with LLMs fine-tuned on proprietary data and industry knowledge graphs.
Inform content generation and reporting
Better understand the who, what, and why behind industry-specific trends to generate summaries, reports, and charts that are customized and impactful.
Improve reasoning and logical deduction
Leverage industry knowledge graphs and training data to craft informative and specific personas. Improve predictions and decisions with a thorough understanding of cause-and-effect relationships.
Power action with tool invocation
Simplify reasoning and fuel action by interacting with API-driven first-party insights and external market data, services, and tools.
Enhance enterprise security and privacy
No data leaves compliance boundaries. LLMs deployed in compliant sandboxes. No data used to train models.
Authenticate enterprise access control
Ensure access is controlled with authentication protections built at data and API layers, and confirming data doesn’t reach LLMs without permission.
Ground decisions in data and facts
Increase the credibility of answers by invoking the right predictive models, which are grounded in data and facts, and not relying on generic LLM knowledge.
Secure and encourage collaboration
Increase the safety and security of collaboration and reporting by utilizing built-in authentication, which is shareable at the level of every insight.
ML pipelines
Guide machine learning workflows
Improve data preparation, model building, training, experimentation, validation and serving for inference.
Enhance training, batch, and real-time inference
Easily build on flexible model training capabilities and deployment of ML models for batch or real-time high-volume transactions.
Develop feature engineering and storage
Successfully build, store, share, and reuse curated features across machine learning pipelines.
Support leading ML frameworks
Effectively operate all the latest frameworks—TensorFlow, scikit-learn, PyTorch, Keras, Apache MXNet, Huggingface, Spark ML, Torch, and more.
Enable SDK and REST API automation
Efficiently optimize processes by using SDK to automate data ingestion, building, training, and model deployment.
Ease explainability
Improve visibility and transparency to help teams understand the reasoning behind model predictions and recommendations.
Reinforce MLOps
Support deployment, oversight, tracking, and scaling of ML pipelines and models while preventing model drift, all from one location.
Data pipelines
Access multiple sources of data
Improve output by accessing industry-specific data sources with over 200 data connectors to enterprise and external databases, tools, and applications.
Continuously improve data
Consistently enrich and transform data to create a single view using SDKs or drag and drop capabilities.
Improve data quality and governance
Effectively manage data and pipelines through robust quality gates, lineage tracking, and governance.
Accommodate streaming and batch scenarios
Adeptly flex to process batch or streaming data scenarios in accordance with its input frequency.
Manage a petabyte-scale lakehouse
Easily contend with and scale large volumes of data with an open table, format-based lakehouse that operates at petabyte scale in production environments.
Security and privacy capabilities
Role-based access control
Ensure data security and privacy with role-based access control built into every level of SymphonyAI’s platform and applications.
Extensive observability
Gain full oversight throughout audit trails with alerting mechanisms built into every level of SymphonyAI’s platform and applications.
Privacy standards compliance
Support and meet all standard security and privacy requirements, including GDPR and CCPA, by utilizing SymphonyAI’s platforms and applications.
