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

SymphonyAI 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

  • 100

    Data engineers, ML engineers, data scientists

  • 3 years

    Platform development

  • 30+

    Patents

SymphonyAI CTO Raj Shukla on the Eureka AI platform

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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.

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