Native support for cloud, hybrid, or on-prem operations via seamless support for and integration with Microsoft Azure, AWS, and Google Cloud Platform to ensure data security at rest and on the network.
Do AI the right way with AI built and optimized for specific business workflows
Tap the power of predictive and generative AI together like never before to understand what’s happened and to plan for what’s next, with near- or real-time insights and the ability to do what-if analysis. With elegant copilot user interfaces designed for specific personas that smartly display information in the right context for specific tasks.
Critical AI capabilities
Predictive + generative AI
AI Copilot for each business user so you can interact in a natural, interactive language way. Combining both predictive and descriptive models to provide insights about what happened and help you predict what could happen next.
Elegant and useful UI/UX
Low code and natural language interfaces ensure teams and users can work quickly and efficiently. Elegant workflow integration gives workers the power of AI directly as they work, with the tools they use today, to help make decisions and power productivity.
Effective AI lifecycle management
All the tools, APIs, SDKs for an effective ML lifecycle optimized for vertical applications and tasks, with data exploration, feature engineering, model building and experimentation, and deployment.
Lakehouse architecture and data platform
For the security, scale, and access that data scientists and business users need for the structured and unstructured data required for AI pipelines and applications in production environments.
Vertical-specific and task-specific fine-tuned LLMs for each industry and use case to provide relevant contextualization for user queries.
Cloud scale and security
Industry-specific data connectors for access to all relevant data sources and formats for retail, CPG, financial services, manufacturing, media, and IT.
The SymphonyAI architecture
Next-gen predictive and generative Eureka AI architecture
Predictive and generative capabilities
Generative AI and LLM Ops
LLMs fine-tuned on proprietary data, plus grounding in industry knowledge graphs, enabling understanding of industry concepts, metrics, and industry terminology.
Content generation and reporting
Understand the what, what, and who behind trends, generate customized summaries, reports, and charts.
Reasoning and logical deduction
Use industry knowledge graphs and minimal training data to reason like specific personas. Understand cause-and-effect relationships to make predictions or decisions.
Actions via tool invocation
Interact with first party and external market data, services, and tools via APIs, for reasoning and action taking.
Enterprise security and privacy
No data leaves compliance boundaries. LLMs deployed in compliant sandboxes. No data used to train models.
Enterprise access control
Authentication and access control built at data and API layers. No data reaches LLMs without permission.
Grounding in data and facts
Answers not coming from LLMs in build generic knowledge, but from looking up the right data from the knowledge graph and invoking the right predictive models.
Ability to share at the level of every insight. Collaborate with a group on reports. Built in authentication for safe and secure collaboration.
Guided machine learning workflow
For data preparation, model build, training, experimentation, validation and serving for inference.
Training, batch, and real-time inference
Flexible model training capabilities and deployment of ML models. Batch or real-time for high volume transactions.
Feature engineering and feature store
Build, store, share, and reuse curated features across machine learning pipelines.
Support for leading ML frameworks
Use all the latest frameworks—TensorFlow, scikit-learn, PyTorch, Keras, Apache MXNet, Huggingface, Spark ML, Torch, and more.
SDKs and REST APIs
Use the SDKs to automate data ingestion, build, train, and deploy models. Models are deployed with REST endpoints for inference.
Full visibility and transparency so you can understand the reasoning behind model predictions and recommendations.
Deploy, oversee, track, and scale your ML pipelines and models all from one location. Detect and prevent model drift through automatic model monitoring, feedback loops, and performance evaluation.
Access all relevant industry-specific data sources with more than 200 data connectors to enterprise and external databases, tools, and applications.
Transform and enrich
Continuously enrich and transform data to create a single view using SDKs or drag and drop capabilities.
Governance, lineage, quality
Manage data and data pipelines through robust quality gates, lineage tracking, and governance.
Streaming and batch
Adaptively process data in accordance with the data’s input frequency, whether for batch or streaming scenarios.
Petabyte scale lakehouse
Easily manage and scale large volumes of data with open table format-based lakehouse that operates at petabyte scale in production environments.
Security and Privacy
Role-based access control
Ensure data security and privacy with role-based access control built in to every level of the SymphonyAI platform and applications.
Full oversight through audit trails and alerting mechanisms built into every level of the SymphonyAI platform.
Privacy standards compliance
Support for all standard security and privacy requirements, including GDPR and CCPA.