Generative AI
for the enterprise
Designed to support user workflows and decision making, SymphonyAI generative AI applications provide deep insights and productivity boosts that let workers do their jobs better and faster than ever before.
LLMs and knowledge graphs
SymphonyAI generative AI applications are built on industry-specific LLMs fine-tuned to address specific use cases, combined with (deterministic industrial) knowledge graphs.
Generative AI for business
The SymphonyAI generative AI architecture is built to deliver insights and answer questions quickly and accurately while protecting data privacy and access. It combines the power of generative and predictive AI so users can get insights and anticipate what’s next, all through a natural language interface.
Generative AI capabilities and features
Generative AI UX and UI components
- Generative AI Copilot UX for each vertical and task to enhance decision-making for specific personas
- UI components: common components tied to response processing and plug-ins so users receive information in the way it best can be consumed
Skills, agents, and orchestration
- Skills library with optimal tools and plug-ins for external data to support reasoning and insights
- Orchestrator to define a dynamic plan to orchestrate reasoning within and across needed skills to fulfill a prompt response
- Agent to execute the orchestration plan with action via tool invocation
- Response processing: for optimal delivery of information as text, a table, visualizations, or charts
- Conversational memory management: for query context and resolution to best support users
Privacy, security, identity, and access control
- Safe, reliable, and secure operations with encrypted data at rest and over the network
- Safe enterprise data never leaves the application and is never imported into SymphonyAI LLMs
- User information access is controlled centrally so users only see the information they are permitted to see
- Modern cloud security at the data and API layers
Data and AI infrastructure
- Vertical-specific LLMs: fine-tuned for both specific verticals and for each specific task to ensure precise insights and information, with accurate inference, qualifications when needed, and no hallucinations
- Knowledge graphs: contextualized information specific to your topics, business, and industry for better and faster responses
- APIs and third-party data: built in connectors to relevant information and data sources for additional context and insights
- Reasoning – add to knowledge graphs
- Eureka ML Platform: for models’ experimentation, validations, and containerized deployment within Kubernetes cluster via Kubeflow pipelines
- Eureka Data Platform: for data integration, wrangling and transformation from raw data to business level aggregates
