Uniphore provides the Business AI Cloud, a sovereign, composable platform that unifies data ingestion, knowledge graph creation, model management, and agentic workflow execution for enterprises. The platform offers multi‑cloud/on‑prem connectors, RAG‑enabled knowledge graphs, a model garden with fine‑tuning and built‑in guardrails, and low‑code BPMN workflow tools to deploy AI agents for customer service, marketing, sales, and recruiting without extensive engineering.
Funding
$260M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
+4Founders
Product
Problem
Enterprises often have siloed data sources and lack a unified, secure AI infrastructure that can scale across functions such as customer service, marketing, sales, and HR. This fragmentation leads to high integration costs, slow time‑to‑value for AI projects, and difficulty meeting compliance and security requirements.
Solution
Uniphore delivers the Business AI Cloud, a sovereign, composable platform that spans four core layers—Data, Knowledge, Model, and Agentic—to unify data ingestion, preparation, and AI execution. The Data layer provides multi‑cloud and on‑prem connectors with zero‑copy ingestion, while the Knowledge layer builds RAG‑enabled knowledge graphs for contextual reasoning. The Model layer offers a model garden with open, closed, and fine‑tuned large language models, protected by built‑in guardrails and policy controls. The Agentic layer enables visual BPMN workflow design and a Model Context Protocol for seamless integration of custom agents and third‑party services. Pre‑built AI agents for customer service, marketing (CDP), sales, and recruiting accelerate deployment, allowing organizations to automate insights, personalize interactions, and drive measurable business outcomes without extensive engineering effort.
Target Audience
Large enterprises seeking an enterprise‑grade AI platform to unify data, automate insights, and deploy domain‑specific AI agents across contact centers, marketing, sales, and talent acquisition.
Features
- Sovereign deployment options: on‑premises, private cloud, or public cloud with full data and model control.
- Composable architecture allowing independent use of any layer, model, or data source via standardized APIs.
- Data Layer: automated connectors, data discovery agents, and zero‑copy pipelines for structured and unstructured data across multi‑cloud environments.
- Knowledge Layer: Retrieval‑Augmented Generation (RAG) pipelines, dynamic knowledge graphs, and process discovery tools for contextual AI.
- Model Layer: Model Garden with curated industry models, BYO model support, fine‑tuning factory for domain‑specific SLMs, and embedded security guardrails.
- Agentic Layer: BPMN‑based visual workflow builder, Model Context Protocol (MCP) for external integration, and library of task‑oriented agents (real‑time guidance, conversation insights, CDP, sales interaction, recruiting).
- AI security and observability: built‑in policy enforcement, audit logging, and compliance‑ready monitoring.
- Low‑code UI and SDKs for rapid agent customization and integration with existing enterprise systems.