Uniphore Business AI

Categories: Automation / Agents, Business & Sales, Customer Support | Pricing: Enterprise | Official Website ↗

Uniphore Business AI provides an enterprise-wide industrial data and AI architecture platform to deliver AI agents and applications for various business functions.

Uniphore Business AI bridges the AI divide by combining the simplicity, personalization, and seamlessness of Consumer AI with the scale, security, and control required for Business AI. It provides an enterprise-wide industrial data and AI architecture platform and delivers AI that is ready for business. The platform connects fragmented data sources, automates data discovery and preparation for AI, and offers a factory for autonomously built, fine-tuned, and domain-specific Small Language Models (SLMs). It evaluates and secures an ecosystem of open, closed, and fine-tuned models for enterprise readiness, and builds and deploys multi-agentic workflows connected to SLMs and data. Uniphore Business AI Cloud is a complete stack that powers the agentic enterprise with a full-stack AI platform spanning data, knowledge, models, and agents. This includes an Agentic Layer for building agent libraries and multi-agentic workflows, a Model Layer for orchestration and security, a Knowledge Layer for RAG and SLM fine-tuning, and a Data Layer for multi-cloud/multi-data compute and data automation. The platform is designed to be Sovereign, Composable, and Secure, supporting various deployment environments and working with diverse models and data sources. The Uniphore Business AI Suite offers specialized AI apps and agents for various departments. This includes Customer Service AI with agents for real-time guidance, conversation insights, self-service, and communication recording. Marketing AI provides agents like CDP Agent, Audience Agent, Marketing Insights Agent, and CDP Search Agent. Sales AI features a Sales Interaction Agent, and People AI includes a Recruiting Agent. These agents are deeply integrated, data-aware, and outcome-driven across the enterprise.

Key Features

Connects fragmented data sources and automates data discovery and preparation for AI
Provides a factory for autonomously built, fine-tuned/domain-specific Small Language Models (SLMs)
Evaluates and secures an ecosystem of open, closed, and fine-tuned models for enterprise readiness
Builds and deploys multi-agentic workflows connected to SLMs and data
Offers a full-stack AI platform spanning data, knowledge, models, and agents
Includes Agentic Layer for building agent libraries, external integration, and multi-agentic workflows
Features Model Layer for model orchestration, guardrails, and AI security
Incorporates Knowledge Layer for RAG, knowledge graphs, process discovery, and SLM fine-tuning
Provides Data Layer for multi-cloud/multi-data compute, data automation agents, and structured/unstructured data
Delivers AI agents for customer service, marketing, sales, and people operations
Supports AI deployments across on-prem, cloud, and multi-cloud environments
Works with any model, application, agent, or data source

Pros

Combines ease of Consumer AI with enterprise-grade scale, security, and control
Offers fast time-to-value through pre-built AI Agents
Provides a complete stack for Business AI, from data to agents
Ensures AI security through built-in guardrails and policy control
Supports sovereign AI deployments with full control over data and models
Composable architecture allows flexibility with layers, models, and components
Offers specialized AI agents for various business functions like customer service, marketing, sales, and HR

Cons

Pricing information is not available on the website
Specific integration details are not explicitly listed
No information on supported languages for the AI agents
Some marketing AI agents are listed as "coming soon"
Requires businesses to have an enterprise-wide industrial data and AI architecture platform

Use Cases

Automating customer service interactions
Personalizing marketing campaigns and optimizing ad spend
Improving sales team effectiveness and closing rates
Streamlining the hiring process and candidate engagement
Connecting and preparing fragmented data sources for AI applications
Building and deploying domain-specific AI models
Orchestrating and securing various AI models in an enterprise environment
Creating multi-agentic workflows for business processes

Best For

Businesses seeking an enterprise-wide industrial data and AI architecture platform
Businesses looking for pre-built AI Agents for fast time-to-value
Enterprises needing secure and compliant AI deployments
Organizations requiring AI solutions for customer service, marketing, sales, and HR
Companies that need to connect fragmented data sources for AI

Integrations: Rackspace, Cognizant, KPMG

Platforms: web

Watch demo on YouTube ↗

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