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Uniphore
Enterprise AI company providing the Uniphore Business AI Cloud platform spanning data, knowledge, models, and agents.
- Founded
- 2009
- Headquarters
- Palo Alto, California
- Company size
- Not disclosed
- Products tracked
- 5
Products by Uniphore
Customer voice
Customer testimonials
Quotes published on Uniphore's official website.
Sales Interaction Agent’s ability to pull out key moments is really important when we’re onboarding new sales team members. One team member is able to work with another to unlock great insights from a great call. They can then replicate that throughout the rest of the organization.
Sales Interaction Agent really extended our sales management organization. It has provided great insights for a more successful sales process. Being able to see how great our sales team is has just given me confidence that we’re meeting our clients where we need to.
I have personally worked with several scripting IVA vendors over the years, and Uniphore has one of the most user-friendly and easiest script building tools. Integrating Self Service Agent into our existing process was painless. The Uniphore team worked with our cloud dialer vendor to ensure the correct settings and configuration successfully delivered calls to the IVA. Our collection software is often difficult to integrate with outside vendors, but using APIs, we successfully achieved integration.
Customer outcomes
Case studies
Selected customer stories from Uniphore.
Pricing for Uniphore
Contact sales
Contact Uniphore for current plans, volume pricing, and enterprise terms.
Trust profile
Security and compliance
No compliance claims have been published for this company.
Built-in guardrails
Policy control
Sovereign architecture
Composable architecture
AI security
Latest updates from Uniphore
Company news
Uniphore Formalizes Sovereign Small Language Model Architecture for Enterprise
Uniphore has formalized its architectural strategy for enterprise AI, focusing on a system of small language models (SLMs) rather than generalist frontier models. This approach involves deploying a stack of domain-tuned SLMs—optimized for specific tasks like latency, compliance, retrieval, and execution—governed as a unified system to provide enterprises with greater control, data sovereignty, and cost efficiency. The strategy emphasizes shifting enterprise AI away from token-heavy general models toward modular, sovereign AI stacks that compound intelligence over time through specialized, domain-specific training on enterprise data.