Bland AI is one of a new wave of “voice first” AI platforms that promise to automate enterprise phone calls with human sounding agents. Founded in 2023 and backed by well known investors, it focuses tightly on phone based automation rather than broader omnichannel customer experience.
For enterprises, this focus can be attractive if the main pain is high outbound or inbound call volume. At the same time, Bland is still a young, LLM centric with prone to hallucinations. The company differentiation leans heavily on infrastructure and latency rather than on proprietary AI models or a wide platform footprint.
Bland AI Company Overview
Bland AI builds and runs AI phone agents for companies. The product is designed to sound human, speak multiple languages and handle both outbound and inbound calls for sales, support and operations.
Company snapshot
- Founded – 2023
- Headquarters – San Francisco, California, United States
- Size – about 60 to 70 employees
- Funding – about 65 million dollars total, including a 16 million dollar Series A and a 40 million dollar Series B announced in early 2025
- Founders – Isaiah Granet, Sobhan Nejad
- Key clients – Cleveland Cavaliers, Better.com, Sears, University of Phoenix, Hertz and others
- Website – bland.ai
What does Bland AI do?
Bland AI provides a platform to automate phone calls with conversational agents that mimic human callers or agents. Typical use cases include:
- Outbound sales and prospecting
- Appointment reminders and scheduling
- Basic customer support and FAQ style calls
- Follow up surveys or notifications
Agents can call customers, answer incoming calls, interact via natural language, capture information and pass data to CRMs and other systems using APIs and webhooks.
Key features
From public product pages and third party descriptions, Bland AI typically includes:
- AI phone agents for inbound and outbound calls
Agents initiate or receive calls, handle multi turn conversations and log outcomes. - Multilingual voices
Voice cloning, customizable voices and multi language support, aimed at making calls feel human while scaling up volume. - Customizable conversational pathways
A visual or script based “pathways” builder to constrain how conversations unfold, helping reduce hallucinations and keep agents on brand. - Self hosted, low latency infrastructure
Bland highlights that its stack can run in customer controlled environments and is optimized for very low audio latency and high concurrency. - System integrations and analytics
Real time APIs to integrate with CRM or booking systems, plus dashboards and analytics on call volumes, outcomes and customer responses.
Technology – LLM centric with an infrastructure angle
Bland’s messaging stresses that it is “not a ChatGPT wrapper” and instead offers a self hosted, enterprise grade voice stack with custom models and infrastructure.
However, based on available information:
- Bland is still part of the broader ecosystem of platforms built around large language models (LLMs), with limited proprietary prompting, conversational pathways and safeguards on top.
That means Bland’s value for many customers lies in:
- Fast audio and telephony handling
- Tooling that simplifies campaign setup
- Guardrails to keep LLM behavior in a safe range although they can’t guarantee any LLM hallucination risks.
Enterprises that need deeper control over language understanding, remove hallucinations, or omnichannel orchestration may still find themselves looking for additional platforms beyond Bland.
Bland AI’s best alternative for enterprises: Teneo
For organizations whose challenges go beyond outbound calling campaigns or point solutions on the phone channel, it is common to pair telephony tools with a broader Agentic AI platform.
One such platform is Teneo, an enterprise focused AI orchestration layer designed for large contact centers that need high accuracy, multilingual support and deep control across both voice and digital.
Where Teneo differs from voice only platforms
Hybrid AI and TLML
- Teneo uses its proprietary Teneo Linguistic Modeling Language (TLML) alongside LLMs. This deterministic layer improves intent accuracy, gives fine grained control and reduces the cost and instability that can come from using raw generative models alone.
Language coverage and scale
- The platform supports development in over 86 languages, including pre built accelerators for major markets.
- Deployments include a Magnificent 7 technology company reaching 99 percent NLU accuracy and 90 percent total call understanding across 42 languages, as well as telecom and healthcare leaders handling millions of monthly calls.
Enterprise grade voice and contact center focus
- Teneo Agentic AI, Conversational IVR, and voice AI products are designed specifically for large contact centers, improving NLU accuracy up to 99 percent and reducing misrouting by around 90 percent in some published case studies.
Model and vendor flexibility
- Teneo is vendor agnostic. Enterprises can orchestrate multiple NLU engines and LLMs, and change providers over time without redesigning journeys from scratch.
Governance and deployment options
The platform is HIPAA, ISO 27001, GDPR, EU AI Act, and SOC 2 compliant. More information can be found at Teneo Security Center.
When to consider Teneo instead of or alongside Bland
Teneo tends to be a strong fit when:
- Voice is critical, and you are looking for omnichannel experiences
- Accuracy must be demonstrably high, including for complex IVR and service flows. With zero risk of LLM hallucinations.
- There is a long term plan to standardize AI behavior across multiple countries, brands and languages
- The organization wants flexibility to combine multiple AI models rather than anchor entirely on one vendor stack
Bland may be sufficient for small solutions with limited capabilities. Teneo becomes more attractive when you need a long term, AI platform that supports both phone and digital journeys, integrates into existing CCaaS infrastructure and has a track record of large scale deployments.