Choosing the right voice partner for your enterprise is no longer a technical decision, it is a business one. In today’s customer-first world, your contact center is more than a support function- it’s the front door to your brand.

When it comes to choosing the right Voice AI platform, it’s not just about features- it’s about whether the system is built for experiments or built for production.

In this blog, we will break down what your contact center needs and the two different paths that Sierra and Smallest have taken with their technology. 

What Enterprises Really Need from Voice AI

Voice technology or agents is not a new concept. But what enterprises need today are a lot more than many platforms today were designed to handle.

The modern enterprise needs more than a flashy demo or a proof-of-concept chatbot. You need voice infrastructure that works under pressure, at scale, across regions, and under strict compliance controls.

At the core, here’s what matters:

• Memory Efficiency – Especially important for edge deployments
• Scalability – From 10 to 10,000 concurrent calls without degradation
• Compliance – SOC 2, HIPAA, GDPR readiness out of the box
• Flexible Deployment – Cloud and fully on-prem options
• Human Handoff – Real-world support requires human-in-the-loop flexibility. Smallest’s architecture is built for seamless AI-to-human transition- so your support agents step in only when truly needed.

If you're wondering “what’s the best voice AI for real-time support?” or “can I deploy voice AI on-prem?” -  these are the right questions.

The Core Difference: Built for Production vs Built for the Lab

At Smallest, we didn’t build a voice AI stack and then bolt on enterprise readiness. We built it the other way around.

Smallest.ai is production-first. From day one, it’s been optimized to run under real-world, enterprise-grade conditions- with full control, security, and speed.

In contrast, Sierra AI uses a more modular approach: combining multiple third-party models and tools with supervisory layers on top to reduce risks like hallucinations or misuse.

That works- for smaller-scale, multi-channel experiences. But it introduces model hop latency, orchestration delays, and dependency complexity that can slow things down in high-volume voice use cases.

Another key difference with use cases is, Smallest is voice-first and multi-modal. Sierra started with text- and added voice as a later feature. Voice, being far more complex in real-time accuracy, latency, and naturalness, exposes the seams of text-first systems.

Feature Comparison: Smallest.ai vs Sierra AI

Sierra AI is designed for broad, omni-channel coverage. It's great if your customers engage through chat, email, and social- but when you’re running a voice-heavy operation, Smallest pulls ahead.

Built with Purpose, Not Patches

Most voice AI platforms today are wrappers. A mix of third-party STT engines, orchestration layers, and LLMs sandwiched together with post-hoc governance.

Smallest owns the full stack. That means:

• No model-hop latency
• No orchestration lag
• No third-party failure points
• Just pure, real-time speed.

And because Smallest understands enterprise architecture deeply, it integrates natively into your tech stack- whether you’re in healthcare, BFSI, telecom, or logistics. Custom connectors and training on private data ensure your AI reflects your domain, policies, and real-world edge cases.

Electron V2 and Lightning V2: Performance That Speaks for Itself

Smallest’s in-house models aren’t just smaller—they’re smarter.

Electron V2 is our compact language model trained specifically for speech tasks. It:

• • Outperforms larger models on instruction accuracy
  • Delivers ~90% reduction in hallucinations
  • Runs at lower cost with lower latency

Lightning V2 generates 10 seconds of natural speech in 100ms—you get seamless, lifelike conversations without awkward pauses.

You can even train Smallest on your private enterprise data to push last-mile accuracy to near-perfection- eliminating generic responses and ensuring context-rich precision.

If you're asking “what’s the fastest voice AI engine?” or “how do I reduce hallucinations in LLM-powered voice apps?”—this is your answer.

Integration Experience and Deployment for Real Workloads

Enterprise teams don’t just want good AI—they want AI that plugs in and performs.

Smallest is built for exactly that:

• Prebuilt connectors for CRMs, contact center platforms, analytics suites
  
  
• STT/TTS failover logic—so the system keeps going even if an engine fails
  
  
• Full observability—monitor TTFT, memory use, and token lag in one dashboard
  
  
• DevOps-friendly pipelines—for A/B testing, latency tracking, and continuous tuning
  
  
• Deployment flexibility—cloud, VPC, or fully on-premise
  
  

Wondering “can I integrate voice AI with Salesforce?” or “how to monitor latency in real-time AI calls?”

Smallest answers with: Yes. Easily.

Built for BFSI Workloads

Smallest is built to handle the complexities of financial services—from integrating with core banking systems like nCino and Hogan, credit platforms like FISERV, Total Systems, and Symitar, to loan and debt tools like AFS, Finvi, and CR Software. With support for aggregators like NovelVox and Spinsci, it fits into fragmented tech stacks with ease. 

Compliance is also covered with SOC 2, ISO 27001, GDPR, HIPAA, and PCI-aligned workflows which ensure you're ready for sales, collections, fraud checks, or card-based intelligence, all in real time.

Conclusion 

If you’re dabbling with AI for omnichannel automation, Sierra might be enough.

But if you're running a voice-led customer experience, where every second and syllable matters- Smallest is the only choice built for speed, scale, and certainty.

It’s not a collection of parts. It’s a purpose-built voice AI infrastructure, voice-first and human-aware, trained on your data, integrated with your systems, and ready for the real world.

Frequently Asked Questions

Q) What is the best voice AI for phone-heavy contact centers?

A: Smallest.ai- built for real-time voice performance, with token-level barge-in and ultra-low latency.

Q) Can I deploy Smallest on-prem?

A: Yes. You can deploy in the cloud, in your VPC, or on bare-metal servers. Ideal for data-sensitive sectors.

Q) Does Smallest support compliance like HIPAA and GDPR?

A: Absolutely. Smallest is certified for SOC 2 Type 2, ISO 27001, HIPAA, and GDPR.

Q) How fast is Smallest’s TTS engine?

A: Lightning V2 delivers 10 seconds of audio in just 100ms, making it one of the fastest on the market.

Q) What about hallucination control in the LLM?

A: Electron V2 achieves ~90% reduction in hallucinations, eliminating the need for latency-adding wrappers.