As voice AI platforms evolve, the choice isn’t just about automating calls, it’s about infrastructure that powers custom, real-time, and scalable voice experiences.

If your voice partner cannot scale with the demands of the market, then it’s time to reevaluate what will help you for the present and the future. 

When companies look to automate their contact center needs, a company which has carved its own niche in the space is Observe AI, by delivering real-time agent assist, QA automation, and coaching tools. Recently, it’s expanded into Voice AI Agents, aiming to automate phone-based customer interactions with realistic voices.

But if the goal is modern call center automation, scaling outbound campaigns, or embedding live voice agents into your product, you may find Observe.AI’s stack limiting.

Smallest.AI, by contrast, offers a full-stack voice infrastructure built for real-time performance, flexibility, and developer control. It isn’t just an Observe.AI alternative, it’s a better choice across most production-grade voice use cases.

Architectures: Proprietary LLM vs Open, Tunable Stack

Observe.AI:

• Uses a 30‑billion‑parameter LLM trained on contact center data, outperforming GPT‑3.5 by ~35% in conversation summarization and sentiment accuracy.
  
• However, it also relies on third-party models (OpenAI/GPT, Anthropic) in an ensemble for tasks like entity recognition and turn detection.
  
• LLM control is vendor‑managed: customers cannot fine‑tune or swap models themselves.
  
  

Smallest AI:

• Offers Electron V2, an instruction‑tuned LLM you can fine‑tune on your own CRM logs, call transcripts, or support data.
  
• Supports optional LLM configuration: run your own OpenAI/Anthropic/Claude or swap out with private models.
  
• Owns full voice stack architecture: STT, LLM, TTS are all built and controlled internally.
  
  

TTS Performance: Lightning V2 Outperforms

Observe.AI uses models from acquisitions and third-party providers. 

Smallest.ai:

• Lightning V2: world’s fastest TTS, generating 10 seconds of speech in just ~100ms with excellent MOS scores (~3.8) and support for voice cloning from 10 seconds of audio. 
• Benchmarked across geographies, Smallest TTS latency (~336–340ms) consistently outpaces ElevenLabs (~350–527ms

Real-Time, Interruptible Conversations

Observe.AI’s voice agents are built from tightly scripted conversation flows enhanced with engine‑driven turn detection

But Smallest is built for true streaming agents. Smallest’s enterprise ready conversational agents- 

• Can receive interruptions mid‑utterance and respond instantly
• Supports multi-turn, branching logic with immediate reaction
• Best for outbound, support routing, or product-embedded agents

Observability & Debugging: Know Exactly What Went Wrong

Observe.AI offers post-call dashboards and summaries. But when something breaks mid-call, like a missed escalation or tool failure, you’re left guessing.

Smallest AI gives you full observability:

• Real-time latency tracing
• Flow-level visibility into tool calls and API failures

If your company runs campaigns at scale, Smallest has the infrastructure to be one of the top alternatives to Observe AI in 2025.

Why Smallest Built a Multi-Nodal Framework

Many voice agents in the market use a single mega-prompt that handles logic, messaging, and tool use all at once. Great for prototypes but this is risky in production.

Smallest takes a multi-nodal approach, breaking flows into structured steps:

• You control exactly when tools are called
• You can retry or fallback if something fails
• You inject custom logic without rewriting prompts
  

Why This Matters in Production

For high-volume voice agents handling use cases such as Lead qualification, Debt collection, order fulfillment and Support triage- this modular approach is critical.

This means-better uptime, easier debugging, more customization and tighter compliance (e.g. regulatory flows that must follow exact paths)

This is part of why Smallest isn’t just another tool for spinning up demos, it’s voice AI built to last in production.

Deployment & Compliance

Observe.AI is primarily deployed as a public SaaS platform. While it offers enterprise-grade security and even private instances for large customers, it lacks flexibility for teams that need full control, like on-prem deployments or air-gapped environments. That makes it harder to adopt in regulated industries like healthcare, finance, or government.

In contrast, Smallest AI is built for infra-heavy deployments. You can run it in the public cloud, your own VPC, or even fully on-prem. It supports air-gapped deployments out of the box, making it a reliable option for teams handling sensitive customer data or building internal LLMs behind the firewall.

Pricing: Enterprise Lock-in vs Elastic Scale

Observe.AI follows a typical enterprise-first pricing model. Products like VoiceAI Agents or Agent Assist are licensed via contracts, often bundled with fixed call or chat volume tiers. Pricing is usage-based, but you won’t find public plans, making it harder for fast-moving teams or mid-market players to try before they commit.

Smallest AI flips this model with transparent, self-serve pricing. You can start for free with test credits, move to a $49/month developer tier, and scale into the $1,999/month Business plan with 10 concurrent calls. Voice minutes are priced clearly (~$0.07–$0.12 depending on region), and there are no hidden platform fees, no per-feature charges, and absolutely no long-term lock-ins.

Summary Comparison

Final Word

Observe.AI delivers results inside the contact center. Smallest.ai delivers voice infrastructure across products, workflows, and industries.

If you’re evaluating Observe.AI alternatives for voice AI, Smallest offers unmatched depth, flexibility, and control from POC to production.