Voice AI

The orchestration layer for enterprise voice agents.

Deploy intelligent voice agents across phone, WhatsApp, and embedded interfaces - with real-time intelligence, full observability, and enterprise-grade control.

Channel-Agnostic

Voice that works wherever the conversation happens.

One voice layer, multiple surfaces. Deploy phone, WhatsApp, and embedded voice agents from a single orchestration layer - with consistent behavior across every channel.

One voice layer, multiple surfaces
Route to phone SIP, WhatsApp Business, or embedded web interfaces from a single agent definition - no per-channel rewrites.
Consistent behavior across surfaces
The same agent logic, tool access, and evaluation standards apply whether the customer calls in or messages on WhatsApp.
Deploy once, run anywhere
Configure once in the platform, and the orchestration layer handles channel-specific protocol differences automatically.

Execution Architecture

Sync or async. Your call. Literally.

Run real-time sync execution for low-latency calls, or async pipelines for workflow-heavy interactions - configured per agent, per route, per call type.

Sync for low-latency turns

Execute immediately with no queue for real-time conversational flows where response speed, turn continuity, and natural pacing matter most.

Async for workflow-heavy calls

Use a dedicated priority queue for calls that trigger external validations, multi-step checks, API dependencies, or longer-running operations mid-conversation.

Built for real workflow complexity

Choose execution behavior based on the interaction pattern, tool depth, and business process behind the call - not a one-size-fits-all runtime model.

Live Intelligence

The agent knows before the turn is over.

Retrieve knowledge, call tools, validate external systems, and shape the next response while the conversation is still live.

Real-time knowledge retrieval
Pull relevant business context from the knowledge base during the conversation so responses stay grounded while the caller is still engaged.
Tool calls mid-call
Trigger actions, fetch system data, and continue the interaction with updated context in the same conversational loop rather than deferring work to post-call workflows.
External validations in flow
Validate identity, policy rules, status, availability, or business constraints before the next turn is spoken, not after the conversation has moved on.

Conversational Control

Not hardcoded behavior. Configured conversation.

Barge-in, interruption handling, silence thresholds, and tool announcements are behaviors you define - not defaults you inherit.

Barge-in and interruption handling
Let users interrupt, redirect, or clarify naturally without breaking the conversational thread or losing system state mid-interaction.
Silence detection and pacing
Control how the system responds to hesitation, pauses, and dead air across support, intake, collections, and workflow-heavy conversation types.
Behavior that fits the use case
Tune response timing, interruption tolerance, silence thresholds, and conversational pacing to match the operational context of the deployment.

VOICE TRACING

When a call breaks, find the turn it broke on.

Trace voice interactions at turn level with visibility into reasoning, tool timing, interruption events, and latency across the full pipeline.

Voice Call Trace
Duration: 2m 34s
Waterfall Timeline
Turn 1: User Input 142ms
- Speech to Text 89ms
- Intent Recognition 53ms
- Turn 2: Agent Response 1.2s
- Knowledge Retrieval 342ms
- LLM Reasoning 654ms
- Text to Speech 231ms
- Turn 3: Tool Execution 2.8s
- check_availability() 1.9s
- Response Synthesis 892ms
- Turn 4: Validation 5.2s
- External API Call 4.8s

"validation_request": {
  "service": "payment_api",
  "method": "verify_account",
  "timeout": 5000
}

{
  "error": "Request timeout",
  "status": "failed",
  "code": "TIMEOUT_ERROR",
  "message": "External API did not respond within 5000ms",
  "timestamp": "2026-03-30T10:23:50Z",
  "latency": 5200
}

Pipeline Breakdown

Speech Recognition
89ms (8%)
LLM Processing
654ms (23%)
External API
4.8s (65%)

Turn-by-turn trace depth

Inspect each spoken turn, system response, tool invocation, orchestration step, and runtime event in sequence across the conversation.

Pipeline timing visibility

See exactly where latency accumulates across transcription, reasoning, retrieval, tool execution, validation, and synthesis rather than treating the call as one black box.

Full-fidelity call debugging

Find the precise turn, dependency, interruption event, or pipeline stage that caused the conversation to degrade, stall, or fail in production.

Post-Call Intelligence

The call ends. The work doesn't.

Record, transcribe, analyze, summarize, and feed structured call intelligence back into your workflows and systems.

Recording and transcription
Capture durable records of what was said, how the interaction unfolded, and what context was gathered during the conversation.
Full-fidelity call debugging
Find the precise turn, dependency, interruption event, or pipeline stage that caused the conversation to degrade, stall, or fail in production.

Enterprise Oversight

Not a recording. A full audit trail.

Maintain compliance-grade records of voice interactions, execution behavior, and post-call activity with the visibility enterprise deployments require.

Audit logs
Keep durable records of calls, tool actions, execution events, validations, and downstream workflow outcomes tied to the interaction.
Operational accountability
Know what happened during the conversation, what systems were touched, what decisions were made, and how the workflow completed.

Enterprise Governance

Built for workflows that happen to speak.

Voice is not treated as a separate product. It runs inside the same orchestration, data, tracing, and governance layer as the rest of the system.

One execution layer

Voice calls, validations, tool actions, knowledge retrieval, and downstream workflows run in the same operational system rather than across disconnected products.

One visibility layer

Tracing, evaluation, auditability, and post-call intelligence stay connected to the actual execution path of the conversation.

One platform, not stitched tooling

Teams do not need one system for calls, another for workflows, and another for debugging what happened across the interaction lifecycle.

Voice that holds up in production.

Build, deploy, and govern enterprise voice agents with real-time intelligence, configurable behavior, and compliance-grade observability - all in one platform.

Trusted by Industry Leaders

SimplAI has fundamentally changed how we approach AI adoption inside the organization. Instead of running isolated experiments with different models and tools, we now have a unified platform to build, orchestrate, and govern AI agents across multiple business workflows.

FAQ

Frequently Asked Questions

What is SimplAI Voice AI and what can it do for my business?

SimplAI Voice AI is an orchestration layer designed to help businesses deploy intelligent voice agents at scale across phone, WhatsApp, and other channels. It supports both real-time (sync) and asynchronous voice calls, with built-in knowledge retrieval, tool-call mid-call support, and post-call workflow automation — making it suitable for enterprise customer support, sales, and operations teams.