Voice AI Platform | Enterprise Voice Agents That Actually Work

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

WaterfallTimeline

›Turn 1: User Input142ms

Speech to Text89ms

Intent Recognition53ms

›Turn 2: Agent Response1.2s

Knowledge Retrieval342ms

LLM Reasoning654ms

Text to Speech231ms

›Turn 3: Tool Execution2.8s

check_availability()1.9s

Response Synthesis892ms

›Turn 4: Validation5.2s

External API Call4.8s

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

OutputError

{
  "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.

📞

Call Ends

📝

Transcribe

🔍

Analyze

🔗

Integrate

Recording and transcription

Capture durable records of what was said, how the interaction unfolded, and what context was gathered during 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.

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-ready oversight

Support governance, reviews, controls, and compliance requirements across production voice deployments with records that are usable beyond debugging.

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.

VoiceToolsWorkflowsData

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.

Trusted by Industry Leaders

Agentic AI in the Enterprise - Satyajit Saha & Sandeep Dinodiya

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.

What stood out for us was the platform's ability to handle enterprise requirements - security, governance, and observability - while still allowing teams to rapidly prototype and deploy AI solutions. SimplAI helped us move from fragmented AI initiatives to a scalable AI operating model

Satyajit Saha

SVP - Global Head of Technology and Digital Solutions

We chose SimplAI for its agentic operating system and enterprise-grade reliability. Today, we run multiple agents across GTM, operations, and customer support — all on a platform that scales and deploys securely on private clouds. The support from the team has been exceptional.

Ft. Jugal Anchalia

Co-Founder & CEO, Refold AI

Satyajit Saha

SVP - Global Head of Technology and Digital Solutions

SimplAI is helping us address customer challenges at scale using AI, without the need to build an in-house AI engineering team. Even before going live in production, SimplAI has shown its value through its robust capabilities and consistent support for our goals. Their responsive and dedicated approach has made them a reliable partner in advancing our AI initiatives.

Lisa McLean

Director of Product Management | Peek

Secure infrastructure alone is not enough. Enterprises need the full stack — governed AI agents running inside a deployment model that never compromises their security posture. Pairing Zeblok’s Ai-MicroCloud with SimplAI’s orchestration layer means enterprises no longer have to choose between capability and control. Furthermore, our ability to offload to Flash memory means significant reduction in GPUs when managing user context.

Mouli Narayanan

Founder & CEO | Zeblok Computational Inc.

With SimplAI, Lawyered isn't just embracing AI, we're redefining the legal landscape. By seamlessly integrating cutting-edge technology with our mission to democratize legal access, we're not only streamlining processes but also ensuring data security and privacy. SimplAI isn't just a platform, it's a catalyst for innovation.

Himanshu

Founder & CEO | Lawyered