What the agents do
It's not an IVR. It's an agent that reads the core and knows when not to act.
The assistant doesn't improvise answers: it checks the real policy, claim, or payment before speaking, and knows its own limits, when to transfer, when not to, and when to ask for a second verification.
Checks the core, not a generic knowledge base
Verifies identity and checks the customer's real policy, claim, or payment status, the same data an agent would see.
Recognizes you and picks up where you left off
Identifies by ANI before answering and, if there was a previous call, offers to continue the same case instead of starting over.
Voice or keypad, the customer's choice
ID numbers and confirmations can also be entered via DTMF, zero digits misread by voice recognition.
Knows when NOT to transfer
If the policy is liability-only, it explains that roadside assistance isn't included instead of routing to the wrong queue.
Checks the queue before transferring the call
If there's no one available at the destination, it overflows to the backup plan and leaves a note in the transcript, never leaves the customer hanging blindly.
Schedules and quotes without leaving the conversation
Faced with an "I want a quote" or a service center appointment, it hands off to the sales specialist or gives the info without breaking the thread.
Extra verification before revealing sensitive data
For sensitive requests it requires a second identity factor before saying a single figure; if verification fails, it reveals nothing and escalates.
Layered AI architecture
Six layers, one brain: from the channel where the customer speaks to the desktop where the agent works.
Each layer has a distinct job and all of them share the same context, nothing gets rebuilt moving from one to the next.
Channels
entryAny channel the customer is already using to talk to you, without asking them to switch apps.
Agnostic Data Plane
connectivityConnects to any data provider without locking into one, the core changes, the layer doesn't.
Voice AI Engine
understandingIt understands what the customer says, in context and intent, and responds naturally by voice or text. Runs over WebRTC straight in the browser, no softphone to install.
OMNIA Hub & Orchestrator
agent automated orchestratorDecides which agent acts, under what policy and what monitoring, the orchestrator that connects understanding to action.
OMNIA AI Agent Assist
live copilotTranscribes, detects intent and sentiment live, suggests the next best action, auto-fills the CRM, and does screen-pop by ANI/UCID, building the customer's 360° view before the agent even answers.
OMNIA Workspace
desktopWhere everything above lands: 360 panel, embedded softphone, digital inbox, and knowledge base, in one unified screen.
The assistant and the specialists
A 24/7 assistant the team configures without writing code.
The assistant answers backed by its own document base, it never invents a fact that isn't cited in the source, and it's tuned from a no-code editor: a personality prompt plus rules for role, tone, accent, and catalog. It handles requests, quotes, and hands off.
- Own document base, answers citing the product's real source, not generic text trained once.
- No-code editor, role, tone, accent, and catalog are configured in a form, without touching a line of code.
- Personality prompt, each agent's "voice" (formal, friendly, technical) lives in configuration, not in the model.
- Handles, quotes, and hands off, it resolves the simple stuff itself and passes the rest with full context to the right specialist.
Open conversation
Answers about product, sales topics, or business verticals with free-form language, within the brand script.
Knowledge with cited source
Classifies intent, searches the knowledge base, and answers citing the exact source the data comes from.
Captures and dispatches
Takes or validates a key piece of data (ID number, plate, policy number) and dispatches the action, with no conversational ambiguity.
voice receptionist
or routes to queue / human
reveals nothing
sentiment · lead · recording · summary → CRM/ITSM
Real cases, not lab demos
The same scenarios running in production today.
Examples of conversations the assistant handles every day: what the customer says and how it resolves it.
Status of my claim
Gives the real status of their case instantly, no waiting, no transfers.
I need a tow truck, my car broke down
Activates assistance and keeps the customer informed until help arrives.
When do I get paid for my disability leave?
Answers about their claim securely, only to the right person.
I want a quote for insurance
Connects with the sales team with all the context ready, no repeating the conversation.
A call on a Saturday night
Handles what's urgent 24/7 and routes the rest for the next business day.
This is garbage, I want to talk to someone now
Acknowledges the frustration and transfers to a person immediately, without running them around.
Governance, no black boxes
The AI suggests. The human decides.
Every interaction is recorded with prior notice, transcribed, and tagged with its AI cost per call. No black box: for every case there's a map of which agent handled it, which tool it called, and why it transferred, or didn't.
- →Recognizes intent across 10 categories and recommends the route: resolve it itself, hand off to a specialist, or escalate to a specific line of business.
- →When transferring, it hands over the full transcript and a suggested next step to the human agent, copilot, not replacement.
- →Every call shows its AI cost and which tool each agent used, traceable end to end.
- →If the customer asks to speak with a person, they're transferred immediately with full context: 0 seconds to pick the case back up.
- →No sensitive data goes out without a verified second identity factor; if it fails, it escalates to a person instead of retrying on its own.
- →Recording with prior notice, transcript + outcome auditable per call, aligned with Law 8968/Prodhab and what SUGESE/SUGEF require.
Bot quality dashboard
We audit the bot like a human agent and improve the model every week.
An agent that speaks the same language as your core.
The assistant isn't a generic plug-and-play: it understands the platform's data model, governs its own actions, and will let a human take over any conversation at any moment.
See capabilities again