Regal.io

AI Agents

Regal’s no-code builder provides AI Customer Service Agent capabilities across voice, SMS, and web chat. Teams define an agent’s role, goals, conversation steps, tone, guardrails, fallback behavior, and escalation paths. Agents can use customer attributes as dynamic variables and retrieve information from knowledge bases built from websites, documents, or text.

Prebuilt and custom actions use function calling to interact with external systems during a conversation. Agents can check availability, schedule appointments, collect structured information, update records, end interactions, or transfer callers to an internal queue, external telephone number, or SIP endpoint. Common applications include lead qualification, appointment scheduling, customer onboarding, inbound support, payment collection, confirmations, and routine account servicing.

Teams can test conversation logic in a browser, inspect action payloads and results, and run bulk simulations against defined scenarios and success criteria. Test cases can also be created from production transcripts. Agent variants and A/B tests support controlled changes to prompts, voices, models, and conversation behavior.

Contact-Center and Sales Workflows

Regal supports inbound routing and Interactive Voice Response (IVR) workflows using voice or keypad input. AI agents and human representatives can operate within the same routing environment, allowing conversations to be escalated or transferred with customer context.

For outbound teams, Regal includes Sales Dialer modes such as preview, progressive, and power dialing. Answering-machine detection can distinguish among live callers, voicemail systems, IVRs, and call-screening services, with configurable handling for each result. Additional telephony functions include branded caller identification, telephone-number management, voicemail handling, spam-label monitoring, call recording, and quiet-hour controls.

The unified agent desktop gives human representatives access to phone, SMS, and email conversations alongside customer profiles, prior activity, campaign information, and assigned tasks. A reduced version of the desktop can also be embedded in third-party CRM or ticketing applications through an iframe.

Customer Data and Engagement

Regal’s Sales Engagement tools use behavioral events, profile attributes, and dynamic segments to trigger outbound calls, messages, and cross-channel journeys. Teams can configure branching logic, audience conditions, timing, suppression rules, and experiments without rebuilding the underlying customer system.

Native Customer Data capabilities consolidate contact attributes, custom objects, consent status, and interaction history into unified profiles. Data can enter Regal through integrations, Segment events, or an API, then be returned through native destinations, JSON reporting webhooks, or a Snowflake share. Supported integration patterns include Salesforce, HubSpot, Kustomer, Segment, and custom CRM or data-platform connections.

Analytics and Operational Controls

Regal’s Conversation Intelligence capabilities include recordings, transcripts, summaries, dispositions, configurable trackers, and custom post-call analysis. For AI-agent conversations, transcripts also expose function calls, action results, errors, knowledge-base retrievals, and transitions between conversation states. Custom dashboards and reporting events support monitoring across campaigns, agents, channels, and customer outcomes.

Compliance controls include opt-in and opt-out logic, audit logs, and quiet hours by area code or postal code for workflows subject to the Telephone Consumer Protection Act and Telemarketing Sales Rule. The vendor states that Regal maintains SOC 2 Type II controls and supports HIPAA- and PCI-regulated workflows. Customer data is hosted in AWS and encrypted in transit and at rest; U.S. data residency and employee-access restrictions are available where required.