Regal
AI agents and human agents on one contact center platform, triggered by customer behavior
Regal is an AI-first contact center platform combining AI voice and text agents with human agent tooling, event-driven outreach, and a customer data layer. Rather than treating automation as a separate product, it routes conversations to AI or people depending on the situation, and triggers outreach from customer behavior rather than from static call lists.
Overview
Most voice AI products sit alongside a contact center; Regal is trying to be one. The distinction matters because the hard problems in customer conversations are rarely the automation itself. They are deciding who to call and when, connecting a conversation to what the customer just did, routing between AI and humans sensibly, and keeping a single record of the relationship across channels.
Its event-driven model is the differentiator. Customer actions, an abandoned application, a viewed pricing page, a failed payment, a form submission, trigger outreach immediately rather than being queued for a batch dialer. An AI agent handles what it can and hands to a human when the conversation warrants it, with the same customer profile visible to both.
The buyer profile is mid-market and enterprise operations with real call volumes, particularly in financial services, insurance, healthcare, education, and home services where phone conversations drive revenue. It is a platform commitment rather than a tool purchase, with implementation, migration from an existing contact center, and compliance work all involved, which puts it well outside small business territory.
Best for
Mid-market and enterprise consumer-facing operations with substantial phone volume that want AI and human agents on one platform, driven by customer behavior rather than static lists.
Not the right fit for
- Small businesses wanting a simple answering agent.
- Developers wanting a voice API to embed in a product.
- Organizations unwilling to replace or substantially integrate their existing contact center.
- Businesses without meaningful outbound and inbound call volume.
- Buyers wanting self-serve signup and published pricing.
How it works
- 1
Customer events flow into the platform from your website, product, CRM, or data warehouse, building profiles with the behavior and attributes that determine when outreach is warranted.
- 2
Journeys define what happens on an event: which customers to contact, on which channel, with what timing, and whether an AI agent or a human should handle it, with branching by segment and prior interaction.
- 3
AI agents handle calls and messages with knowledge grounding and tool calling, escalating to human agents with full context when the conversation exceeds their scope or the customer asks.
- 4
Human agents work in a unified interface showing profile, event history, and prior conversations across channels, with supervisor tooling, quality review, and reporting spanning both AI and human handled interactions.
Feature breakdown
20 features in 4 modulesAI agents
Automation as part of the contact center rather than beside it.- AI voice agents
- Conversational agents handling inbound and outbound calls with knowledge grounding and tool calling.
- AI messaging agents
- The same conversational logic applied to SMS and chat so the channel is a routing decision rather than a rebuild.
- Escalation with context
- Handoff to human agents carrying the conversation, profile, and event history so customers do not repeat themselves.
- Guardrails and knowledge grounding
- Agent responses constrained to approved information, which matters in regulated consumer sectors.
- AI and human blending
- Routing decisions per conversation rather than a fixed split, so complexity determines who handles it.
Event-driven outreach
Calling because something happened, not because a list exists.- Behavioral triggers
- Outreach initiated by customer actions such as abandonment, form submission, or product usage.
- Journey builder
- Multi-step, multi-channel sequences with branching by segment, response, and prior interaction.
- Timing and pacing controls
- Rules on when customers may be contacted, respecting both regulation and reasonable behavior.
- Channel orchestration
- Voice, SMS, and other channels coordinated within one journey rather than run separately.
- Suppression and frequency rules
- Contact limits and do-not-contact enforcement applied across every channel from one place.
Contact center capability
The parts that make it a platform rather than an add-on.- Human agent workspace
- A unified interface with customer profile, history, and conversation context for agents handling escalations.
- Routing and queueing
- Skills-based routing across AI and human capacity with priority handling.
- Supervisor tooling
- Live monitoring, coaching, and quality review across both automated and human conversations.
- Call recording and transcription
- Full conversation capture with search, subject to jurisdictional consent requirements.
- Reporting across channels
- Volume, outcome, and revenue reporting spanning AI and human handled interactions.
Data and compliance
Operating in regulated consumer sectors.- Customer profile layer
- Events and attributes unified into profiles that drive both targeting and agent context.
- CRM and warehouse integration
- Two-way connections with CRM systems and data warehouses so profiles reflect the business's own data.
- Consent management
- Contact consent tracked and enforced, which is a legal requirement rather than a convenience in outbound calling.
- Compliance controls
- Calling window enforcement, disclosure handling, and audit trails for regulated outreach.
- Security certifications
- SOC 2 and sector-appropriate compliance posture for enterprise vendor review.
Use cases
4 documentedInsurance operation recovering abandoned applications
Applicants drop out partway through and generic follow-up email recovers few of them.
Abandonment triggers an immediate call from an AI agent that answers the blocking question and transfers serious applicants to a licensed representative.
Education provider handling enrollment enquiries
Interest spikes around deadlines and human capacity cannot cover the volume without long queues.
AI agents handle routine enrollment questions while advisors take conversations requiring judgment, with context preserved across the handoff.
Home services company converting inbound demand
Calls arrive at all hours and after-hours enquiries are lost to competitors.
AI agents cover overnight and overflow, booking jobs and escalating urgent work, with the same customer record humans see during the day.
Financial services team managing compliant outreach
Outbound calling must respect consent, calling windows, and disclosure requirements with auditable evidence.
Consent and timing rules are enforced at the platform level with audit trails, rather than depending on agent discipline.
Pricing
from Quoted; mid-market and enterprise contractsQuoted subscription combining platform fees, agent seats, and usage for AI conversations and telephony. Enterprise contracts with implementation; no self-serve tier.
| Plan | Price | Includes |
|---|---|---|
| Platform | Quoted annual |
|
| AI agents | Quoted usage-based annual |
|
| Enterprise | Quoted annual |
|
Billing notes
- Pricing combines platform, seat, and usage components, so quotes should be broken down before comparison against per-minute-only vendors.
- Telephony and messaging costs are additional and vary by destination.
- Implementation and migration from an existing contact center is a real project cost alongside the subscription.
- AI conversation usage is metered, so automation savings and automation costs both scale with volume.
- All pricing as of August 2026 is quoted; no list pricing is published.
Value assessment: Regal's economics rest on replacing or absorbing contact center spend rather than adding to it. Handling a meaningful share of conversations with AI while keeping humans for what needs them changes the cost structure of an operation, and event-driven timing improves conversion on outreach that would otherwise be batched and late. The commitment is correspondingly larger: this is a platform migration, and it only pays back at volumes where contact center cost is already significant.
Strengths & limitations
Strengths
- AI and human agents on one platform with shared context, rather than automation bolted beside a contact center.
- Event-driven outreach triggered by behavior, which materially outperforms batch calling on timing.
- Multi-channel journeys covering voice and messaging under one set of rules.
- Consent, frequency, and calling window enforcement built in rather than left to process discipline.
- Customer profile layer gives both AI and human agents the same view.
- Strong fit for regulated consumer sectors where compliance evidence matters.
Limitations
- Enterprise commitment with quoted pricing and a real implementation project.
- Overkill for businesses wanting only a voice agent.
- Migration from an existing contact center is disruptive and should not be underestimated.
- Not a developer platform for embedding voice in products.
- Outbound calling remains constrained by regulation regardless of platform capability.
- Combined pricing components make cost comparison against simpler vendors difficult.
Head-to-head comparisons
4 alternativesRegal vs Retell AI
from From roughly $0.07 per minute combined, with free credits to startDifferent scopes. Retell provides voice agents that a team integrates into its own operation, priced per minute. Regal provides the operation: routing, human agents, journeys, consent, and reporting, with AI as one part. Teams with an existing contact center that want automation choose Retell; organizations rethinking the contact center itself consider Regal.
Full Regal vs Retell AI comparisonRegal vs Invoca
from Quoted; enterprise contracts typically starting in the low thousands of dollars per monthBoth serve high call volume consumer businesses but from opposite directions. Invoca analyzes inbound calls for marketing attribution and quality without handling them. Regal handles conversations with AI and human agents and orchestrates outreach. Some organizations run both, with Invoca measuring marketing effectiveness and Regal running the contact operation.
Full Regal vs Invoca comparisonRegal vs Twilio Voice
from $1.15 per month per local US number, plus $0.0140 per outbound minuteTwilio supplies the telephony primitives that platforms like Regal build on, and remains the right choice for teams building a bespoke solution. Regal supplies the finished operational platform including agents, journeys, and compliance. The decision is the familiar build versus buy question, with contact center complexity making buying more attractive than it first appears.
Full Regal vs Twilio Voice comparisonRegal vs Thoughtly
from From roughly $50 per month with included minutes, plus per-minute usage beyondBoth handle outbound and inbound at scale, but the trigger differs. Regal fires conversations from customer events such as an abandoned application or a failed payment, and routes between AI and human agents on one platform sold on quoted contracts with implementation. Thoughtly runs list-based campaigns and inbound answering from about $50 per month, self-serve, with no human agent workspace underneath. Operations replacing a contact center take Regal; teams wanting measurable campaign calling without that commitment take Thoughtly.
Full Regal vs Thoughtly comparisonImplementation & onboarding
- Setup time
- Months for a full deployment. Event integration, journey design, agent configuration, human agent migration, and compliance review each take real time.
- Learning curve
- Substantial across roles. Operations teams learn journey design, agents learn a new workspace, and compliance teams need to understand how rules are enforced in the platform.
- Onboarding
- Structured implementation with dedicated resources is standard and effectively required at this scope.
- Migration notes
- Migrate one journey or queue at a time rather than switching the contact center wholesale, and run AI handling on a subset of conversations with human review before expanding. Consent and suppression data must transfer accurately, since errors there are legal rather than operational problems.
Platform, API & security
- Platforms
- Web applicationTelephony and messaging infrastructureREST APIs and webhooks
- API
- APIs for events, profiles, journeys, and conversations, with CRM and warehouse integrations and webhook delivery of interaction data.
- Compliance
- TCPA and consent managementGDPRCCPASOC 2Sector-specific requirements on qualifying arrangements
- Data residency
- US-centric with enterprise arrangements for specific requirements.
- SSO
- SAML single sign-on standard on enterprise agreements.
- Security notes
- Consent tracking and calling window enforcement are enforced at platform level with audit trails, which is the practical requirement in regulated outbound calling where individual violations carry statutory penalties.
Support & resources
- Channels
- Dedicated success managementTechnical supportImplementation services
- Documentation
- Administrator and developer documentation covering events, journeys, agent configuration, and integrations.
- Community
- Presence in contact center and revenue operations circles rather than developer communities, with published material on AI and human blending.
Company
- Founded
- 2020
- Headquarters
- New York, United States
- Ownership
- Private, venture-backed
- Employees
- ~150 (est. 2026)
- Funding
- Raised venture funding including Series A and B rounds.
Timeline
- 2020Founded to make outbound customer contact event-driven rather than list-driven.
- 2022Expands into full contact center capability with human agent tooling and routing.
- 2024AI voice agents become central, blended with human agents on the same platform.
- 2026Positioned as an AI-first contact center for consumer businesses with high conversation volume.
Integrations
- Salesforce
- HubSpot
- Segment
- Snowflake
- Twilio
- Zapier
- Zendesk
- Stripe
Frequently asked questions
10 questionsWhat is Regal?
Regal is an AI-first contact center platform. It combines AI voice and messaging agents with human agent tooling, event-driven outreach triggered by customer behavior, a customer profile layer, and compliance controls, so conversations are routed to AI or people depending on what the situation needs.
How is it different from a voice AI platform?
Voice AI platforms provide agents that a team integrates into an existing operation. Regal provides the operation: routing, queues, human agent workspaces, journeys, consent enforcement, and reporting, with AI agents as one component. It is a platform decision rather than a tool purchase.
What does event-driven outreach mean?
Calls and messages are triggered by what a customer just did, an abandoned application, a viewed page, a failed payment, rather than by a list processed later. Timing is one of the largest determinants of contact success, and reaching someone minutes after they acted converts far better than reaching them the next day.
How much does Regal cost?
Pricing is quoted and combines platform fees, agent seats, and usage for AI conversations and telephony, under annual enterprise contracts with implementation. There is no self-serve tier, and comparisons against per-minute-only vendors require breaking the quote into components.
Who is it for?
Mid-market and enterprise consumer-facing operations with substantial call volume, particularly in insurance, financial services, healthcare, education, and home services. Small businesses wanting an answering agent should look at packaged voice products instead.
How does it handle handoff between AI and humans?
Escalation carries the conversation, customer profile, and event history to the human agent, so the customer does not repeat themselves. That shared context is the main argument for having both on one platform rather than integrating an AI agent alongside a separate contact center.
Does it help with calling compliance?
It enforces consent, calling windows, and frequency rules at the platform level with audit trails, which matters because outbound calling violations carry statutory penalties. The legal obligations remain the operator's, but enforcement in software is considerably more reliable than enforcement by process.
Can it replace our existing contact center?
That is the intended deployment for many customers, but it is a migration project rather than an addition. Expect months of work covering event integration, journey design, agent transition, and compliance review, and plan to migrate one queue or journey at a time.
Does it work for inbound as well as outbound?
Yes, with AI agents answering inbound calls and routing to humans as needed, using the same profiles and reporting as outbound journeys. Handling both directions on one platform is part of what distinguishes it from outbound-only or answering-only products.
Do customers know they are speaking with AI?
They should be told, and disclosure requirements are expanding across jurisdictions. In regulated consumer sectors particularly, undisclosed automation is a compliance risk as well as a trust problem, and disclosure should be configured as standard rather than considered optional.
Editorial verdict
Regal is arguing something more ambitious than most of this category: that AI agents should not sit next to a contact center but inside one, sharing routing, profiles, consent rules, and reporting with the humans they escalate to. That argument is correct, and the event-driven trigger model addresses the other half of the problem most voice platforms ignore, which is that timing determines outcomes more than script quality does. The price of that ambition is scope. This is a platform migration with implementation, compliance work, and a quoted enterprise contract, which makes it irrelevant to anyone below serious conversation volume. For consumer businesses where the contact center is a major cost and a major revenue channel, it is one of the more coherent propositions available.
Written by the SaaSTracker editorial team. Awards, when shown, are judged against the published criteria in our methodology.