The enterprise AI voice shortlist is getting a new shape. Cognigy, Kore.ai, and PolyAI remain useful reference points, but 2026 buyers are also comparing Parloa, Sierra, and Decagon: a voice-AI-native enterprise platform, an expert-serviced customer-service agent company, and a no-code support-agent builder. This is a vendor-on-vendor comparison first. The six-row table below focuses on deployment posture, not invented pricing or a claim that one vendor fits every contact center.
At a glance: three different buyer motions
| Criterion | Parloa | Sierra | Decagon |
|---|---|---|---|
| Prebuilt enterprise agents | Partial — enterprise agent platform with reusable configurations; expect deployment work | Partial — agents are shaped around each enterprise's service operation, with expert implementation | Partial — teams configure support agents for their own use cases in a builder |
| BYO LLM posture | Partial — model orchestration is part of the platform; confirm available model choices for the proposed deployment | Partial — model choice is not the headline buying distinction; confirm the supported configuration | Partial — no-code agent building is the public posture; confirm model controls during evaluation |
| Telephony ownership | No — connects to a customer's contact-center and telephony estate | No — an agent layer for customer service, not a wholesale voice carrier | No — a support-agent platform, not a wholesale voice carrier |
| SIP/BYOC | Yes — voice deployments integrate with enterprise telephony; validate the target SIP and carrier design | Partial — voice is part of the service-agent story; validate the required carrier and SIP path | Partial — voice availability and telephony fit depend on the deployment; validate SIP/BYOC requirements directly |
| Omnichannel breadth | Yes — voice and digital customer-service channels | Yes — customer-service agents across digital and voice interactions | Yes — support agents across digital channels, with voice as part of the broader service motion |
| Deployment model | Enterprise cloud deployment, with architecture and residency requirements confirmed in procurement | Enterprise SaaS with hands-on implementation and service design | SaaS platform configured by the customer, with enterprise rollout support as needed |
Cells are categorical, not a substitute for a solution design. Product packaging and supported integrations change; buyers should validate the exact models, contact-center connectors, channels, deployment controls, and SIP requirements in a current vendor evaluation. None of these rows makes a pricing or performance claim.
The archetypes behind the shortlist
Parloa: voice-AI-native enterprise automation
Parloa is a Berlin-based enterprise AI company whose product is organized around AI agents for customer service, including voice. That voice-first history matters when a buyer starts with high-volume calls, natural-language self-service, and the need to connect automation to an existing contact center. Its enterprise partnerships and integration posture make it a fit for teams that want an AI agent program designed around incumbent customer-service infrastructure, rather than a generic bot builder. Expect to scope the integration and operating model with the vendor; a prebuilt agent does not remove the work of matching it to a company's policies and systems.
Sierra: expert-serviced customer-service agents
Sierra's approach pairs an AI customer-service platform with substantial design and implementation work for the enterprise. That model suits a company that wants agents to reflect its service policies, brand, and business systems, and is prepared to involve a vendor team in shaping the rollout. Buyers should compare the degree of control they retain over prompts, tools, models, and ongoing changes, alongside the implementation support. Sierra is not simply a self-serve voice platform: its value proposition is the managed path from customer-service use case to production agent.
Decagon: a no-code support-agent builder
Decagon puts the agent-building workflow closer to the support team. A no-code approach can suit organizations that want service operations staff to configure and refine agents without routing every iteration through a large software project. The fit depends on whether the team's channel mix and contact-center requirements align with the platform's supported integrations. Buyers with voice at the center should validate telephony routing, escalation, and SIP/BYOC specifics in a technical evaluation rather than infer them from the phrase “AI agent.”
How to use the table in a shortlist
Start with the work to automate, not a vendor's label. For a voice-led program integrated with an established contact center, examine Parloa's voice and telephony design. For a high-touch enterprise service transformation, assess Sierra's implementation model and how the customer team governs changes after launch. For support teams seeking direct control over agent configuration, test Decagon's builder against real customer conversations and escalation paths.
Then run the same proof-of-fit across all three: one representative call or support interaction, the systems the agent must read or update, a human handoff, failure recovery, and the controls the tenant owns. Ask each vendor to show the supported model options and production deployment boundaries for that exact workflow. A categorical comparison narrows the questions; it does not replace a hands-on evaluation.
Where Devotel Orbit fits
Devotel Orbit is a different buying frame for teams that want voice AI agents and the communications platform underneath them on one account. The dashboard brings agent configuration together with voice and messaging surfaces: see the Agents workspace and Voice workspace. Orbit also includes customer data and message channels, so the team can evaluate agents, telephony, and channel operations as parts of one platform rather than selecting a specialist agent vendor alone. The right fit depends on the buyer's operating model: a team specifically seeking a specialist implementation should assess these vendors on their own terms; a team seeking agents alongside full telephony and channels should include Orbit in its platform evaluation.
For the earlier enterprise shortlist, see Cognigy vs Kore.ai vs PolyAI. For the broader product-shape distinction, read AI-agent-first vs UCaaS incumbent.
Frequently asked questions
Is Parloa, Sierra, or Decagon a wholesale voice carrier?
No. They are AI-agent vendors, not substitutes for a wholesale carrier. Confirm how the selected product connects to your contact center, SIP trunks, and carrier arrangements.
Which vendor is built for voice?
Parloa has the clearest voice-AI-native enterprise posture of the three. Sierra and Decagon address broader customer-service automation; buyers should test their voice requirements, integrations, and handoff design directly.
Which offers no-code configuration?
Decagon is the clearest no-code support-agent archetype. Sierra emphasizes a more expert-serviced enterprise motion, while Parloa centers its enterprise voice-agent platform and integrations.
Can I bring my own LLM?
Do not assume that “AI agent platform” means unrestricted model choice. Ask each vendor to identify supported models, tenant-controlled configuration, data handling, and which choices are available in the deployment you are evaluating.
How should I compare deployment options?
Ask for the available hosting and residency models for your account, how integrations are operated, and which changes your team can make without vendor involvement. Confirm each answer in the proposed contract and technical design.
Published 13 October 2026.