Move your team from Voiceflow to Kore.ai.
Each person gets a short interview, then a personalized step-by-step guide showing exactly where their saved work, prompts, and projects land in Kore.ai — and the few things that need a manual step, walked through. You send one invite; nobody becomes the help desk, and nothing in Voiceflow is changed or cancelled. Want to see where you’re paying for both first? Run the free audit.
Both tools offer a no-code/low-code visual studio for assembling AI agents from building blocks. When moving from Kore.ai to Voiceflow: export any intent libraries and flow documentation from the Kore.ai Agent Builder (AI for Service/Work modules), then recreate conversation flows in Voiceflow's drag-and-drop canvas using its Playbooks (for agentic LLM-driven paths) and Workflows (for deterministic scripted steps). Kore.ai's 'scripted + reasoning hybrid' maps directly to Voiceflow's agentic/deterministic toggle. When moving from Voiceflow to Kore.ai: export Voiceflow flows as JSON or PDF screenshots, then rebuild in the Kore.ai Agent Builder within the appropriate module (AI for Service for customer-facing, AI for Work for employee-facing). Both support mixing scripted and LLM reasoning paths, so logic transfer is conceptually straightforward; the main manual effort is recreating intent examples and slot definitions.
- Warning: Kore.ai's Agent Builder is module-scoped (AI for Service vs. AI for Work) so flows built for one cannot be reused in the other without adjustment; Voiceflow has a single unified canvas for all agent types.
- Warning: Voiceflow's agent builder includes an integrated knowledge base natively; Kore.ai's knowledge base is a separate configuration step in the same studio.
- Warning: Kore.ai benchmarks '1 developer achieves what 5 previously required' but Voiceflow specifically targets non-developer builders; teams without engineering support may find Voiceflow's UX more accessible.
Both platforms automatically score and analyze 100% of agent interactions rather than relying on manual sampling. Moving from Kore.ai to Voiceflow: export historical interaction data from Kore.ai's Quality Management dashboards (CSV or API if available) for record-keeping before switching; set up Voiceflow's Measure pillar in the new workspace to capture resolution rate, deflection, CSAT, response time, and token usage via its LLM-powered evaluations. Moving from Voiceflow to Kore.ai: note which automated metrics are tracked in Voiceflow's analytics dashboards, then configure the corresponding Kore.ai Quality Management scoring criteria and reporting dashboards in the AI for Service module. Kore.ai also surfaces ROI measurement tools for quantifying business impact, which has no direct Voiceflow equivalent.
- Warning: Kore.ai's quality management includes human QA workflow tooling (supervisor review, coaching flags); Voiceflow's analytics are primarily automated LLM-scored evaluations without a native human QA workflow layer.
- Warning: Voiceflow separates dev, staging, and production environments and tracks analytics per environment; Kore.ai's environment model may differ and should be confirmed during scoping.
- Warning: Analytics data retention limits and export formats differ by plan tier on both platforms; confirm retention SLAs before migrating historically important interaction logs.
Both platforms provide pre-built connectors to popular CRM, helpdesk, and business systems so agents can read and write data without custom code. Moving from Kore.ai to Voiceflow: audit your active Kore.ai connectors (Salesforce, ServiceNow, Zendesk, HubSpot, etc.) and identify which are available as Voiceflow native integrations (Salesforce, HubSpot, Zendesk, Shopify, Airtable, Google Sheets, Make, and Gmail are listed); for connectors not in Voiceflow's pre-built set, use the Conversations API or a middleware such as Make to bridge them. Moving from Voiceflow to Kore.ai: Kore.ai's Marketplace offers 200+ pre-built agents and 100+ connectors covering enterprise systems (SAP, Workday, ServiceNow, Oracle, ADP) that Voiceflow does not natively support; map each Voiceflow integration to the Kore.ai connector and configure it in the Agent Builder.
- Warning: Kore.ai exposes 9,000+ API actions across connectors; Voiceflow relies on its Conversations API for custom integrations, which requires more configuration effort for long-tail enterprise systems.
- Warning: Kore.ai's 200+ marketplace agent templates are purpose-built for HR, IT, and finance workflows (SAP, Workday, ADP, Oracle); Voiceflow's pre-built connectors skew toward SMB/e-commerce tools (Shopify, Google Sheets, Airtable) rather than ERP.
- Warning: Microsoft 365 deep integration (Teams, Azure AI Foundry, Copilot Studio) is natively listed for Kore.ai; Voiceflow's Microsoft channel support should be verified for Teams deployment if that channel is in scope.
Both platforms deploy customer-facing AI agents across web chat, voice, and telephony channels from a single build. Moving from Kore.ai to Voiceflow: document all active channels in Kore.ai's AI for Service module (chat widget embed codes, telephony SIP configurations, voice IVR settings), then redeploy the rebuilt agent in Voiceflow to its web chat widget and voice/telephony channels. Voiceflow's Conversations API handles any custom channel not covered by its pre-built set. Context-carry across touchpoints is native in both platforms. Moving from Voiceflow to Kore.ai: note channel configuration in Voiceflow's deployment settings, then configure the Kore.ai AI for Service channel integrations to match. Kore.ai adds outbound proactive campaign capability that Voiceflow does not expose as a distinct feature.
- Warning: Kore.ai explicitly supports outbound proactive campaigns within AI for Service; Voiceflow focuses on inbound and reactive deployments and does not list a proactive outbound campaign mode.
- Warning: Voiceflow rates its platform at 300,000 messages per minute with 10,000+ live agents; Kore.ai does not publish comparable throughput benchmarks, so high-volume contact centers should test Kore.ai capacity independently.
- Warning: Voiceflow voice widget targets ~500ms latency; Kore.ai latency benchmarks are not publicly listed and may differ by deployment region.
Both platforms target enterprise and regulated-industry buyers with audit logging, role-based access, and compliance certifications. Moving from Kore.ai to Voiceflow: export Kore.ai's audit logs and policy configurations before cutover, then configure Voiceflow's SSO, granular least-privilege access management, and audit logging (full project history with rollback). Voiceflow's compliance covers SOC 2 Type II, ISO/IEC 27001:2022, GDPR, and HIPAA; confirm the specific certifications your contracts require are present on both sides. Moving from Voiceflow to Kore.ai: replicate role-based access and governance guardrail policies in Kore.ai's centralized Admin Controls; Kore.ai enforces compliance at runtime (blocking non-compliant responses before they reach users) rather than as post-hoc logging, which is an architectural difference teams should validate.
- Warning: Kore.ai enforces governance guardrails at the moment of agent execution (runtime blocking); Voiceflow's compliance model relies on audit logging and access controls rather than real-time response filtering — teams in highly regulated industries should verify this distinction satisfies their compliance team.
- Warning: Kore.ai lists HIPAA-compliant modules for healthcare and banking-specific regulatory modules; Voiceflow lists HIPAA as a supported framework but does not separately call out vertical-specific regulatory modules.
- Warning: Voiceflow offers customer-managed encryption keys and CDN-backed WAF/DDoS protection as documented security features; Kore.ai's equivalent infrastructure-level controls are not publicly enumerated and should be confirmed via a security review.