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Chat Core — Orchestration Engine for Sessions, Routing, Handoff & Governed AI | Velaxe

Chat Core

Chat Core vs Google Dialogflow CX

Dialogflow CX is a powerful state-machine bot builder. Chat Core is the orchestration layer for all conversations—owning sessions, routing, handoff, guardrails, and event fan-out—while supporting CX/Rasa/LLM tools as plug-in actors.

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Who this comparison is for

Ops leaders needing deterministic bot→human handoff with SLAs Platform teams orchestrating multiple bots, channels, and agents Enterprises standardizing guardrails and analytics across bots

Chat Core highlights

  • Omnichannel session manager + auditable handoff contracts
  • Pipeline: detect → enrich → decide → act → learn with plug-in nodes
  • Event bus (webhooks, SSE, EventBridge/Kafka) and InsightLake metrics

Google Dialogflow CX highlights

  • Graph-based dialog builder with NLU intents and flows
  • Native telephony/voicebot tooling in GCP

Capability matrix

7 rows
Capability Chat Core Google Dialogflow CX Notes
Durable session orchestration (multi-channel) Native Partial CX sessions per agent/bot; cross-system stitching via custom work
Deterministic bot→human handoff (SLAs/queues) Native Partial Requires external contact center or custom glue
Multi-bot routing (LLM/CX/Rasa/flows) Native Partial Router/skills vs intent handoff patterns
Guardrails (moderation, DLP, prompt firewall) Native Partial GCP moderation available; orchestration-wide policies in Chat Core
Event streaming (SSE/Kafka/Webhooks) Native Partial Pub/Sub oriented; externalization needed for UI/workflows
Agent desk integration (queues/macros/SLA) Native Add-on Chat Core → LiveConnect/Agent Desk vs adapters to CCaaS
A/B routing & cost controls Native Partial Experiments across models/routes vs flow comparisons
  • Matrix tokens: full/partial/none/native/addon/self_hosted/config-dependent.
  • Dialogflow CX excels at bot design; Chat Core focuses on cross-bot orchestration, governance, and handoff.

Total cost of ownership

Teams keep CX for dialog design while lowering glue-code by letting Chat Core own sessions, routing, safety, and handoff. This reduces custom middleware and speeds rollout across channels.

Assumptions

  • 3 bots (CX/LLM mix), 5 channels, 50k sessions/mo
  • Existing GCP footprint; need human handoff + governance

Migration plan

From Dialogflow CX · Keep CX bots; place Chat Core in front for orchestration & handoff

  1. 1

    Register CX as an Actor in the Chat Core pipeline (tool/function call)

  2. 2

    Configure routing rules and confidence bands; define handoff queues

  3. 3

    Enable webhooks/SSE for inbox UIs; turn on guardrails & cost limits

Security

  • Region-pinned storage, RBAC, audit trails, DLP redaction
  • HMAC webhooks and idempotent intake

Evidence & sources

Claim Value Source
Handoff contracts Reason, macros, do/don’t, tool blocklist product_docs
Auditable and reversible
Event bus options Webhooks, SSE, EventBridge/Kafka product_docs
CloudEvents JSON

About Chat Core

Chat Core decides what happens next in any live conversation. It stitches identity across channels, maintains durable sessions, detects intent and sentiment, calls tools and knowledge bases, and chooses between automated replies or human handoff with clear SLAs. Operators get routing/skills rules, cost & safety guardrails, experiments, and an orchestration trace for explainability.

Tightly integrated with PulseGate for transport, LiveConnect for real-time inbox, Agent Desk for tickets, FlowForge for automation, Chronicle for audit-ready timelines, and InsightLake for analytics—so you can ship omnichannel support that scales safely.

See orchestration + CX together