The words we use, defined.

Atender's in-workspace AI assistant for human agents. Surfaces relevant knowledge, drafts suggested responses from context, and stays active alongside the agent — so humans pick up conversations without starting cold.

Specialist AI agents trained per domain (billing, technical, account, etc.) using your knowledge base and guardrails. Each agent routes incoming conversations to the right specialist automatically and resolves routine volume instantly across every channel.

The layer that decides when an AI conversation hands over to a human. Analyzes sentiment, frustration, stalling, and compliance-risk signals in real time; triggers a hot, cold, or async handover when any threshold is crossed.

Atender's live operations dashboard. Shows every AI and human conversation in real time — queue depth, agent availability, AI activity — so supervisors can peek, reassign, or intervene in any conversation instantly.

The unified environment where AI and human agents work on the same conversations with the same context, knowledge base, and tooling. No handoff friction between automation and human judgment.

Atender's 24/7 platform-monitoring function. Watches uptime, latency, error rates, queues, and jobs; runs client runbooks on alert; coordinates incident communications and status-page updates while engineering resolves root cause.

Atender's flexible engagement model starting at 20 hours/month. Works as a quick start for smaller companies, as a flexible resource pool layered on dedicated agents to absorb spikes, or as extra hands for routine back-office work — without hiring or attrition cycles.

A workflow where trained humans review AI-generated responses before they reach customers — approving, editing, or handling escalations. Every correction becomes a training signal that makes AI more accurate over time; critical for high-stakes and regulated interactions.

Shared, brand-consistent response templates used by both AI and human agents. Ensures new agents have the same tooling as your most experienced person from day one, and that responses stay on-voice across channels.

A post-interaction survey measuring customer satisfaction, typically scored 1–5. In Atender, surveys are automatic after AI- and human-resolved conversations, collected in any language your customers speak, and tracked by channel, team, and agent.

One unified conversation thread per customer across email, live chat, WhatsApp, SMS, voice, Messenger, Instagram, and more. The conversation follows the customer — not the channel — so no context is lost when they switch from chat to email to phone.

Traditional outsourced labor working in its own tools with its own data, creating a gap between the brand and the outsourced experience. Atender's managed teams are distinct: they work inside your Atender workspace with your AI, knowledge base, and QA standards — no brand gap.

Second-line technical diagnosis — APIs, webhooks, containers, Kubernetes, CI/CD pipelines, cloud resources (AWS/GCP/Azure), databases, DNS, SSL, CDNs, and integrations. Escalations to engineering come with logs, traces, and reproduction steps.

Automated phone menu system that routes callers by input. Atender's visual IVR builder lets ops teams design call flows by dragging and dropping nodes — no vendor consultants, no weeks of lead time.

The moment a conversation transfers from AI to a human agent (or between human agents). In Atender, handovers carry full context — conversation history, customer profile, AI-suggested responses — so the receiving agent never starts cold.

Resolving a customer issue on the first interaction, without callbacks or escalation. A core metric in customer service; Atender improves it via AI that answers instantly, shared knowledge base, and human agents backed by Sidekick.

Preventing a support ticket from being created — usually via self-service knowledge base, AI resolution, or in-product guidance. Lowers volume without lowering service quality; measured alongside CSAT so quality doesn't slip.

A response or resolution-time commitment tracked per channel and customer tier. In Atender, SLA policies drive routing and alerting so nothing falls through the cracks when volume spikes.

A structured store of articles and guidance powering both AI agent responses and human agent search. Update an article once and every agent — AI and human — learns immediately; no retraining cycle.

A support team recruited, trained, managed, and scaled by the vendor on behalf of the customer. Atender's managed teams work inside the Atender platform — same AI, same knowledge base, same Monitor — so they feel like your team, not an outsourced one.