Get started with Callario

Callario is one platform behind a single data model: inbox, autonomous AI agent, copilot, RAG knowledge, no-code workflows, CRM, routing and SLAs, reporting, and CSAT all read and write the same contacts, conversations, and tickets.

That means you don't wire integrations between your own modules. Connect a channel and the AI agent, the inbox, routing, and reporting all see it at once. This orientation walks the path most teams take to go live, in order.

Callario is in supervised alpha. Start in a sandbox, keep a human in the loop, and expand the AI's autonomy as you build trust in its answers.

Bring your support surfaces into one inbox. The web chat widget is the fastest place to start: drop it on your site or app and you have a live channel in minutes.

Email connects through a per-tenant inbound address with reply parsing and threading, so customer replies land on the right conversation instead of spawning new ones. Other channels attach to the same unified feed.

Voice is in early access. If voice matters to your rollout, raise it during onboarding rather than planning around it as generally available.

The AI is only as good as what it's grounded in. Bring in your knowledge base — articles, help content, and policies — so answers stand on your sources rather than the model's guesswork.

Knowledge feeds the RAG layer that the agent and copilot both draw from. Curate it: accurate, current articles produce grounded answers, and stale ones produce confident mistakes. Treat knowledge ingestion as the highest-leverage step you take.

You can scope what a given agent is allowed to use — specific articles, categories, or the whole base — so different agents answer from the right slice of your content.

Define the agent's instructions, tone, and the knowledge it's allowed to draw on. Give it a clear job and clear boundaries rather than a vague persona.

Decide its autonomy: what it can answer on its own, when it must hand off to a human, and which tools or actions it's permitted to take. Handoffs are a feature, not a failure — and they're never billed.

Test in the sandbox with full-history dry runs before you publish. A publish gate stops an under-configured agent from going live; clear it deliberately.

Guardrails are always on: PII redaction, jailbreak resistance, and grounding checks run on every answer so the agent stays inside the lines you've drawn.

Set spend caps and alerts before you go live. Choose a monthly ceiling and an alert threshold so AI spend stays predictable and you're warned in advance — both ship on every plan.

Remember the billing model while you tune: you're charged about $0.99 only on a verified resolution, and $0 for handoffs, silence, and low-confidence answers. Configuring conservatively costs you nothing extra.

Publish the agent, route real traffic to it, and watch it work. Routing and SLAs distribute what the AI hands off to the right humans automatically.

Use the agent-and-tool trace and the resolution receipts to review what the AI did and why. Reporting and CSAT show whether it's actually helping, and the efficacy view keeps you honest about it.

Expand autonomy gradually. Start narrow, verify the receipts, widen the agent's scope as the evidence supports it. Supervised rollout is the intended path, not a limitation.