Configure a Team of AI Agents That Qualify Leads For You

It's built from four signals captured during the conversation — intent, confirmed budget, fit against your ideal customer profile, and urgency — each saved with ##save_custom_field## and ##add_label##. Because the AI lead score calculation methodology lives in the system prompt, you can read and adjust exactly how it's weighted.

It's lead scoring software in the sense that the scoring logic, labels, and thresholds are configurable inside the platform — no separate scoring engine to buy or maintain, and no data science team required to stand it up.

Custom fields, labels, and routing rules are the core AI tools lead scoring relies on here — a lead's score can trigger a label like "hot-lead," which then triggers a routing rule, which then triggers a handoff, all inside the same system prompt.

Yes — since the scoring rules are written in plain language in the system prompt rather than buried in a fixed model, adjusting how much weight urgency or budget carries is a matter of editing the instructions, not retraining anything.

It updates as the conversation happens — each ##save_custom_field## and ##add_label## action fires the moment a signal like budget or urgency comes up, so a lead's score and labels are current the instant a routing rule needs to check them, not calculated after the fact.

Both — the AI sales automation handles the repetitive parts of the conversation (answering pricing questions, checking availability, booking a call), while ##assign_human_member## or ##assign_human_role## brings in a real person for the actual close.

Yes — configure separate AI sales agent instances, each with its own system prompt and pricing knowledge, then use routing rules to send a conversation to the right one based on product line, language, or region.

The current agent triggers ##transfer_agent## to hand the conversation to another AI agent — for example, the Frontline Agent transferring a budget-confirmed lead straight to an AI sales agent, without the lead repeating anything they've already said.

Yes — offering real calendar slots the moment a lead is ready is one of the highest-leverage forms of AI sales automation, since it removes the multi-day back-and-forth that usually happens over email just to schedule a call.

Both — once the Frontline Agent hands off a budget-confirmed lead, the AI sales agent is built to work through pricing questions and common objections as part of AI sales automation, not just recite a price list.

Automated Follow-Ups is a clean example — pre-approved WhatsApp templates automatically re-engage a lead who went quiet, on a schedule you set, without anyone on your team remembering to follow up manually.

No — automated lead qualification here means writing plain-language instructions plus ##action## tags chosen from autocomplete. No code is required to configure scoring, routing, or handoff.

Yes — ##call_http_api## pushes a captured, scored lead straight to a CRM or webhook mid-conversation, and Google Sheets Sync offers a zero-setup alternative if you don't have a CRM yet.

Whatever gets saved via ##save_custom_field## — including the lead score — can be pushed out through ##call_http_api##, so downstream systems see the same score your routing rules are acting on.

Yes — WhatsApp Flows lets the agent drop a native in-chat form into the conversation for structured fields like name or budget, so automated lead qualification isn't limited to free-text answers when a form is faster for the lead.

Both are connected — the moment lead qualification automation confirms high intent, the Booking Agent can offer real calendar slots in the same conversation, so qualifying and scheduling happen without switching tools.

They're two independent controls. Pause Bot stops your automated bot flows; Pause AI stops the AI agent's replies — so you can pause just one or both while your team handles a sensitive or high-value lead. Resume Bot and Resume AI switch each one back on, with no need to permanently disable your setup.

Inbox IQ reads the latest messages on a thread and gives your agent a short summary, a lead score out of 100, churn risk, sentiment and trend, whether the person is already a customer, and one recommended next action — coupon, escalate, upsell, or an information request. Your agent knows how to open the conversation before typing a word.

The Shared Inbox includes a lightweight conversational CRM beside every chat: pipeline, stage, deal value, owner, lead score, source, and expected close. AI can autofill the deal fields from the conversation, and you can open the Kanban board without leaving the inbox. If you already use an external CRM, ##call_http_api## can still push the same lead data out.

Yes — conversations from all five channels land in one shared inbox. Your sales and support team work from a single queue, with filters like Mine, Unread, Important, and Resolved, instead of juggling five separate apps and losing leads between them.

Set a follow-up right from the conversation with a date and time, a reason, and an internal note — or tap a quick option like 1 Hour, 4 Hours, or 1 Day. You can also start a message sequence, type / to send a saved canned reply, or send a bot flow, template, or WhatsApp Flow now or scheduled for later, all from the same thread.

No — the entire AI lead score calculation methodology is configured through the system prompt and custom fields inside the platform. No separate scoring model, no engineering ticket required.

It escalates — ##assign_human_member## or ##assign_human_role## hands the conversation to your team, with ##add_note## capturing context so whoever picks it up isn't starting cold.

Often more so — a small team feels a slow response the most. An AI digital employee for sales lead qualification means no lead waits on one person's calendar, and the team only spends time on conversations already confirmed as worth having.