Use AI to capture leads
Automate the repeat path and keep human handoff clear.
7-day free trial
What it handles
Works with
Why it matters
The practical reason to use it.
Manually handling lead capture in your customer portal is slow, inconsistent, and hard to scale.
How it works
A step-by-step look at the workflow.
Step 1
A visitor starts a conversation in your customer portal — the assistant identifies the intent and begins collecting visitor intent, contact details.
Step 2
The assistant checks your knowledge base and Knowledge base, CRM sync, Calendar booking to determine the right next step.
Step 3
Once enough context is gathered, the assistant captures leads with traceable decisions and stored context.
Step 4
If the request falls outside the assistant's scope, InsertChat escalates to a human via authenticated customer sessions with the full conversation summary.
Step 5
You review which lead capture conversations resolved end-to-end, where escalation happened, and what rules to tighten for better throughput on the next.
Task flow
How the assistant handles repeat work.
Lead Capture
The assistant captures leads in your customer portal by collecting visitor intent, contact details, and handoff readiness before it decides what should.
Customer Portal coverage
Deploy the same workflow across authenticated customer sessions when the workflow depends on account data and prior activity, so the task starts.
Audit-ready records
Keep the inputs, rules, and outputs attached to each automated action so compliance and operations teams can review what happened.
System actions and handoff
Once the conversation is ready, InsertChat can sync qualified conversations into your CRM or booking flow, and it can escalate to a.
Accuracy controls
How answers stay accurate.
Grounded in your sources
Responses stay tied to the docs, policies, and structured data your team already trusts for lead capture.
Rules before replies
Use approval logic, routing thresholds, and business rules before the workflow changes status or triggers downstream actions.
Human review when needed
InsertChat hands off the edge cases, exceptions, and judgment calls instead of pretending every conversation should be fully automated.
Visible automation performance
Track which conversations resolved end-to-end, where escalation happened, and what to tighten next for better throughput.
Add next
Useful next automations.
Route account-specific questions
Split high-intent conversations by territory, segment, plan fit, or product line without asking visitors to restart on a form.
Sync clean handoff notes
Push summaries, captured fields, and next steps into the CRM so reps pick up the conversation without manual copy-paste.
Trigger timely follow-ups
Use conversation signals to send reminders, booking nudges, or rep alerts while buying intent is still fresh.
Standardize pricing answers
Keep plan comparisons, qualification rules, and objection handling aligned with your latest sales narrative.
What you get
The changes teams should notice first.
- Less manual work on repetitive conversations
- Faster resolution without human bottlenecks
- Consistent execution every time, at any scale
- Clear visibility into what gets automated and what doesn't
The facts do the selling
Plan facts, platform capabilities, and worked examples — every claim here is checkable, not a pitch.
White-label included — never a paid add-on. Copyright removal from $98/mo. Full white-label — custom domain, branded portal, your-domain emails — from $198/mo.
The white-label wedge
Platform fact
Training runs on your sitemap, PDFs, docs, and YouTube transcripts. Answers cite the source pages they came from.
Trained on your content
Platform fact
Five clients at $300/mo on a $198/mo Agency plan is $1,300+ of monthly margin before usage.
A 5-client agency on one flat plan
Worked example
Your questions, answered.
Tap any question about the product, pricing, security, or setup to see a straight answer.
InsertChat
Answers about InsertChat
Hi! Tap any question below and I'll answer it for you.
Use AI to capture leads questions
Can an AI assistant capture leads without human approval?
Yes — you configure exactly which lead capture actions the assistant takes autonomously and which require human review. For example, the assistant can capture leads with traceable decisions and stored context on its own, but escalate edge cases based on thresholds you set. Routine lead capture cases resolve end-to-end while exceptions get flagged for a person to review.
How does the assistant know how to capture leads correctly?
The assistant is grounded in your knowledge base and Knowledge base, CRM sync, Calendar booking. It collects visitor intent, contact details, and handoff readiness before deciding the next step, and it can sync qualified conversations into your CRM or booking flow once enough context is gathered. It never improvises — it follows the sources and logic you configure, then keeps the next owner in the loop when the workflow needs a handoff.
What happens when the assistant can't handle a lead capture request?
InsertChat hands the conversation to a human via authenticated customer sessions with the full context already attached — the user doesn't repeat themselves. You configure when handoff triggers based on confidence thresholds, request complexity, or visitor intent, contact details, and handoff readiness that falls outside the assistant's scope. The result is a cleaner escalation instead of a dead-end chat.
Does lead capture automation work in your customer portal?
Yes. The assistant captures leads across authenticated customer sessions when the workflow depends on account data and prior activity. The same workflow, knowledge base, and escalation rules apply regardless of where the conversation starts, so the task execution stays consistent at any scale and across every channel you enable.
How do teams measure whether lead capture automation is working?
Teams usually measure resolution time, handoff quality, and how many conversations finish without manual re-entry. If those numbers improve, the workflow is doing real work instead of just deflecting messages. That makes it easier to expand the automation into adjacent steps once the first path is reliable.
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