Commercial Automation
AI Lead Operations System
Every inbound enquiry researched, qualified, and answered — with humans deciding where it matters.
The workflow
See the system
in context.
Explore an illustrative interface, then go deeper into the architecture and decisions behind the work.
- Lead received
- Company research
- AI qualification
- CRM record
- Personalized message
- Meeting workflow
A new enquiry
From your website
“We’re moving every lead from email into our CRM by hand. Can you help us automate it?”
01 / Inside the system
The problem to solve
Inbound leads arrive across forms, email, and messaging channels. Each one requires manual research, a judgment call on fit, a CRM entry, and a first response — and the speed of that response largely determines whether the conversation happens at all.
In practice, research is skipped under load, qualification is inconsistent, CRM data decays, and follow-up is delayed by hours or days. The work is repetitive, but it carries commercial weight — which makes it a strong candidate for a governed automated system rather than a chatbot.
02 / Inside the system
How it fits together
- 01
Intake
Webhooks and inbox listeners capture enquiries from forms, email, and messaging channels into a single normalized event.
- 02
Enrichment
Company and contact context is assembled from external data sources — firmographics, size, industry, and public signals.
- 03
Qualification
A language model scores the lead against an explicit ICP rubric and returns a structured result — score, reasoning, and flags.
- 04
CRM Write
A typed, deduplicated record is created or updated. Every field written by the system is traceable to its source.
- 05
Drafting
A personalized follow-up is prepared using the enriched context — not a template with a first name merged in.
- 06
Approval & Booking
Outbound messages pass a human approval gate. Qualified leads route into a meeting workflow with calendar coordination.
03 / Inside the system
From input to outcome
Capture
An enquiry arrives through any channel and becomes a structured event with source metadata attached.
Research
The system assembles company context in seconds — the work a salesperson would otherwise do in fifteen minutes.
Evaluate
The lead is scored against the qualification rubric. Low-confidence results are flagged rather than forced through.
Record
The CRM is updated with clean, complete, structured data — the state the CRM should always have been in.
Respond
A contextual follow-up is drafted and queued for approval. Nothing sends without a human where that gate is configured.
Route
Qualified leads enter the meeting workflow; the sales team is alerted with full context attached.
04 / Inside the system
Decisions that matter
Structured outputs everywhere
Qualification returns a constrained schema — score, reasons, flags — never free-form text that downstream steps must parse.
Idempotent intake
Webhook handlers deduplicate on email and domain, so retries and double-submissions never create duplicate records.
Approval gate on outbound
Messages to prospects require human approval by default. Autonomy is expanded only where the client asks for it.
Full audit trail
Every decision — score, write, draft, approval — is logged with timestamps and inputs, so behavior is inspectable after the fact.
05 / Inside the system
When things go off-script
- enrichment miss
- Proceed with partial data and flag the record for manual review.
- model timeout
- Retry with backoff; escalate to the team if the lead remains unqualified.
- crm api failure
- Queue the write and retry; alert if the queue grows beyond threshold.
- low confidence score
- Route to a human with full context instead of guessing.
06 / Inside the system
What this demonstrates
Make the next move
What could this unlock for you?
A workflow in your business may look like this. Let’s explore what a useful system would involve.