AI Sales Engine

The system researches suitable companies, keeps the evidence attached and prepares the next action. Your team controls who to approach and what gets sent.

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The pain

Salespeople spend their day searching for new clients, checking the status of leads, and following up to close deals, not selling.

The result

The system finds suitable companies, verifies contacts, sends a relevant first message, watches replies, and keeps every opportunity in one clear stage.

How it works

The added value is in the criteria. Before the system contacts anyone, it defines what a good lead looks like for your business and scores every company against those parameters. This is what makes the results useful rather than generic. We agree what counts as a qualified match and measure the rate during the pilot. The salesperson receives a qualified lead with a specific reason for contact, ready for a real conversation.

Define who matters
A precise research brief
Find and verify
A defensible shortlist
Review and continue
A useful human conversation

Scope, savings and a working example

A working example

Monday 9am. Five new leads needed by Friday. The salesperson opens LinkedIn and starts scrolling. Two hours later: three names, no verified contacts, and no clear reason to reach out.

Every week, sales teams lose hours to three tasks that should not require human attention: finding new leads worth contacting, tracking where each conversation currently stands, and writing follow-ups to keep deals moving. The more leads in the pipeline, the more time disappears into tracking and administration instead of actual selling.

Savings to measure

Less time spent searching for new clients and verifying contacts manually
More focused conversations. Leads are pre-qualified before the salesperson calls.
Fewer wasted calls on contacts who are not ready or not relevant

Exact savings depend on your industry, current process, and lead volume. We estimate together before launch. No specific number applies to every business.

What the system handles

Find companies matching your approved criteria
Verify contact availability from public sources
Log replies and update pipeline stage
Send follow-up reminders on open leads

What your team controls

Review and approve campaigns before sending
Handle uncertain or sensitive replies personally
Manage pricing and negotiation yourself

Best fit: B2B services · Equipment & machinery · Real estate · Wholesale

Reference: built and tested on Fable Labs' own outreach process. Data and results are ours, available for review.

Try the workspace

Choose a company, inspect its signal, then prepare and review a first message.

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Sample data

FableLabsDemo workspace

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Sales workspace

AI Sales Engine

Sample data

Research3

Review0

Outreach0

Sales handoff0

Business typeTeam size3 sample matches

Education · 18 people

Northstar Learning

Research

Why approach this company?

A second location adds enquiries and scheduling work. A shared intake process could help the team prepare students consistently.

Opening a second teaching centre

Sample company announcement · fictional evidence

Our second centre opens next term, with additional evening classes and a new admissions team.

A signal suggests relevance; it does not prove buying intent.

Operations managerContact checked

First message

The system prepares a draft from the selected company signal. You decide what goes out.

Activity history (1)

Sample company added to research.

About this example

Sample data only. Companies, sources, contacts and replies are fictional. No live research, AI generation or messages are sent. Changes reset when you reload.