Pitchly by Datics AI
Salespeople and BDC agents practice the call before the real one, scored on the dealer's own process.
Salespeople and BDC agents practice calls by voice with an AI shopper who follows the dealer's scenarios, and get a score on the dealer's own process that managers can review.
Built into your codebase and shipped under your name, on an engine we license to you.
lotline.example/training/roleplay
Pinecrest RV and Marine · Pitchly
DemoThanks for calling Pinecrest, this is Chris. Which model caught your eye, and how do you plan to use it?
Score: 3 of 5 steps on the dealer's call process
- Asked about use before price: done
- Set an appointment: done
- Did not confirm the shopper's name and number: missed
Scenario: price shopperScored on the dealer's processManager can review
Try it step by stepIllustrative demo on a fictional dealership. Not client work.
Try it step by step
Pitchly on a fictional dealer.
Pinecrest RV and Marine (fictional). Step through the conversation, then see what Pitchly hands back, the way your Build Sprint would build it on synthetic data.
lotline.example/training/roleplay
Pinecrest RV and Marine · Pitchly
DemoStep 1 of 5
Illustrative demo on a fictional dealership. Not client work.
What it hands back
lotline.example/training/roleplay
Roleplay scorecard · Price shopper
Pinecrest RV and Marine · Chris B.
- Greeting and name
- Thanked the caller and said who was speaking
- Done
- Asked about use before price
- Weekends with the kids
- Done
- Handled the price question
- Partly · moved on without coming back to it
- Check
- Set the appointment
- Saturday morning, on the water
- Done
- Confirmed contact details
- Missed
- Check
Scored against the dealer's own call process. The manager reviews and assigns the next scenario.
Illustrative demo on a fictional dealership. Not client work.
What it does
What Pitchly can do.
Voice roleplay with an AI shopper who follows the dealer's scenarios, scored against the dealer's own process, with coaching notes the manager can review.
Voice roleplay
Live calls with an AI shopper, in practice and coach modes, at set difficulty levels.
Your scenarios
Admins change shoppers, scripts and scenarios without a release.
Scored on your process
Feedback against the dealer's own steps, not generic coaching.
Manager view
Scores and notes by person and by team.
How it works
A realtime voice model plays the shopper from the dealer's scenario; after the call, the transcript is scored against the dealer's own steps and saved for the manager.
Built on a voice roleplay and scoring engine we have in production for sales agents.
Insurance Sales Lab
AI engine · Voice roleplay
Insurance agents practice calls with an AI prospect, scored on the company's script
Practice used to wait for a human coach, and feedback varied. Now agents call an AI prospect any time and get the same checklist score.
Insurance Sales Lab
Sales training · Real call recording
Real sales calls recorded from any meeting tool, never cutting the agent off
Real calls went unscored because agents use many meeting tools. Now one signed desktop app records both sides, and AI scores the call.
A leadership author's company
Practice apps · Phone, desktop and web
Leadership exercises on phone, desktop and web, shipped from one codebase for launch
The app existed only as a web prototype with a store deadline close; we shipped it to phones and desktops from the same code, no rewrite.
Why it sells
What Pitchly does for your business.
What your dealers get, and what it does for your renewals and pricing.
A training add-on
Practice sold per seat, inside the platform salespeople open every morning.
Ramp new hires faster
New salespeople practice the calls they will get before they take a real one.
Coaching managers can see
Scores by call step show who needs help, without listening to every call.
Controls
What Pitchly touches, and who approves.
Your dealers' data is not used to train models for anyone else and stays in your cloud. Built and tested on synthetic or test data.
Who uses it
Salespeople, BDC agents, sales managers
What it connects to
Your platform's users and teams, and the dealer's scripts
What a person approves
Managers set the scenarios and review the scores
Switch per dealer
On or off for each dealer, with data settings their admins control.
How to get it
Two steps to a finished Pitchly.
Start with a three-week Build Sprint. Add more only if you want it.
First · Build Sprint · $10,000 fixed
Every salesperson practices the call before the real one
- Voice roleplay
- Your scenarios
- Scored on your process
- In your staging, behind a feature flag
- Delivered as pull requests
- A test set your team reviews
- Week 1Setup
- Weeks 2 to 3Build
- You getPitchly in your staging and a fixed production quote
- Your time
- About 2 to 3 hours a week from a product owner
- Data
- Synthetic or test data, never your dealers' customers
- The fee
- Counts toward production
Then · Live in production
A finished product, yours to run
- Fixed quote
- Tested before launch
- Switch per dealer
- A finished, working Pitchly in your product
- Runs in your cloud, under your name
- Fixed quote, agreed before we start
Optional · Add more later
Only if you want it
More of Pitchly:
- Manager view
Another module:
- Each one quoted on its own
- Nothing ongoing unless you ask
Already built or tried AI? Get it scored with the AI Scorecard. Need something else? Start with a Planning Sprint.
FAQ
Questions about Pitchly.
Can managers change the scenarios?
Yes. Admins change shoppers, scripts and difficulty without a release.
Does it use our real call recordings?
Not in the Sprint. Scenarios come from your scripts; real call review can be added later with consent rules you set.
Which languages?
English first; other languages are scoped in the Product Review.
See Pitchly on your own product.
Bring your product and one workflow. In 30 minutes we look at where Pitchly fits, what it would cost to serve and what your dealers' security review will ask.
Calls run in US Central time. No generic AI presentation: we discuss your product, users and production constraints.