Built to remove sourcing bias, not automate it
Here's exactly how the marketplace works: anonymized by default, built on a curated pool, and backed by a team that still gets involved when it matters.
Here's exactly how the marketplace works: anonymized by default, built on a curated pool, and backed by a team that still gets involved when it matters.
How TOAST TALENT works
No cold outreach to strangers. No names until she says yes. Here's exactly what happens.
1
Search
Describe who you need in plain English. Every card is anonymized: generic descriptors only, no names, no companies, no schools.
2
Unlock
Found someone promising? Spend an unlock to reveal her full profile and contact info.
3
Connect
Add her to your pipeline or ATS and reach out directly whenever you're ready.
Anonymized by default
No name, photo, or company logos until you unlock. You evaluate on merit first. The introduction happens after.
Opted-in only
Not scraped. These women chose to be discoverable. Response rates reflect that.
No placement fees
Pay for access. Find 40 candidates in a month and it's still the same subscription cost.
Recency signals
Every profile shows when it was last updated. No paying to contact someone who signed up three years ago.
Always growing
About 100 new members join every week. The search that came up short last quarter is worth running again.
Anonymization
Profiles hide name, photo, company names, and contact details until you unlock them.
What you see before you unlock
Role & company stage
Skills
Experience level
Salary benchmark
Last-updated date
For example: “Senior Engineer at a Series C fintech”
The result: the first decision gets made on merit. Does this person's experience match what we're looking for?
The pool
Women in tech across Canada have chosen Toast for the sponsorship, the advocacy, and the community that actually shows up for them. That relationship didn't come from a database scrape. It was built over years. Every candidate in the pool is there because she chose to be.
15,000+
Women in the pool
65%
In technical roles: software dev, AI engineering, DevOps, data
~100
New candidates joining per week
50/50
Canada and US split
How the pool breaks down
Years of experience
47.5%
of the pool sits at mid-senior level and above
Job function
36%
of the pool works in Engineering — Toast's single largest function
Pool composition
That combination, engineering depth plus concentration in the 4 to 12 year experience range, means the pool has real density exactly where clients struggle most: experienced women in technical roles who aren't visible on LinkedIn because they're not actively promoting themselves.
sits at mid-senior and above, disproving the idea that there aren't women at this level.
of mapped profiles are Engineering alone. Add Data at 12% and you're near half the pool in core technical functions, before Design, Product, or Tech Strategy.
Have a question we didn't cover above? Book a call and we'll walk you through it.
Create a profile and get discovered by hiring teams looking for candidates like you.
Your identity stays protected until you choose to share it.
