Proof
What the system has done, with the source next to every number.
One live engagement, three public products, and the readings they produce. Nothing here is a promise. Where we do not have the number yet, the tile says so.
Measured on the live engagement
companies researched
1,048
each with a legal identifier where one exists
addresses checked
2,320
1,120 of them named people
domains warmed
24
deliverability score, a B
70
50 before we fixed one record
deals closed
—
your sales team owns that part, and we will not claim it
One client, an industrial developer in northern Mexico. Read from the working files, not from a slide.
One record, one fix
The SPF fix that moved a domain two grades.
A customer domain came to us reading 50 on the checker, a D. One SPF record was wrong.
We fixed it before any warmup started. The same checker then read 70, a B. Nothing else had changed.
That is the whole shape of the work: find the gate that is failing, fix it, read again. The reading is the proof, not our word.
Before
50
deliverability score, a D
After
70
deliverability score, a B
What you see
Your team looks at the same screen we do.
The list as it fills, what each mailbox sent today, where every contact stands, and every reply with what it means. Anything we have not measured says so.
Your list
1,048
companies
Sending
600
emails a day
Handoff
60
seconds to your team
Public work you can inspect
The components of the machine exist on their own, under their own names. Two are open source. One is a paid product with its readings exposed as an API.
warming.email
Fixed-price domain warmup with readiness, health and state exposed as an API. The pool behind it has 24 domains in rotation.
email-intel
Open source. Reads who runs a domain's mail, grades SPF, DKIM, DMARC and STARTTLS, and parses headers. The same check we run before touching a customer domain.
Crawlio for Chrome
Open source. Connects an agent to the Chrome you already have open, so it reads the pages you are logged into and turns them into records with a source on every field.
The essay and the case study
How the machine is built and why it is engineering rather than marketing, written for a general reader, with the three layers of infrastructure as a case study.
How we measure
Three grades of address
Published on the company's site. Verified by its mail server. Inferred from a naming pattern. Only the first two are ever sent to.
Opens, twice
Total opens and opens excluding known proxies, side by side. No screen leads with open rate alone.
Readings, not reports
Reputation and placement are read against real Gmail and Outlook inboxes, daily. The cap for each mailbox is set by the reading.
Sources on every number
Every figure on this site is a proof entry with its status and the file it was read from. The build fails if a target is shown as a claim.
What we do not claim yet
We can show deliveries, opens and replies with confidence, because the machine measures them. We cannot yet show, across enough clients, how the volume converts into signed contracts, because the sales team owns that last step and the numbers are still coming in. The frame is settled. The evidence at the far end is not.
Get your own reading
The first screen of the plan reads the mail records of the domain you sell from. That reading is yours before any call.
Get your planTell us who you want to talk to.
Three screens, then a call. If outbound is not worth running for you, we say so on the call.
Already sending? Say so and we start from your numbers.