
Industries Email Deliverability
Sent isn'tthe same as delivered.
AI Engineering and software development for email deliverability companies.
Deliverability failures don't announce themselves - no bounce, no error, just a reply rate sliding in the spam folder. We're working with Emailmarketing.com and EmailDeliverability.com, the leaders in this field, helping them create the infrastructure behind the deliverability that drove over $250M in brand sales.


EmailDeliverability.comDeliverability, Built Into The Marketer's Editor
The deliverability software of EmailMarketing.com, Troy Ericson's group. We built the product: a Chrome extension that optimizes an email for inbox placement inside the marketer's own ESP editor, and the admin system behind it.
- 40+
- ESPs supported
- 640+
- Businesses on the software
- $250M+
- Generated for their clients
Why email teamstrust us with delivery.
A domain that slides into spam, or a complaint rate crossing Gmail's threshold, can undo a year of sending in weeks. This is why we pay special attention to the most sensitive parts of the system.
Failure here is silent
No bounce, no error, no alert: the message is accepted and filed where nobody looks. Reply rates drift for weeks while the team debates subject lines, and by then the damage is months old.
Reputation is earned per domain, per provider
Gmail and Outlook form separate opinions of your domain, your subdomains, and your IPs, and they do not share them. Volume pacing and keeping transactional mail away from marketing are infrastructure decisions.
Engagement is the ranking signal
Replies, deletions, and complaints all feed the filter's judgement of you. Sending to the unengaged part of a list drags down placement for the people who did want to hear from you.
The feedback loop is partial and late
Postmaster tools show yesterday, feedback loops cover only some providers, and open tracking stopped being reliable years ago. Nobody says why a message was filtered, so measurement is always indirect.
Authentication is table stakes now
Mail that still sends without SPF, DKIM, and an enforcing DMARC policy has already been placed by the bulk sender rules. One-click unsubscribe and a complaint rate under the threshold are the rest of the price of entry.
What deliverability demandsfrom engineering and AI.
01The authentication and policy baseline
Providers now refuse bulk mail that fails authentication, so SPF alignment, DKIM signing on every stream, and DMARC moved from monitoring to enforcement are the entry fee rather than an optimisation. Getting there takes an inventory of everything that legitimately sends on your behalf, because enforcement breaks whatever the inventory missed.
02Reputation as an operational metric
Deliverability collapses gradually and then suddenly, and the entire advantage is in noticing during the gradual part. That takes placement, complaint rate, and domain reputation tracked continuously, with alerting on the trend rather than the incident.
03List hygiene as a pipeline
Most reputation problems are a list problem nobody wanted to shrink a list to fix. Validation at capture, bounce and complaint handling that actually suppresses, re-engagement windows, and sunsetting rules have to run automatically, not as a quarterly cleanup.
04Send decisions with real feedback
Opens stopped being trustworthy years ago, and a model pointed at a broken metric will happily learn to game it. Which segment, at what cadence, and when to stop have to be modelled on replies and conversions, the outcomes a privacy proxy can't inflate.

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8 dedicated engineers across 3 projects, scaling the infrastructure that sends 40M emails per month.
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Frequently asked questions
Everything senders usually want to know before rebuilding their email infrastructure. Not here? Ask us directly.
Usually, but slowly and by sending less before sending more: authentication fixed, the list cut back to demonstrably engaged recipients, volume rebuilt on a warmup curve, and the damaged stream separated from the healthy one.
Anyone promising a fast fix is describing a new domain, which inherits the same problem in a quarter if the underlying sending behaviour doesn't change.
Within the rules of the market you're sending to, and those rules differ sharply. B2B outreach with a legitimate-interest basis, clear identification, and honest opt-out is workable in much of Europe; several jurisdictions are stricter, and some list sources are never acceptable anywhere.
We'll build the infrastructure and tell you plainly where a plan crosses a line. Purchased lists are the fastest route to the reputation problem in the previous answer.
Seed panels for directional placement, postmaster and feedback-loop data where providers expose it, and engagement patterns by provider as the strongest indirect evidence. Reply and click behaviour holds up where open rates no longer do.
None of that is exact, and we present it as an estimate with its error bars rather than a placement percentage that implies precision nobody actually has.
We also built and run MailGenius, the spam test that grades a message before it goes out, so this is a measurement layer we operate rather than one we read about.
It depends on volume, whether your streams need genuine isolation, and how much control you want over the sending path. High-volume senders with mixed streams usually benefit from separating transactional and marketing at the infrastructure level, whoever the vendor is.
We're not resellers and take no vendor commission, so the recommendation is whichever one fits, including staying where you are.
We have built that layer ourselves. InboxPro sends on infrastructure we wrote from scratch: KumoMTA on owned bare metal, its own egress IP estate, multi-tenant routing, warmup, and ISP feedback loops.
Yes, with a staged cutover: new sending infrastructure warmed alongside the old, traffic moved by segment starting with your most engaged recipients, and reputation watched at each step with a rollback point.
The failure mode is a big-bang switch that moves full volume onto cold infrastructure overnight. With planning, that is entirely avoidable.
You do. Code, trained models, pipelines, and documentation are yours, along with the infrastructure access to run them without us.
We hand over a codebase your own team can pick up. Nothing we build is designed to keep you dependent on us.



