Florin Armasu, CEO and founder of Data Innovation and creator of the Sendability platform, has spent fifteen years building email infrastructure for brands including Nestle and Brown-Forman. In a conversation with Sophie Steffen for The Open Rate Club, he walked through the open source stack that his team uses in production – a collection of tools that would make most commercial ESP sales teams quietly excuse themselves from the room.
The Front End: Mautic as Campaign Orchestrator
The conventional wisdom in email marketing holds that you choose an ESP – Iterable, Braze, Salesforce Marketing Cloud, perhaps Klaviyo if you are feeling mid-market – and then you build your entire operation inside it. Armasu has taken a different path. The front end of his stack runs Mautic, an open source marketing automation platform that handles campaign orchestration, customer journeys, and segmentation. It is comparable to any of the commercial orchestrators. It does not, however, charge you per contact for the privilege of storing your own data.
This is not an academic exercise. Armasu runs this infrastructure for FMCG brands, agencies, and enterprise clients who have grown tired of the economics of commercial ESPs. The appeal is not ideological – he is not running open source software because he read a manifesto. The appeal is practical: when your data sits inside a vendor with a two-year retention policy, you lose the ability to analyze historical performance beyond that window. When your pricing is per-contact, you end up paying for unengaged subscribers you are not even emailing. When your infrastructure is shared, you inherit the reputation problems of strangers.
The Delivery Pipeline: KumoMTA, SparkPost, Amazon SES, and a Dinosaur
The delivery layer – the part of the stack that actually puts emails into mailboxes – is where things get interesting. The primary mail transfer agent is KumoMTA, an open source MTA built by a team of former SparkPost engineers. It handles the heavy lifting of SMTP delivery with the sort of fine-grained control that commercial platforms abstract away, because commercial platforms do not want you thinking about IP rotation, connection throttling, or per-domain sending limits. They want you thinking about subject lines and A/B tests. The infrastructure, in their view, is their problem. Armasu disagrees.
Alongside KumoMTA, the stack includes SparkPost itself, Amazon SES for volume distribution, and Qmail. Qmail was created in 1998. It is, by any reasonable measure, a dinosaur. It is also still running in production, still delivering emails, and still doing so with the quiet reliability of a piece of software that was designed before “move fast and break things” became an acceptable engineering philosophy.
“Try to integrate your tools, the six, seven, eight, four tools, whatever number the tools you are using, into one. It’s easier and easier to do with AI agents because it could give you more control and more flexibility if you have everything incorporated into one dashboard.”
The orchestration layer between MTA and campaign front end is handled by their Volume Deliverability Manager Suite, which solves a problem most marketers do not even know they have: determining the safe volume to send on each mailbox provider based on current reputation. You cannot blast your entire database through Gmail if your Gmail reputation is mediocre. The suite calculates, per provider, how many emails you can safely send and to which engagement tiers, then distributes volume accordingly. It is the sort of tool that makes deliverability less of an art and more of a calculable optimization problem, which is precisely how Armasu thinks it should be treated.
The Analytics Layer: Tableau and Seven Years of Data
Most ESPs retain your data for two years, at which point it vanishes into the contractual void and you lose the ability to ask even basic questions about long-term trends. Armasu’s response was to build an external analytics layer on Tableau, extracting data from every ESP his clients have used and consolidating it into a single view.
The result is a dashboard that lets you compare deliverability metrics across Gmail, Hotmail, and Yahoo at a newsletter level, going back seven years. You can see whether your Gmail reputation has been gradually eroding or whether that Hotmail dip in 2023 was a blip or the beginning of a trend. You can compare performance across multiple ESPs if you have migrated platforms, which is useful precisely because ESP migrations are the moments when data loss is most acute and most painful. The data that most platforms silently discard after their retention period expires is, in Armasu’s view, the data that tells you the most about where your program is actually heading.
Email Verification: The Aggregator Approach
The verification layer follows the same consolidation philosophy. Rather than relying on a single verification provider, Armasu aggregates results from Webula (Oracle), BrightVerify (Validity), IP Quality Score, Email List Verify, and seven years of proprietary historical data. The aggregation matters because no single verification tool catches everything. Some are better at detecting disposable domains. Some are better at catching role-based addresses. Some return ambiguous “gray list” results for catch-all domains where individual provider results would be misleading.
The proprietary historical data adds a layer that no off-the-shelf tool can replicate: if Armasu’s system has seen an address bounce across three different clients over two years, that is a stronger signal than any real-time SMTP handshake check. The combination of multiple providers plus longitudinal data produces verification results that are measurably more accurate than any single source.
The Expert Pick: Inbox Analyst
When asked for a single tool recommendation, Armasu did not hesitate. Inbox Analyst – a panel-based monitoring tool used by Cheetah Digital, Oracle, and Adobe – tracks where emails actually land using a panel of real users. Most deliverability monitoring tools, including GlockApps and Email Console, rely on seed accounts: synthetic addresses placed inside various mailbox providers to detect inbox placement. The problem is that a seed address does not behave like a real user. It does not ignore emails. It does not move them to spam. It does not exhibit the engagement patterns that modern spam filters use to make per-recipient delivery decisions.
Inbox Analyst solves this by maintaining a panel of actual humans who have opted in to have their inbox placement monitored. The data reflects real-world conditions, which makes it considerably more valuable for diagnosing deliverability problems – and, presumably, considerably less flattering for senders who have been relying on seed-based metrics to tell a story that bears only a passing resemblance to reality.
For the full interview breakdown, see our complete Expert Insight with Florin Armasu.
Tools Mentioned in the Interview
The following tools and platforms were referenced during this conversation.
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