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The Seeft co-founder is rethinking how sophisticated operational software can serve companies without Fortune 500 budgets or technical teams
For years, advanced process-intelligence tools have been concentrated inside the world’s largest companies. Those organizations could afford complex deployments, outside consultants, and internal teams capable of supporting lengthy implementation cycles. Many mid-market businesses faced similar operational problems but had no practical way to use the same technology.
Naol Mekuriya Bassaye saw that divide from inside the enterprise market.
During two years at Celonis, he developed process-intelligence solutions for large multinational enterprises across energy, aviation, automotive, pharmaceuticals, medical devices, and industrial manufacturing. The work gave him a close view of how large companies use operational data to trace activity, locate inefficiencies, and improve the way work moves across departments.
It also revealed how many businesses remained outside that system.
“Complexity does not begin at the Fortune 500 level, but access to the best tools often does,” Naol said. “A mid-sized manufacturer can face demanding operational problems without the budget, implementation support, or internal resources available to a global enterprise.”
Naol is now the co-founder and chief technology officer of Seeft, where he is adapting enterprise-grade process intelligence for mid-sized businesses that make, move, and sell physical goods.
His focus is not simply reducing the cost of a large-company platform. Naol believes mid-market businesses require a different product philosophy altogether.
“A smaller company does not need a diluted enterprise system,” he said. “It needs software built around its own operating reality. The setup has to be faster, the value has to arrive sooner, and the product cannot assume there is a large transformation team waiting to manage it.”
That influences how Seeft is being developed. The company is entering the market through procure-to-pay because the workflow crosses several departments and gives businesses a contained place to prove the value of a broader operational system.
Instead of requiring a drawn-out technology program, the goal is to help a company identify meaningful opportunities within one to two weeks.
Naol sees speed as part of accessibility. A lower subscription price offers limited value if a business must still spend months preparing data, coordinating consultants, and assigning employees to support the implementation.
“Time is one of the costs people forget to measure,” he said. “A product can look affordable on paper and still be unrealistic once you account for the people and effort required to make it useful.”
His approach has been shaped by work beyond Celonis. Naol previously served as chief technology officer of an aerospace workflow-optimization company, where the consequences of weak implementation extended beyond inconvenience.
One experience there changed how he thinks about operational software. A problem had remained unresolved through nearly two months of remote discussion. Naol went to the company’s location, spent three days observing the work directly, and helped compress the investigation into that shorter period.
“The issue became clearer once I could see the environment and watch the handoffs,” he said. “People often describe a process based on how it is supposed to function. The product has to account for how the work is actually completed.”
That lesson now affects how he approaches mid-market customers. Naol believes software built for operational teams must reflect the workarounds, informal decisions, and practical constraints that rarely appear in a formal process map.
He also brings experience building products outside traditional enterprise engagements. Naol created a synthetic data generator that has been used by more than 10,000 people and has produced over 2 billion data points. The project required him to move beyond technical architecture and consider adoption, usability, and scale.
“Building something technically sound is only one part of the job,” he said. “A product has to make sense to the person using it. If the value requires constant explanation, the design is probably asking too much from the customer.”
His work has attracted attention from selective startup programs. Three Sigma, his previous company, was accepted into Antler’s UK Spring cohort, which admitted fewer than 2 percent of applicants. The company was later included in a £1.7 million investment round covering 14 businesses chosen from more than 5,000 applicants. Naol has since received backing for Seeft through Entrepreneur First.
“A customer does not care that a product was selected by a respected program,” he said. “They care whether their team can adopt it without reorganizing the entire company.”
That standard has become increasingly relevant as artificial intelligence lowers the cost of building advanced software. Capabilities that once required extensive custom development can now be delivered more efficiently, but Naol cautions that easier development does not automatically produce a useful operational tool.
Mid-market companies still need technology that respects their staffing limits, protects critical workflows, and reaches a meaningful result without forcing them to adopt an enterprise-scale implementation model.
“The opportunity is larger than making old software cheaper,” Naol said. “AI gives us the chance to redesign the category around companies that were never well served by it in the first place.”
Seeft’s initial focus is procurement, but Naol plans to extend the same approach into collections, inventory, and fulfillment. Each area affects working capital and requires companies to coordinate information across multiple functions.
The larger ambition is to reduce the operational advantage that has traditionally come with size. A global corporation may always have more resources, but Naol believes sophisticated visibility should no longer depend entirely on budget or headcount.
Leaders in these companies, chief operating or financial officer of a company large enough to have real process complexity but small enough that they still carry most of it themselves, rarely lack judgment about their own business. What they lack is the staff to assemble the picture that judgment depends on. The week of analyst time that turns scattered ERP records into a ranked list of what is actually costing money. Software that does that assembly does not replace the decision. It moves the operator from reconstructing what happened to deciding what to do about it, and it shortens the distance between noticing a problem and acting on it.
“Good operational judgment begins with having a clear view of the work,” he said. “Mid-market leaders should not have to operate with less clarity simply because enterprise technology was not built for them.”
Naol has already worked inside the companies that could afford the most advanced tools. His next test is whether software once associated with enterprise budgets can become practical enough to fit the way mid-market companies actually operate.
