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Tendermore is building AI-powered software to help SMEs, startups, and other businesses find relevant tenders, cut application time, and avoid costly submission errors.
In another life, when I ran an NGO, one of my more arduous tasks was applying for tenders. While tenders can create huge financial opportunitiesffor startups, SMEs and NGOs, they are complex and incredibly time-consuming. It’s not only about filling in a form but also about providing project proposals, budgets, documentation, financial statements, timelines, and other items that may vary by provider.
But now a startup has found a way to reduce complexity and eliminate the common errors that put your application at the bottom of the pile or exclude it altogether.
Tendermore is a Norwegian startup building SaaS software that automates and simplifies the process of finding and applying for public and private tenders. The company focuses on helping businesses—particularly SMEs and startups—navigate the complex procurement landscape.
I spoke to CEO Sebastian Mandal and COO Eivind Wassend to learn more.
From door-to-door sales and coding to tackling the tender problem
Both founders come from different backgrounds. Wassend has been in sales since he was 12, starting with newspapers and later selling alarm systems door-to-door. At one point, he was ranked the best alarm salesperson in Norway.
Mandal started coding at 12, which evolved into machine learning and AI —” before the hype cycle”, he stressed — and building software.
Following a shared stint at a now-defunct startup, they decided to merge their complementary knowledge sets into a consulting practice.
Mandal shared:
“We ended up running around 50 workshops with construction companies, examining their biggest pain points. Almost every single one mentioned responding to tenders.”
In response, the duo decided to stop consulting and focus on solving the problem around tenders.
The challenges of applying for tenders
According to Mandal, the traditional tender process is often painstakingly slow and complex. “You have to understand every requirement before you even start writing,” he explains.
“If you miss one detail — even a small one buried deep in a long document — you can lose the entire tender after spending days or even weeks preparing the submission.”
Language and terminology add another layer of difficulty. Even when a company is technically qualified, the way responses are framed can determine the outcome.
“If you don’t respond in the right way, or use the right framing, you can still lose the bid,” Mandal says.
When Tendermore launched its MVP, the team discovered that writing proposals was only part of the challenge. Many companies also struggled to determine which tenders were actually worth pursuing.
“What we learned early on is that companies also need help identifying which tenders are relevant to them in the first place,” he adds.
“They don’t want to spend time preparing a bid for something they’re not pre-qualified for.”
In Mandal’s view, the core problems come down to two factors: the significant time and effort required to prepare bids, and the difficulty of identifying tenders that a company realistically has a chance of winning. On average, a tender today can take 30 to 40 hours. For larger organisations, it can be almost continuous work because different departments are handling different parts of it.
While its early days to measure win rates as the sales cycles and tender processes are often longer than the amount of time Tendermore has been working with some of these companies, Wassend revealed that “based on the beta and MVP, we’ve seen around a 60 per cent reduction in the time spent across the process — from analysing and refining through to responding.”
How Tendermore works
Tendermore was designed by closely observing how companies already manage tenders.
“We saw how customers structure their work — the spreadsheets, the requirement lists, the way they prepare answers,” Mandel said. “So we built AI into that existing workflow instead of forcing them into something unnatural.”
Tendermore connects to a company’s existing data sources — including Google Drive, SharePoint, previous tender submissions, pricing data, equipment lists, and other internal documents — and analyses them to build a structured knowledge base.
Accuracy is critical in tender applications, so the platform is built around a sophisticated retrieval-augmented generation (RAG) system that ensures responses are grounded in verified company data rather than generic outputs.
Tendermore also structures responses using a requirement matrix, where each tender requirement is broken out and matched with a short factual answer. The platform’s analytics help companies discover tenders they are likely qualified for. It then analyses the tender requirements, highlights what is being asked, identifies relevant internal information, and flags any gaps that still need to be filled.
From there, the system generates the proposal. To avoid generic AI-sounding submissions, Tendermore uses a brand analysis engine that learns a company’s writing style so the final output reflects its voice, making the tool feel like an extension of the organisation rather than a generic AI writer.
A human-in-the-loop approach
Accuracy is critical in tender submissions, so Tendermore was designed to minimise the risk of AI hallucinations.
Mandal explains that the company is strict about promoting its agents never to hallucinate. In the early days it had things like web search in the system, but that actually increased the risk because it could pull in outside information and confuse what belonged to the company and what didn’t.
So we removed that and made the system rely only on the company’s internal knowledge base. We also turn the temperature down so it has less creative freedom. If it can’t find a basis for a claim, it leaves that blank or flags it instead of making something up.
“If we can fill that in automatically, great. If not, the user can step in.
“Then the AI mainly helps turn that factual structure into polished language. So the focus is really on making facts shine, not inventing them.”
Despite the company’s long-term ambitions for automation, the founders believe human oversight remains essential.
“We’re very AI-first, and our long-term vision is to automate much more of the process,” said Wassend.
“But today, human-in-the-loop is the best approach. People still need to trust the system, and that trust has to be built step by step.”
The cross-sector opportunity
So far, the startup has gained the most traction with consultancies, contractors, and the hospitality sector. In sectors like construction, tenders form the basis of revenue, with some handling several each month. In hospitality, it depends on the season and the volume of events or development activity. In consulting, it can be for major client projects or government contracts.
According to Mandal, “Hotel groups also deal with large RFPs (Requests for Proposals), for example, when developers are deciding which hotel brand to place in a new building or estate.”
The team was surprised by how big the private tender market is. It was initially thought that public tenders would be the main opportunity, but companies revealed they handle two to four times as many private tenders as public tenders.
“That really changed how we thought about the market,” shared Mandal.
According to Wassend, the startup is also seeing interest in API-based distribution. “Some consulting firms want to embed our functionality into software they already provide to clients, rather than using a standalone platform. So that’s becoming a secondary offering for us.”
Tendermore raised $400,000 in a round led by Antler in October 2025. The company brought in Ymir Egilson as CTO, formerly the youngest tech lead in Visma’s history-
According to Mandal:
“He loves building. He wants to shape products and ship things with people who are hungry and moving fast. Eivind and I are very execution-focused, and I think that energy mattered.
We’re out there doing the outward-facing work, which means he can focus on what he does best.”
Tendermore is also looking beyond Europe to Asia because it has become clear that many companies don’t know what opportunities exist outside their own countries.
“If we integrate with tender portals across different regions, we can help match companies with international tenders as well. That’s something we see as a really strong future differentiator,” shared Mandal.
Future features will enable discovery, evaluation, and management of both private and public tenders in one place.
Wassend contends, “So many people struggle with tenders, and smaller companies are at a real disadvantage comparedtz5e43w with large enterprises that can throw whole teams at the process. In a lot of smaller companies, the CEO is doing it all day and then all night, on top of everything else. My goal is to enable anyone to respond to tenders. Sebastian’s focus is on building the best AI in the world for that. We’re very aligned on that mission.”
Mandal agrees. “Accessibility is the driving force for us. No matter what kind of company we built, we wanted it to make opportunities more accessible. That’s really what motivates us.”