How Claimlane’s commercial team used AI to accelerate growth

About Claimlane

Claimlane is a Copenhagen based software company providing a returns and warranty claims management platform for brands and retailers selling physical products. The company was founded in 2019 and is now used by more than 45,000 businesses all over the world, including iconic brands such as Black Diamond, GANNI and Marc Jacobs.

Challenge

Claimlane has the ambition to grow faster than most companies. AI gives them the possibility to accelerate, both by building AI into their product and by using AI internally to boost productivity. When Claimlane engaged us they had just launched their first AI product: The world’s first AI Agent for automated handling of warranty claims. So Anders Sommer, a technical CEO, knew first hand the potential AI had for their customers and the effect it had already had on his own work and that of his developers. Anders and his CCO, Thomas Æbelø, wanted to realise the same positive impact of AI on their growth and for the commercial team.

Approach

We started with a simple plan: First, understand how growth actually works at Claimlane today. Then set goals with management and agree on the strategy. Finally, execute together with the team on the plan.

We began with a two-week discovery process interviewing the team and crunching the data. This resulted in a understanding of status quo and a growth plan for the rest of the year. Then started execution.

Our work span across three primary tracks:

1. Run the growth team

We helped set the strategy. Implemented a biweekly sprint and experimentation process. And ran the process with the existing team.

2. Build AI leverage into the workflows that drive growth

We identified the key levers in the growth plan. Helped optimize inbound and outbound processes and built systems and AI agents to grow accelerate growth.

3. Enable the commercial team to use AI themselves

We set up the growth team on Claude, defined guardrails and configured system connections. Facilitated training workshops to help the team get their first wins.

Results

We deployed as the interim growth lead, delivered the 2026 growth plan after two weeks of discovery, and executed alongside the team.

After the first 2 months, new monthly leads (MQLs) had grown 38% and new pipeline generation hit new highs. We continue supporting the team in executing across the growth function to improve process and build and implement tools that help the company grow.

Here are a few highlights from what we built together:

An SDR Prospecting Agent that centralises and automates list building

Like most B2B companies, Claimlane needs to reach many relevant companies. But prospecting was manual: each salesperson hunting for accounts and contacts by hand. It's slow, and it meant reps chased slightly different companies and personas, some less qualified than others.

So we refactored the process. List building now sits centrally with a Revenue Operations person, and salespeople get a prequalified list of companies and contacts instead of building their own.

To make centralised list building work, we needed leverage. So we built a solution that programmatically runs bulk searches for relevant companies, enriches them with metadata, and qualifies them against Claimlane's ICP.

An n8n workflow orchestrates the searching and qualification, then hands off to Clay for enrichment. AI agents in Clay surface what an SDR needs to personalise outreach: the software a company uses, its returns and warranty policies, sentiment from recent reviews; anything that can be evaluated from a company's online presence that a person used to check by hand. ‘People search’ runs automatically too, finding relevant contacts with their LinkedIn profiles and contact details.

The team has surfaced thousands of new relevant companies this way. It's now the foundation for their outbound model, where list building sits with Revenue Ops instead of individual SDRs, freeing SDRs to focus on crafting thoughtful, personal outreach.

A ghostwriter agent that turns team insight into content

Being active on LinkedIn with useful content is central to the growth strategy, but the best ideas usually live with the product and sales people who face customer problems daily. Naturally, writing a lot of content takes long time and the blank page can be daunting.

We set up a ghostwriting process where the team's content creator interviews key stakeholders for 10–15 minutes to surface ideas. The interviews are recorded, transcribed, and summarised into content ideas for blogs and LinkedIn posts, with the agent drafting in the desired tone of voice. For a small time investment, the content person now has ideas straight from the trenches, plus drafts to build on.

A sales coaching agent: a lightweight Gong at a fraction of the cost

We built an agent that transcribes and summarises sales meeting notes onto the HubSpot deal, then reviews sales performance against the team’s sales methodology (SPICED). The agent pulls together what's known for deal reviews, highlighting gaps, and suggesting which questions to cover in the follow-up or next meeting. Now every sales call is QC'd, and the sales team gets more reps on the sales methodology.

Conclusion

In the first two months, Claimlane went from an ambition to accelerate growth to a commercial function that runs on a faster cadence and is measurably compounding. New monthly leads grew 38%, pipeline generation hit new highs.

The team now has a centralised, automated prospecting engine, a content process that turns internal insight into published thought leadership, and every sales call quality-checked against their methodology.

Most importantly, the team sees the effect AI can have. For their own work and the team’s output.

We're glad to keep supporting Anders, Thomas, and the team as they accelerate from here.

Learnings

Fix the process before you automate.

It can be tempting to jump directly to automation. But most often it’s worthwhile taking a look at the underlying process first. Does it even need to exist? What can be removed or done smarter? In this example with claimlane, a lot of value was generated simply by centralising the list building.

Building v1 is faster than ever. Implementation still takes time.

With LLMs, coding agents, and powerful off-the-shelf software building an impressive demo and first working solution is extremely fast. However, getting that to work in production, with the client’s existing systems and data structures, and having people still take the bulk of the time in a project.