Taktile raises $110M to automate banking’s riskiest calls

Taktile has raised $110m in a Series C led by Goldman Sachs Alternatives. The startup wants banks and insurers to hand their riskiest decisions to AI agents, the calls that cost millions when they go wrong.

Banks and insurers spend billions on people to screen risky transactions, process claims and vet new customers. Get one of those calls wrong and the bill can run into millions. Taktile wants AI to take the wheel. Now one of the world’s biggest financial institutions is paying it to try.

The Berlin-and-New-York startup has raised $110m in a Series C round. Growth Equity at Goldman Sachs Alternatives led it. Balderton Capital, Index Ventures, Tiger Global, Y Combinator and Dig Ventures all joined. The deal brings Taktile’s total funding to $184m. The company declined to share its valuation.

The pitch is narrow on purpose. Taktile does not want to build the next ChatGPT. It wants to be the layer that turns models from the big AI labs into trusted agents for a bank’s most sensitive work.

What Taktile actually does

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Taktile sells what it calls an Agentic Decision Platform. The system blends AI agents, hard rules, relevant data and human oversight. The aim is to automate a decision while keeping a person able to check it.

The use cases are specific to finance. They cover underwriting business loans, assessing insurance claims, onboarding customers and catching financial crime. These are jobs that once took human experts hours, and that carry real consequences if they go wrong.

The customer list is credible. Taktile counts the banking startups Mercury and Monzo, the wholesale marketplace Faire and the spend platform Pleo among its users. The company says it powers millions of decisions every day. The machine-learning engineers Maik Taro Wehmeyer and Maximilian Eber founded it in 2020.

The results it claims are striking. Taktile says customers have reached 95% automation in business-to-business underwriting. It also cites a 75% drop in false alarms for anti-money-laundering checks. One of the world’s largest insurers runs several use cases on the platform, with projected savings of more than $90m in claims processing alone.

Why the money is moving now

The timing reflects a shift in what AI can do. Wehmeyer argues the models only recently grew reliable enough for high-stakes work. “AI has been around for a couple of years, but 2026 is the year where AI comes to financial services,” he told Fortune. The agents, he says, can now beat humans at many complex tasks.

Taktile’s own research arm, Taktile Labs, says it spotted the turn in December 2025. It found that frontier models had crossed a threshold. The systems could suddenly handle the kind of judgement calls that banks had long reserved for trained staff.

The costs at stake are large. Moody’s reckons financial institutions spend an average of $72.9m a year on know-your-customer and anti-money-laundering work alone. That is a vast pool of manual labour, and exactly the kind Taktile wants to automate.

The startup is far from alone in chasing it. AI labs and tech giants are racing to automate white-collar work across the board. Salesforce agreed to buy the support-AI firm Fin for $3.6bn this month, and Meta unveiled a business agent to handle customer chats. Software engineers were the first to feel it. Office workers are next.

The control problem

Taktile’s argument is that finance is different. A chatbot that invents an answer is awkward. A loan or claims agent that invents one is a regulatory problem. The stakes change what counts as good enough.

“General purpose AI tooling is fine for simple automations, but it isn’t sufficient for operating mission-critical financial decisions where errors can cost millions,” Wehmeyer said. His pitch is that business owners, not just engineers, need to understand and steer the system. A head of credit or a fraud officer has to be able to see why an agent did what it did.

That framing sets Taktile apart from rivals who bolt a thin layer onto a frontier model. It also fits a wider lesson from finance. Other startups, including the former Citadel quants behind Moment, are selling operating systems built for the messy reality of regulated money rather than generic tools.

The control angle matters because the work is sensitive. Catching financial crime wrongly flags innocent customers and lets real fraud slip through. A system that cuts false positives by three quarters, as Taktile claims, is valuable precisely because the errors are so costly.

The jobs question

The harder question is what happens to the people. Taktile is candid that thousands of employees currently process these decisions by hand. The promise is to free them for higher-value work, not to cut them.

That is the optimistic reading, and it is one many AI firms offer. The reality has often been blunter. Companies across tech and industry have used autonomous agents to trim headcount, not just redeploy it.

Wehmeyer prefers a concrete example. Picture a tornado tearing through a house in Minnesota. One agent reads the claim document. A second interprets the damage against the policy. A third decides whether to pay. What once took an examiner weeks could take minutes.

For the homeowner waiting on a cheque, that is a clear win. For the examiner, it is less obvious. The same automation that speeds the payout also thins the desk that used to process it.

What comes next

The fresh capital targets growth. Taktile will spend it on better tools for complex banking and insurance cases. It also plans to widen its reach across the United States, Europe and Latin America, including a new office in São Paulo.

The Goldman backing carries a signal. Christian Resch, a partner in the bank’s growth-equity arm, praised Taktile for pairing technical depth with an understanding of how regulated institutions really work. A bank putting its own money behind a tool that automates banking is its own kind of endorsement.

The wager is bold all the same. Taktile is betting that banks and insurers will trust agents with decisions that, until recently, only humans were allowed to make. The savings look real. So does the risk. Whether a regulated industry hands its hardest calls to software, at the scale of millions of decisions a day, is the question this round leaves open.