Germany-based language service provider (LSP) lengoo has raised EUR 6m (USD 6.6m) in Series A funding. The funding round, completed in August 2019, was led by Zurich-based venture capital firm Redalpine, with other follow-on investors and angels participating.

Lengoo develops a translation workflow that combines neural machine translation (NMT) with human post-editing, resembling the operational models of tech-forward LSPs Lilt and Unbabel.

The Series A is lengoo’s fourth funding round to date. Lengoo has now raised EUR 7.94m (USD 8.7m), of which USD 0.75m came from an EU grant in April 2018. Slator contacted lengoo Co-founder and CEO Christopher Kränzler for comment on the latest funding round. Kränzler declined to disclose the company’s current valuation.

Post-editing for the Enterprise

Lengoo was founded by Christopher Kränzler (CEO), Philipp Koch-Büttner (COO), and Alexander Gigga (CMO) in 2014. Prior to lengoo, Kränzler “was working for a big US consultancy as a localization manager and witnessed firsthand how the translation industry was, and in big parts still is, highly inefficient,” he said.

Looking to eliminate efficiencies, lengoo’s original offering centered around automating project management tasks through an online platform. The company then introduced machine learning for smart outsourcing.

Although lengoo was founded before the advent of neural machine translation (NMT), the company quickly integrated it once it became available. “Having completed our first financing round, we shifted to an AI-first strategy, automating the translation process itself. We started developing NMT technology in 2016 and received an EU grant to turn NMT fit to perform expert level translations in 2018,” Kränzler told Slator.

“Post-editing of neural machine translated output is just a transition phase” — Christopher Kränzler, CEO, lengoo

Lengoo’s proprietary platform is now geared toward streamlining the post-editing workflow. Yet Kränzler believes that “post-editing of neural machine translated output is just a transition phase,” speculating that “the future of translation will see true interaction between humans and machines and move way past a sequential process, where one part completes one step and the second performs another.”

Lengoo focuses “on traditional B2B enterprise selling,” said Kränzler, and the company has made inroads into this customer base in Europe. No mean feat since B2B customers are often loyal to incumbent providers.

One upside to this market is that lengoo’s B2B customers “all have a professional translation process in place,” Kränzler said, “and, hence, can provide us with their past translations in a structured way.” Lengoo is then able to use the vast amount of data contained in customers’ translation memories (TMs) to train their machine translation engines.

Sourcing Talent & Securing Investment

According to Kränzler, the fragmented Germany market is “the perfect market to start a language company” and its location offers “a great opportunity for rapid growth.”

Asked about the talent crunch for machine learning and AI talent, most pronounced in rising tech centers like Berlin, Kränzler agreed that “Berlin has become a vibrant tech hub attracting top talent,” adding that lengoo attracts engineers into the business by providing them with the opportunity to work on real-world problems.

Redalpine, the lead investor in the USD 6.6m round, is focused on “highly scalable European start-ups,” according to their website. Meanwhile, the participation of lengoo’s two follow-on investors, Creathor Ventures and Piton Capital, “shows that we are on the right path,” Kränzler said.

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Lengoo’s angel investors include Kai Hansen, Philipp Hartmann, Mattias Hilpert, Feliks Eyser, and Michael Schmitt. Hansen and Hartmann are the serial investors who sold their delivery service for more than USD 100m in 2014. Hilpert is an investor in early-stage technology companies. Eyser founded and sold an online marketing agency, while Schmitt is an ex-Googler turned angel investor.

Lengoo plans to invest the funds raised in “scaling our enterprise sales team to handle the great demand,” Kränzler said. They also plan to add features to the platform and to continue research into machine translation.