Translation management tech and marketplace provider Smartcat has closed a Series B round worth just over USD 14.6m. According to Smartcat CEO Ivan Smolnikov, participating in the deal were “our existing VCs, with Matrix Partners as the largest contributor, plus a new VC from the US and two from Europe.” Transaction closed at the beginning of August 2020 but Smartcat chose to not actively publicize it at the time.
Smolnikov declined to elaborate on how much this latest financing round valued the company, only describing it as “good and in line with what a fast-growing SaaS or marketplace at our stage could get in the US.”
Smartcat’s Series B adds to the recent string of financing rounds by translation, localization, and interpreting technology startups; which is set to make 2020 one of the most active years ever in language industry funding.
Investors have — brace yourself — placed bets on tech-only startups Lokalise (USD 6m Series A), LocalizeDirect (USD 1.1m Seed), Localised.com (USD 6.5m Series A), Intento (USD 3m Seed), and Memsource (sold to PE giant Carlyle); funded AI agencies Lilt (USD 25m Series B) and TAIA (EUR 1.2m Seed) as well as interpreting platform Kudo (USD 6m); and have also underwritten captioning and subtitle provider Ai-Media’s USD 47.9m Australia IPO (Pro).
Market Network Credo
Founded by Smolnikov in 2016, Smartcat is based in Cambridge, Massachusetts (US). Smolnikov told Slator, “We currently have more than 115 FTEs and several thousand active LSPs and end buyers, plus more than 300,000 freelancers and LSPs on the marketplace — not all of them are active, of course. Overall, the team has been growing throughout the year independently of the round.”
Among the recent additions to Smartcat as reported by Slator: former Upwork CEO Stephane Kasriel (Board); Richard Delanty (GM for Apac); and Igor Afanasyev (Senior Product Manager).
Smolnikov and team have fashioned Smartcat to be an all-in-one market network platform for the language industry industry with a three-pronged strategy that targets language service providers (LSPs), end buyers, and freelancers. This all-in-one market network philosophy is explained in an article penned by Smolnikov; in a nutshell, Smartcat combines network, marketplace, workflow, and translation productivity components in a single platform.
Serving LSPs Vis-à-vis the Enterprise
Smolnikov emphasized that, “while most vendors in the market see LSPs as a secondary audience after end buyers,” serving LSPs remains at the core of Smartcat’s mission.
Hence, using the team’s own prior experience while running LSPs (“seven team members have headed LSPs, and many others have worked in different LSP roles”), Smartcat is developing a platform that features much of the infrastructure that LSPs would need to run their business.
Slator 2020 Medtech Translation and Localization Report
The Smartcat CEO explained: “LSPs have to use several loosely connected products such as TMSs, CAT tools, sometimes CRMs, and vendor management tools. This leads to data duplication that has to be handled manually and takes a toll on project management productivity. This makes it very difficult to meet the needs of localization today. As batches of content become smaller and more frequent, project managers simply don’t have the capability to continue handling tasks manually; not to mention what that does to their margins.”
Smolnikov added that they recently started targeting the needs of enterprise customers by automating the sourcing and management of suppliers, as well as payments and workflows. And they saw this resonate with segments noted for their quick product- and content-release cycles, such as software development, SaaS, gaming, e-commerce, and e-learning.
“As batches of content become smaller and more frequent, project managers simply don’t have the capability to continue handling tasks manually”
He said clients like that Smartcat “requires no proprietary SDKs, works autonomously on clients’ premises, offers first-class security and reliability, and prevents vendor lock-in,” and that they can deploy the system in a short period of time with minimum hassle — that is, without having to “carve out any engineering resources to build and maintain the custom API integrations.”
According to Smolnikov, “Our system works like LEGO bricks, with modules that are plugged in and configured to allow for version control system integration, customized file parsing, file pre- and post-processing, multiple code branches, and more.”
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Smartcat also offers a Portal tailored for enterprise clients, where they can switch between translation vendors and scale production as needed. The Portal is basically “a simplified UI that allows internal teams, like marketing, product, or legal, to quickly send files for translation without having to sign into the TMS environment.”
Asked on which parts of the platform Smartcat has prioritized development, Smolnikov replied that all the different components feed off one another and they will continue improving all the modules over the coming year.
He said, “Payments, for example, can be automated with our automated billing feature, which has access to all the centralized assets (Translation Memory) to automatically calculate the right breakdowns and amounts for invoicing and payouts. Project management, the second largest cost after translation, can’t be automated if you can’t source vendors from the marketplace and assign them tasks automatically, or do the billing and payouts automatically after.”
Selective (Rather than Predictive) MT
Any translation management platform worth its salt will have, by now, integrated continuous localization. And, as Smolnikov and team designed it, Smartcat’s continuous localization setup enables what he calls “selective MTPE” (machine translation post-editing) — “an approach that usually requires a lot of management that makes it impractical with traditional automation solutions.”
“Selective MTPE […] is not entirely new to the industry, but without continuous localization it, historically, wasn’t practical as it required a lot of management overhead”
Compared to predictive or adaptive MT, selective MTPE is essentially more workflow-driven: just publish the MT-translated content and then jump in to edit as needed after the content goes live. A hybrid between pure MT and MTPE, selective MTPE “offers both speed and quality,” according to Smolnikov.
He further explained: “The idea here is that MT pretranslation can be done instantaneously, and the content pre-translated through MT is automatically integrated into customers’ products, websites, or knowledge bases. However, the entire pre-translated content can be post-edited at any point. A reviewer can jump in and edit any segments that need correcting, based on the results of selective QA, or external signals, like the level of importance of help center articles, traffic, or user feedback.”
Pro Guide: ISO and Quality Management for Language Service Providers
Selective MTPE, Smolnikov said, allows the user to “improve on the quality of their translations by allocating resources — whether money or labor — selectively, instead of doing blanket MTPE. This selective MTPE approach is not entirely new to the industry, but without continuous localization it, historically, wasn’t practical as it required a lot of management overhead.”
“We have seen an increased interest in custom-trained MT engines”
We also asked the Smartcat CEO to weigh in on the popularity of public versus custom MT engines as part of the workflow. His reply: “Beyond stock MT engines, we have seen an increased interest in custom-trained MT engines. By popular demand, we recently added support for custom Google MT models and glossaries.”
No-Seats Policy, Covid Impact
One Smartcat differentiator is that they do not charge per user — what Smolnikov calls “our no-seats policy” — a pricing model fairly rare in SaaS.
According to Smolnikov, charging per user “limits the value of software and keeps businesses from growing.” Additionally, because the user “needs to think twice before inviting a colleague to collaborate,” it also stifles innovation and product improvement.
Finally, as no interview in 2020 would be complete without it, we asked the Smartcat founder how the pandemic has affected business. Smolnikov said that, on the positive side, overall interest in Smartcat increased because more end buyers needed to automate their processes and LSPs, go fully remote; but “on the downside, we’ve seen many deals slip or be delayed as people have been more cautious with their spending.”
Ending on an upbeat note, Smolnikov said business out of their main regions (i.e., the US, Apac, and Europe) has steadily grown, “and, of course, it hasn’t stopped our free user base from growing.”
Hat tip to Konstantin Dranch, Localization Industry Researcher and Co-founder of Custom.MT, for first flagging the fundraise in a LinkedIn post.
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