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Langdock is an enterprise AI platform that helps organizations securely deploy generative AI across their workforce. It is model-agnostic, giving access to multiple providers (OpenAI, Anthropic, Google, Meta) to avoid vendor lock-in, and it emphasizes security with GDPR, ISO 27001, SOC 2 Type II, and EU data hosting. The platform includes an employee chat interface, customizable AI assistants, enterprise search, and a unified API, with workflows that integrate with tools like Slack, Google Drive, and Confluence. Its goal is to help knowledge workers use AI tools productively while maintaining data security and regulatory compliance.
Industries
Data & Analytics
Enterprise Software
Cybersecurity
AI & Machine Learning
Company Size
51-200
Company Stage
Seed
Total Funding
$3.1M
Headquarters
Berlin, Germany
Founded
2023
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Total Funding
$3.1M
Below
Industry Average
Funded Over
2 Rounds
Industry standards
Remote Work Options
Hybrid Work Options
Flexible Work Hours
Paid Vacation
Paid Holidays
Health Insurance
Dental Insurance
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Walid Mehanna on carrying the world's oldest pharma giant into the A.I. Era. * 24 July 2026 * colind88 * News Feed When ChatGPT set off a global corporate scramble in late 2022, Walid Mehanna was already deep into rebuilding the digital backbone at the world's oldest pharmaceutical company. As group data officer at Germany's Merck KGaA (also known as Merck Group in the U.S. and unrelated to the American pharmaceutical firm Merck) at the time, Mehanna had spent two years overhauling the company's data and analytics systems for its 62,000 employees. About eight months into the GPT era, his title was elevated to chief data and A.I. officer. The creation of that role, he said, "was an evolution by design, not a reaction to a development, hype or trend." Merck KGaA's roots stretch back to the 17th century, when pharmacist Friedrich Jacob Merck laid the foundation for the family business in Darmstadt, Germany. Today, its business spans pharmaceuticals, medical equipment manufacturing and electronics. Leading an A.I. strategy inside a 350-year-old company is a unique kind of challenge. Mehanna, who was born in Egypt, compares it to building a pyramid. At the base are everyday A.I. tools that improve personal productivity across the workforce. The goal is to build digital fluency, save time and reinvest those gains into growth. The middle layer - where the company is today - focuses on embedding A.I. into core workflows, such as research and development, supply chains, and commercial operations over the next several years. At the top of the "pyramid" is product A.I., where machine learning becomes part of what the company sells, helping speed up drug discovery and innovation. "Philosophically, A.I. at scale is not a technology challenge," Mehanna said. "You still have to do your homework on the technology side, but the real transformation is about leadership. It happens when strategy, culture and ambition come together with a clear commitment." Choosing a local startup partner. Merck KGaA moved early into generative A.I. by rolling out an internal platform called MyGPT to its employees in June 2023. Initially built in-house, the tool gave staff a safe space to experiment. But Mehanna soon saw the limits of relying on a single setup. Within a year, Merck KGaA replaced its original setup by partnering with LangDock, a then-fledgling Berlin-based startup. At the time of their initial conversations, LangDock had four customers and roughly $50,000 in annual recurring revenue. Choosing a young European company might seem political in today's A.I. landscape. Mehanna says it wasn't. "The thinking behind the collaboration was about optionality, speed and sovereignty, not the sentimentality of working with a German startup," he said. "LangDock gave us the ability to build something fully GDPR-compliant that we could host in our own environment. We were able to work with the company to achieve enterprise-grade security while retaining the agility of a startup." The setup adds a buffer between employees and major A.I. providers, giving Merck flexibility as models evolve. "It was important for us to establish a flexible, model-agnostic user layer that gave us access to the world's best models, regardless of who made them, without creating vendor lock-in," Mehanna said. Building A.I. guardrails like a Mercedes brake. Deploying A.I. across a global workforce of Merck KGaA's size requires navigating strict regulatory frameworks and labor relations, particularly in Europe. Mehanna chose to build governance into the strategy from the start, working closely with the company's works council. Since deploying A.I., Merck KGaA has internally generated over 12 million prompts, a gold mine of data containing insights into how employees work, what's on their minds, and what they need A.I. to help with. Mehanna said the company analyzes these prompts strictly at an aggregate level and never monitors individual employee activity. "We learn from patterns in prompts, never from individual employees or their usage," he said. "All usage is privacy-protected, and we do not monitor individuals." Before joining Merck KGaA, Mehanna served as chief data officer at Mercedes-Benz for five years. He often compares A.I. ethics to brakes in a high-performance car: easy to overlook, but essential. "My view is that I want to have the best brakes in the world so that I can go fast. A Mercedes-AMG, Porsche or Ferrari has some of the best brakes because it also travels at very high speeds," Mehanna said. "Governance and ethics work the same way. I want the best governance and ethics in place because the right guardrails allow us to move quickly while remaining safe and secure." Putting that philosophy in practice, Merck KGaA established a Digital Ethics Advisory Panel guided by five principles: autonomy, beneficence, non-maleficence, justice, and transparency. Instead of simply approving or rejecting projects, the panel pushes teams to identify risks early and design safeguards before launch. "Our outside experts ask difficult questions and make us think carefully about the consequences of potential actions. We then determine which guardrails are needed to proceed in a safe and compliant manner that aligns with our values," Mehanna explained. Why models are no longer the edge. Like many tech executives, Mehanna's view of the market has matured alongside the technology. He no longer believes the enterprise race will be decided at the foundational model level, as frontier models continuously leapfrog one another. "Two years ago, I was fairly convinced that the race for artificial general intelligence or enterprise A.I. would be decided at the model layer - that whoever had the best model would win. I have definitely changed my mind about that," Mehanna admitted. "Models are still crucial, but they leapfrog one another every few months. They are therefore not a durable advantage," he added. "I believe the more durable advantage lies in your context, data, processes, people's fluency and, most importantly, the trust you build with your organization and your customers." That shift has changed how Merck KGaA builds its systems. A top-down semantic data layer across the entire company proved too slow. Instead, teams now integrate data incrementally - process by process and use case by use case. On the inevitable question of A.I.'s impact on jobs, Mehanna rejects the notion that A.I. will simply eliminate human roles. Instead, it rewrites job requirements. "We do not see roles disappearing. We see roles evolving," Mehanna said. "A.I. becomes a dynamic tool for accelerating and extending work. The leader of the future will also have to lead a hybrid workforce composed of people and agents." Reflecting on leadership through industrial shifts, Mehanna references an unexpected source: Arnold Schwarzenegger's management guide, Be Useful: Seven Tools for Life. Across disparate careers in athletics, entertainment and politics, the underlying constant remains clear. "The underlying foundational principle is to always be useful, and that deeply resonated with me," Mehanna reflected.
Judith Dada, general partner at VC firm Visionaries, is joining Berlin-based AI startup Langdock as co-CEO whilst remaining a senior partner at Visionaries. The move comes as the firm prepares for a new fundraise later this year.
Langdock, a Germany-based platform provider for businesses to utilize large language models (LLMs) while maintaining data control, has secured $3 million in seed funding. The round was led by General Catalyst and La Famiglia, with participation from over 25 angel investors, Y Combinator, and notable figures like Rolf Schrömgens and Hanno Renner. The funds will support Langdock's operational and growth initiatives under CEO Lennard Schmidt.
A German AI startup backed by General Catalyst is considering opening a US office, its first overseas office.Founded in 2023, Langdock has an office in Berlin but its executives are spending a considerable amount of time in New York and San Francisco.Lennard Schmidt, Langdock CEO and co-founder, says the US is “more dynamic when it comes to AI than Europe”.He said: “I think for us it’s still on the table if we move to the US.”Schmidt said that should the startup open an office in the US, it would retain its Berlin office.Schmidt also pointed out that Germany was behind the US and UK in commercialising AI research.He said: “In Germany we have these very established institutions around doing deep research, what we do lack is the commercial aspect of taking that research and commercialising some of it.“I feel the UK is in a better position right now, but also Paris, given their ties to the big American companies that have research facilities there.”Germany has some well-known AI companies, such as Helsing, Aleph Alpha and Black Forest Labs.Langdock is looking to capitalise on the fervour around ChatGPT and other LLMs while addressing employer concerns around data sharing and compliance when introducing AI chatbots into the workforce.Langdock has built what is essentially a model agnostic chatbot, which sits between the LLM and a business, that it says employers can roll out centrally, securely, and compliantly to its employees, saying it gives businesses “peace of mind”.Its tech, is says, basically addresses concerns a business might have when introducing ChatGPT, Claude or Gemini into the workforce.Schmidt, who along with his co-founders Jonas Beisswenger and Tobias Kemkes, attended Berlin startup university CODE, says: “We take away all the concerns about what happens to the data because we have essentially all the compliance in place for that in terms of contract work and providers we work with.”One potential benefit of Langdock, whose $3m seed fundraise last year was also backed by La Famiglia and Y Combinator, is that its clients, which include US pharma giant Merck and payment startup Mondu, are not tied to using one LLM for life, but can chop and change as they see fit.While it is relatively easy for individual users to swap models, it is harder for enterprises given compliance and regulatory challenges.Merck, for instance, uses Langdock as its AI base layer, which Merck calls MyGPT (with the Merck chatbot looking very similar to ChatGPT), which is rolled out to around 23,000 employees, about 45 per cent of its workforce.Langdock, which has 15 employees, has European and US clients, but Schmidt points out European firms have more regulatory and data concerns than US firms, given the relative tightness of the rules, along with concerns about data sharing
Langdock, the platform empowering companies to leverage large language models (LLMs) while staying in control of their data, has raised a $3 million seed round led by General Catalyst alongside La Famiglia.
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Industries
Data & Analytics
Enterprise Software
Cybersecurity
AI & Machine Learning
Company Size
51-200
Company Stage
Seed
Total Funding
$3.1M
Headquarters
Berlin, Germany
Founded
2023
Find jobs on Simplify and start your career today