Top 10 AI Startups to Watch in the Czech Republic in 2026

Table of Contents

• From crumpled lists to a living ecosystem
• BottleCap AI
• Duvo.ai
• E2B
• Zaitra
• Myriad
• Langtail
• ValkaAI
• Talentiqa
• Filuta AI
• Kapnetix
• Beyond the list: what this says about Czech AI in 2026
• Frequently Asked Questions

BottleCap AI

Tucked between tram lines and cafés in Karlín, BottleCap AI is one of the few Czech teams trying to solve the hardest problem in generative AI: how to make large language models that enterprises can actually run, afford and trust. Instead of chasing leaderboard scores, they build lean, specialised LLMs for internal copilots, document search and workflow automation where latency, accuracy and cost all matter at once.

World-class brain trust, Prague address

The company is co-founded by Tomáš Mikolov (Word2vec pioneer, ex-Google and Meta), together with Jaroslav Beck and David Herel. This gives Prague something rare in Europe: an LLM lab led by one of the most-cited AI researchers globally. According to Seedtable’s overview of Prague AI startups, BottleCap’s early team stacks multiple ex-Big Tech researchers on top of strong local engineering talent, making it a magnet for ČVUT and MFF UK graduates.

Backed by a seed round of $7.5M (≈178M Kč) led by Rockaway Ventures, BottleCap focuses on models that are small enough to deploy on-prem or in EU-sovereign clouds, but smart enough to understand dense enterprise data. For Czech banks, utilities or telcos bound by GDPR, banking secrecy and sector regulation, that combination - performance plus strict data residency - is often more valuable than another marginally better general-purpose model.

A practical bridge from research to Czech industry

Imagine a Prague insurer wanting an internal claims copilot: it must read Czech-language policy documents, avoid leaking data to public APIs, and respond in under a second on hardware the company already owns. That is the sort of problem BottleCap designs for. Their work aligns with the broader local trend towards secure, auditable AI infrastructure described in regional analyses, but with a rare, home-grown LLM stack at its core.

For developers and students here, that means high-impact roles in model optimisation, evaluation and tooling - without leaving the Vltava for Silicon Valley.

Duvo.ai

For anyone who has queued at a Prague supermarket on a Friday evening, the chaos behind the scenes is easy to imagine: pallets arriving late from a central depot, pickers rushing online orders, drivers stuck on Jižní spojka while customers refresh tracking links. Duvo.ai steps directly into that mess, building vertical AI that understands the real constraints of Central European retail instead of pretending every store is a frictionless spreadsheet.

Retail DNA with an AI engine

Co-founded in 2025 by Tomáš Čupr (Rohlik Group), together with Martin Pecha and Marek Paris, Duvo.ai starts with a rare advantage: founders who have spent a decade optimising grocery logistics across Prague, Brno and multiple EU markets. According to EU-Startups’ profile of Czech innovators, Duvo is backed by both domestic and international investors who see that operational know-how as a defensible moat.

The platform targets the entire “from shelf to doorstep” chain in omnichannel retail, with models that tackle:

• demand forecasting for fresh and non-perishable inventory
• warehouse slotting and order-picking orchestration
• shift planning for in-store and dark-store staff
• last-mile routing under real traffic and labour constraints

From gut feeling to measurable ROI

Consider a mid-sized supermarket chain in Moravia juggling brick-and-mortar stores, click-and-collect, and home delivery. Today, many such operations still rely on Excel, manager intuition and overnight batch reports. Duvo’s promise is to replace that patchwork with continuously updated AI models that rebalance picking capacity, adjust delivery slots in real time and cut both stockouts and overtime.

That matters in a sector where margins are thin and cash flow is king. It aligns with Czech consultancies’ observation that once data is cleaned and integrated, AI optimisation projects in operations can pay back in as little as 3-6 months through reduced waste and labour costs. For Prague and Brno engineers, Duvo.ai offers a chance to work on hard optimisation problems that show up in every grocery run.

E2B

As AI moves from polite chatbots to agents that can browse the web, call APIs and run code, one question keeps Prague’s banks and telcos awake at night: where, exactly, do you let that code execute? E2B, founded in Prague, answers with a simple idea that is hard to implement well - give every AI agent its own disposable, tightly controlled sandbox in the cloud.

The “operating system” for agentic AI

E2B provides a secure runtime where agents can run Python, access tools and work with files without ever touching production infrastructure. Developers call a few APIs, spin up an isolated environment, let the agent work, then tear everything down. According to Digest.pro’s overview of Czech AI startups, this positions E2B squarely in the country’s emerging “secure-by-design” AI stack, alongside players focused on fraud detection and regulated data.

The product resonates strongly with sectors clustered around Prague 4 and Chodov - banks, insurers, large IT outsourcers - where experiment velocity is important but compliance officers insist on auditable boundaries. Instead of giving an LLM a shell on a shared server, teams can:

• limit network access to approved domains and services
• enforce quotas on CPU, memory and runtime
• capture detailed logs for incident response and audits

From GitHub stars to Czech paychecks

E2B gained early traction in the global developer community, with its open-source tooling regularly trending on GitHub and being adopted by indie hackers and Silicon Valley teams building autonomous workflows. For Czech students at ČVUT or MUNI, that global footprint matters: working on E2B’s core runtime or SDKs means your code ends up in stacks from San Francisco to Singapore.

In practical terms, E2B is quickly becoming part of the invisible plumbing that lets Czech enterprises pilot AI agents without inviting them straight into their core systems - a quiet, essential bridge between research demos and production reality.

Zaitra

From quiet offices near Brno’s VUT campus, Zaitra is doing something that still feels like science fiction: running AI models not in a data centre, but on the satellite itself. Instead of downlinking every image and sorting them out on the ground, their software decides in orbit which pixels are worth sending back.

AI at the edge of space

Zaitra specialises in on-device AI for Earth observation. Its models run on constrained satellite hardware, filtering out useless data such as heavy cloud cover and compressing the rest. Media coverage of Brno’s AI scene reports that this approach can cut communication costs by up to 98%, turning expensive radio links into a much more efficient “priority lane” for truly important observations.

In practice, that means a satellite can ignore a hundred cloudy passes over Šumava and only transmit the few frames where it detects real canopy change, or focus bandwidth on flooding along the Morava after heavy rains while skipping routine images.

Brno deep tech with ESA credibility

According to a profile in Yahoo Finance’s feature on Brno AI startups, Zaitra recently raised €1.7M (≈43M Kč) to expand into the US market and deepen collaborations with the European Space Agency. Their technology has already been tested in missions involving the International Space Station, giving a young Brno company immediate validation in one of the most demanding environments imaginable.

Dual-use potential, local opportunity

Edge AI in orbit is inherently dual-use. The same models that help farmers monitor drought stress can also assist with maritime surveillance or border monitoring. For Czech engineers interested in computer vision and embedded systems, Zaitra offers a rare combination: working on global security and climate challenges while staying within Brno’s growing space-tech cluster, rather than moving to Toulouse or California.

Myriad

In meeting rooms from Karlín to Brno-střed, every Czech scale-up founder hits the same wall sooner or later: the spreadsheet where GDPR, PSD2, DORA, the AI Act and half a dozen local rules collide. Myriad exists for that moment, turning regulatory overload into something a fast-moving product team can actually work with.

AI co-pilot for an alphabet soup of rules

Founded in 2023 by Jan Špidlen (engineering veteran from Google, Airbnb and Dropbox) and Ralf Schönherr, Myriad builds an AI-driven platform that ingests regulatory texts, maps obligations onto real company processes and keeps track of who is responsible for what. Backed by $7.8M (≈185M Kč) in funding, it goes after fintech, insurtech and healthtech teams where compliance is mission-critical, not a side job.

Instead of manual cross-border spreadsheets, teams get a living system that can:

• parse and categorise new regulations as they appear
• link specific articles to internal controls, policies and systems
• surface gaps before auditors or supervisors do

Those sectors often see compliance consuming a double-digit share of operating budgets, making even small automation gains meaningful in CZK terms.

Why this matters in Prague and Brno

Czech SaaS and fintech companies rarely stay local; selling into Germany, France or Benelux is a default ambition. Each new country multiplies the regulatory surface area. As consultancy analyses of the Czech market note, organisations are pushing ahead with AI, but fragmented data and governance remain major blockers, especially in regulated industries; this is precisely the terrain Myriad targets. A recent review on Czech organisations and AI adoption underscores how quickly complexity mounts once firms scale beyond the domestic market.

For a Prague-based fintech expanding into Germany and France, Myriad can generate a consolidated obligations map, align it with existing processes and assign clear ownership across risk, legal and engineering. For Czech AI/ML practitioners, that translates into work at the intersection of NLP, knowledge graphs and governance - with a direct line of sight to the EU’s evolving AI rulebook rather than yet another generic chatbot.

Langtail

Walk into a product planning meeting in a glass tower above Nové Butovice or around Brno’s business district and you will probably see the same thing on someone’s screen: a maze of prompts in Notion, ad-hoc scripts hitting OpenAI, and a production “copilot” that nobody quite knows how to measure. Langtail was born to tame that chaos, turning LLM experimentation into a shared, repeatable workflow.

Turning prompt chaos into shared workflows

Langtail offers a collaborative layer for teams building LLM-powered products. Instead of prompts living in private docs or local files, the platform centralises them, tracks versions and lets developers, product managers and domain experts run experiments side by side. In ecosystem roundups such as Failory’s overview of Czech startups to watch, Langtail is highlighted as part of a growing wave of MLOps and LLM tooling coming out of Prague.

Core capabilities typically include:

• a prompt repository with history, comments and rollbacks
• evaluation runs on real user data, not just toy examples
• monitoring of latency, cost and quality in production
• team-level permissions and audit trails for regulated environments

Why this matters for Czech product teams

Across Prague 4’s corporate campuses and Brno’s shared-service centres, most companies now have at least one AI pilot: an internal support bot, a sales-email generator, a documentation assistant. The bottleneck is no longer access to models, but the ability to iterate, compare and govern them in a way risk and compliance teams can live with. Langtail’s collaboration-first design directly targets that gap, making it easier to move from a clever prototype to a reliable feature.

Career signal for LLM-native builders

Backed by leading European VCs (funding amounts remain undisclosed), Langtail positions itself at the tooling layer of the Czech AI stack. For students from ČVUT, MFF UK, VUT or MUNI, experience with Langtail-style evaluation, prompt design and monitoring is fast becoming a practical signal: it shows you understand not just how to call an API, but how to make an LLM-driven product survive real users, SLAs and Friday-afternoon deployments.

ValkaAI

On the surface, ValkaAI looks like a studio for flashy avatars. Underneath, it is a serious synthetic-media company aiming to redefine how sports and esports organisations talk to their fans. Founded in 2025 by Vlastimil Venclík and Miloš Lokajíček, the Prague-based team builds persistent, AI-driven “digital humans” that can host streams, interview players and interact with supporters in real time.

Digital humans as always-on talent

ValkaAI combines generative models, computer vision and speech technologies to create hyper-realistic virtual presenters that can operate 24/7 across Twitch, YouTube, club apps and AR experiences. Instead of a static overlay or occasional video, clubs get a digital persona that can react to match data, answer fan questions and switch between Czech, English or other languages on demand.

This ambition is backed by one of the largest early-stage rounds in Czech synthetic media: a $14.2M (≈336M Kč) seed led by Rockaway Ventures in February 2026, highlighted among major regional deals in Top CEE funding round reports. With the global esports and sports media market already worth billions of Kč annually, ValkaAI is clearly aiming well beyond the local Extraliga.

Use cases from O2 arena to global arenas

For a Czech hockey club or a major esports league, ValkaAI can power:

• a virtual host that presents line-ups and statistics during live broadcasts
• interactive Q&A sessions with fans before and after matches
• personalised highlight recaps sent to supporters based on their favourite players

Ethics, safety and the “Prague defense” lens

Synthetic media inevitably raises concerns about deepfakes and misuse. This is where ValkaAI fits into Prague’s wider “secure-by-design” mindset: watermarking, consent management and strict brand controls are not afterthoughts but core product features. For Czech AI engineers, that means working at the frontier of generative tech while wrestling directly with identity, privacy and trust - issues that regulators in Brussels, and fans in Libeň or Brno-střed, are watching closely.

Talentiqa

In the office parks of Prague 4 and Brno-Královo Pole, HR teams at call centres, logistics hubs and shared-service centres sift through thousands of CVs every month. Most still juggle email inboxes, Excel sheets and overworked ATS systems. Talentiqa steps into this reality with a narrow but high-impact promise: use NLP to pre-screen candidates in high-volume hiring so that recruiters spend their time on conversations, not sorting.

From CV piles to language-aware filters

Founded by Marek Dian and Miro Šmelko, Talentiqa focuses on roles where application volumes explode - customer support, retail, logistics, junior tech. The platform parses CVs and structured forms, evaluates written answers and flags best-fit candidates based on criteria you define, while keeping a human recruiter in the loop.

In September 2025, the company raised €1.1M (≈28M Kč) from Purple Ventures and Venture to Future Fund, fuelling expansion into Ireland, France and the US by April 2026. That trajectory places a Czech-Slovak team on the map of international HR tech, alongside larger AI vendors highlighted in rankings of Czech AI development companies.

• automatic CV parsing across multiple languages
• scoring based on skills, experience and availability
• structured handoff to recruiters via shortlists, not raw inboxes

Hiring automation under EU scrutiny

Algorithmic hiring is under growing EU scrutiny, especially with the AI Act classifying many HR tools as high-risk. Talentiqa’s edge will depend on offering clear bias checks, explainable scoring and robust audit logs so that Czech employers can demonstrate fairness to works councils, candidates and regulators.

Picture a Prague BPO centre hiring 300 customer-support agents for a new German client. Instead of manually scanning every CV, recruiters define language, shift and experience requirements. Talentiqa screens the full pool, surfaces a ranked shortlist and lets recruiters focus on interviews and culture fit - speeding up hiring while giving candidates faster, clearer outcomes.

Filuta AI

For game studios spread between Prague’s Smíchov and Brno-centrum, testing is the part of development nobody boasts about. Every new build means hours of repetitive clicking, trying to break systems that designers already know too well. Filuta AI, founded in 2022 by Martin Doušek and Filip Dvořák, tackles this pain point by sending swarms of intelligent agents to “play” the game instead.

Autonomous play-testers at scale

Filuta’s platform uses AI agents that explore levels, combine abilities and items, and push game systems into edge cases that human testers rarely have time to reach. Instead of a QA team manually replaying the same tutorial for the hundredth time, teams can configure agents to:

• search for crashes, soft-locks and scripting bugs
• probe balance issues across classes, builds or weapons
• stress-test performance in dense combat or AI-heavy scenes
• generate structured reports that plug into existing issue trackers

According to ecosystem summaries of Czech AI funding, Filuta has raised around $4.2M (≈100M Kč) to date, giving it enough runway to integrate deeply with engines like Unity and Unreal and court mid-sized studios across Europe.

Why Prague and Brno are ideal testbeds

Both cities host a mix of AA and indie developers, mobile studios and outsourcing houses, making the Czech Republic a compact laboratory for this kind of tooling. A Prague mobile studio shipping live-ops events every week can use Filuta’s agents overnight to validate new content drops; a Brno PC studio can run large-scale balance sweeps before a patch hits Steam.

Filuta’s rise also reflects the broader capital flowing into local AI, documented in recent Czech startup funding overviews. For Czech ML engineers, it offers a chance to work on reinforcement learning, simulation and tooling that directly shapes what millions of players experience - without leaving Prague or Brno’s growing gaming hubs.

Kapnetix

On mocap stages from Prague’s Barrandov studios to compact facilities in Brno, animators share the same quiet frustration: beautiful performances ruined by jittery markers, occlusions and tracking drift that take hours per shot to fix. Kapnetix, based in Brno, exists to turn that grind into a mostly automated step, using computer vision models to clean motion-capture data before artists even open their timelines.

From noisy markers to animation-ready motion

Kapnetix builds AI tools that detect and correct common mocap issues: missing markers, foot sliding, spikes in joint rotation, subtle jitter. Their pipeline takes raw data streams and produces smoothed, retargeted clips that can drop straight into Maya, Blender or game engines. The team reports cutting cleanup time from hours to minutes, which, over the course of a season of a streaming series or a mid-budget game, translates into weeks of animator time reclaimed.

Rooted in Brno’s computer-vision talent

The company grew out of experience across 50+ AI projects, and taps into VUT and Masaryk University’s strong graphics and vision labs. That academic-industrial loop is a hallmark of Brno’s AI ecosystem, which international directories of Czech AI companies increasingly recognise as a deep-tech hub rather than just an outsourcing destination.

Serving indie teams and major productions

Kapnetix deliberately targets both ends of the market. Independent game and film studios get access to tools that would traditionally sit inside expensive proprietary pipelines; major productions gain a way to standardise cleanup across large teams and vendors. Typical workflows include:

• overnight batch cleanup of a day’s mocap sessions
• on-the-fly correction during live previz for directors
• retargeting human performances to stylised or non-human rigs

For Czech AI engineers who love both neural nets and cinema, Kapnetix offers an unusually direct path: your models don’t just move numbers; they move characters that audiences around the world will actually remember.

Beyond the list: what this says about Czech AI in 2026

Standing on Charles Bridge with a soggy “Top 10” in your hand, you eventually realise the paper isn’t wrong, it’s just small. The same is true of any ranking of Czech AI startups: it offers a sharp, limited view over something much messier stretching from Karlín to Brno-Královo Pole, from corporate towers in Pankrác to late-night hacking in dorms at Dejvice and Bohunice.

Secure-by-design as a Czech signature

One clear pattern across the list is infrastructure that treats safety and auditability as first-class features. E2B’s sandboxes for agents, Myriad’s compliance knowledge layer and BottleCap’s efficient, EU-sovereign LLMs echo what local consultants describe: Czech organisations are keen to use AI, but only when they can see and control the risks. Analyses like Adastra’s study of Czech enterprises and AI hesitation underline how data quality, governance and explainability have become non-negotiable, especially in finance, telco and the public sector.

Universities, verticals and the public sector as launchpads

Another thread is how deeply these startups plug into local institutions. Teams draw heavily from ČVUT, MFF UK, VUT and MUNI, turning thesis work in NLP, computer vision or embedded systems into companies like Zaitra, Kapnetix or Filuta. Others go vertical: Duvo in grocery logistics, ValkaAI in sports media, Talentiqa in HR, mirroring Czech industry strengths from retail to gaming.

Even municipalities are part of this story. Citymind’s multilingual chatbot in Prague 6, for example, reached a citizen satisfaction score of 4.05/5, outperforming many national e-government services and quietly proving that local AI can handle real-world public workloads.

Turning the Top 10 into your own roadmap

If you are building an AI career in Prague or Brno, the smartest way to use this list is as a starting compass, not a checklist. You might:

• pick one infrastructure startup to learn from if you care about safety and tooling
• choose a vertical (retail, games, health, space, HR) that matches your curiosity
• seek projects or internships that sit at the intersection of local universities and these companies

Like the tourist folding his crumpled guide and wandering off the main route, your job now is to pocket this Top 10, lift your eyes from the bullets, and start exploring the side streets of the Czech AI ecosystem that no ranking can fully capture.

Frequently Asked Questions