Data processing and analytics stand for the main competitive advantage for most of the businesses in the years to come. Companies started to analyse massive amounts of data and derive predictive insights to beat their competitors.
Accelerating adoption of AI / Machine Learning stack by a broader set of companies, ranging from medium-sized to the very largest multinationals.
chat bots, data integration and visualisation, machine learning, real-time analytics, deep learning, search, industry application of analytics tech, pattern recognition.
Bitcoin the digital currency was the first successful application of blockchain. The technology allows disintermediation of business models by eliminating trusted 3rd parties from value chains. The ultimate goal of this technology stack is to liberate the data and empower the users.
Now, innovative startups are using blockchain technology to provide greater efficiency, transparency and security in all sorts of industries.
smart contracts – digital rights, escrow, wagers; record keeping for ownership, voting, ownership, compliance; digital currencies – payments, value transfer, remittance, P2P lending, decentralised apps stack
Big data analytics is the process of examining large and varied data sets to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organisations make more-informed business decisions.
Companies sit on large data sets and have just started a transformation from traditional business models into data centric models.
Hadoop/Spark/No-SQL DB/Graph DB/MPP DB tools, undesrstanding and targeting customers, optimising and automating business processes (incl. RPA), intelligent search, fraud and risk detection
Programming seems to be a next industry to be disrupted by automation of code writing, testing, software deployment and management.
Record high cost of hiring engineers forced companies to focus more on automation and increased efficiency of programmers. DevOps and automated testing are the concepts that have catalysed into a movement and are rapidly spreading throughout the technical community.
tools for microservices, provisioning, CI, monitoring, cloud IaaS/PaaS, build/config management, release management, deployment, logging, repo management, software testing, tools assisting in software development
Financial Industry was for years one of the the least vulnerable for disruption in the economy. FinTechs are a group of startups aiming for disintermediation and defragmentation of traditional financial business models.
Now it’s perfect time to get off the bench: over 20% of Financial Services businesses are at risk to FinTechs and the industry is growing at exponential pace. We bet on both horizontal and vertical unbundling of financial industry.
digital and mobile payments, roboadvisors, smart insurance solutions, new generation brokerage servies, financial market data, B2B lending and receivables, alternative equity financing, alternative assets, anti-fraud
SaaS is the essence of whole cloud computing idea. Services delivered over the Internet have no technical limits to make a global impact.
All companies fit into one of two buckets: either becoming a software company or being disrupted by one. Every industry is being fundamentally altered by software.
specialised vertical SaaS products for enterprise, data-as-a-service, platform-as-a-service, analytics-as-a-service, APIs, tools for SaaS apps administration
Data processing and analytics stand for the main competitive advantage for most of the businesses in the years to come. Companies started to analyse massive amounts of data and derive predictive insights to beat their competitors.
Accelerating adoption of AI / Machine Learning stack by a broader set of companies, ranging from medium-sized to the very largest multinationals.
chat bots, data integration and visualisation, machine learning, real-time analytics, deep learning, search, industry application of analytics tech, pattern recognition.
Bitcoin the digital currency was the first successful application of blockchain. The technology allows disintermediation of business models by eliminating trusted 3rd parties from value chains. The ultimate goal of this technology stack is to liberate the data and empower the users.
Now, innovative startups are using blockchain technology to provide greater efficiency, transparency and security in all sorts of industries.
smart contracts – digital rights, escrow, wagers; record keeping for ownership, voting, ownership, compliance; digital currencies – payments, value transfer, remittance, P2P lending, decentralised apps stack
Big data analytics is the process of examining large and varied data sets to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organisations make more-informed business decisions.
Companies sit on large data sets and have just started a transformation from traditional business models into data centric models.
Hadoop/Spark/No-SQL DB/Graph DB/MPP DB tools, undesrstanding and targeting customers, optimising and automating business processes (incl. RPA), intelligent search, fraud and risk detection
Programming seems to be a next industry to be disrupted by automation of code writing, testing, software deployment and management.
Record high cost of hiring engineers forced companies to focus more on automation and increased efficiency of programmers. DevOps and automated testing are the concepts that have catalysed into a movement and are rapidly spreading throughout the technical community.
tools for microservices, provisioning, CI, monitoring, cloud IaaS/PaaS, build/config management, release management, deployment, logging, repo management, software testing, tools assisting in software development
Financial Industry was for years one of the the least vulnerable for disruption in the economy. FinTechs are a group of startups aiming for disintermediation and defragmentation of traditional financial business models.
Now it’s perfect time to get off the bench: over 20% of Financial Services businesses are at risk to FinTechs and the industry is growing at exponential pace. We bet on both horizontal and vertical unbundling of financial industry.
digital and mobile payments, roboadvisors, smart insurance solutions, new generation brokerage servies, financial market data, B2B lending and receivables, alternative equity financing, alternative assets, anti-fraud
SaaS is the essence of whole cloud computing idea. Services delivered over the Internet have no technical limits to make a global impact.
All companies fit into one of two buckets: either becoming a software company or being disrupted by one. Every industry is being fundamentally altered by software.
specialised vertical SaaS products for enterprise, data-as-a-service, platform-as-a-service, analytics-as-a-service, APIs, tools for SaaS apps administration
Data Ventures
Head Office
Rozbrat 6/18
00-451 Warsaw, Poland
HQ
Wloclawska 161
87-100 Torun, Poland
Data Ventures LLC (previously Data Invest LLC.) implements the project entitled “Data Fund 1 – specialised in technology of big data fund type seed with the main areas of interest: financial industry (fintech), IT security, technology, SaaS, Internet of Things, Artificial Intelligence” co-financed by European Union funds under the Intelligent Development Operational Program 2014- 2020.
Measure 1.3. R & D works financed with participation of capital funds.
Sub-measure 1.3.1. Support for research and development projects in the preseed phase by proof of concept funds – BRIdge Alfa
Value of the project: PLN 15,000,000
Co-financing of the EU project: PLN 12,000,000