One tends to think of digital data as something that’s easy to contain in neat silos and access on demand. The reality is that the zettabytes of data that enterprises collect and store is increasing by the minute. Data collection and storage are expected to grow at double-digit rates for the foreseeable future.

The shift toward distributed teams

Employers no longer expect teams to work in the same location to solve problems or collaborate. Thanks Miro… Naturally, this means your team needs access to the data. From wherever. Whenever. To do that, data needs to be agile.

So much data, so little time

Remember the double digit increase in zettabytes we mentioned? As the collection of data increases for enterprises, it can be hard to find the right Data. AI-enabled tools that can draw unprecedented insights from mounds of data. Orchestration tools come into play here because AI requires massive amounts of data, much of it of the unstructured variety.

Keep an eye on these players

Tools that help companies organise, navigate and access all that digital information are generating more interest as well.

According to Gartner, unstructured data constitutes as much as 90% of new data generated in the enterprise, and is growing three times faster than the structured equivalent. At the same time, the vast majority of AI R&D projects never make it into production, which is usually due to a lack of the right tools.

Jina AI 

Founded in February 2020, Jina AI has swiftly emerged as a global pioneer in multimodal AI technology. Within an impressive timeframe of 20 months, they have successfully raised $37.5M, marking their strong position in the AI industry. Our ground-breaking technology, open-sourced on GitHub, has empowered over 40,000 developers around the globe to seamlessly build and deploy sophisticated multimodal applications.

This year, Jina AI made significant strides in advancing AI generation tools grounded on multimodal technology. This innovation has benefited over 250,000 users worldwide, catering to a plethora of unique business requirements. From facilitating business growth and enhancing operational efficiency to optimising costs, Jina AI is dedicated to empowering businesses to excel in the multimodal era.

Qdrant 

Qdrant engine is an open-source vector search database. It deploys as an API service providing a search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more.

Easy to Use API Provides the OpenAPI v3 specification to generate a client library in almost any programming language. Alternatively utiliseready-made client for Python or other programming languages with additional functionality.

deepset Ai

deepset is an open source startup that empowers developers to build flexible and semantic search systems to query all types of data using their Haystack framework. deepset is at the forefront of Natural Language Processing and are on their way to becoming a standard for semantic search. Developers who use their products work at companies like Airbus, Wells Fargo, BMW, and BetterUp and their currently building a new SaaS product called ‘deepset Cloud’.

Their team recently raised 14mil USD Series A from Top Tier-VC firm GV (Google Ventures) as well as the founders of Snorkel, Deepmind, Neo4j, Cockroach Labs, and Cloudera.

Tinybird 

Tinybird helps developers build data products over analytical data, at any scale. Their platform is helping businesses realise the full potential of their data at any scale by turning it into real-time insights, actions and business value. ​​Developers can build data products which make use of our low-latency, high-concurrency APIs – in minutes. Their product is used by start-ups through global enterprises including Vercel, The Hotel Network, and Keyrock.

Launched in 2019, Tinybird is headquartered in New York, with an office in Madrid, and remote employees globally. Tinybird is backed by investors including Crane, CRV, and Singular

Weaviate

Weaviate is a cloud-native, real-time vector database that allows you to bring your machine-learning models to scale. There are extensions for specific use cases, such as semantic search, plugins to integrate Weaviate in any application of your choice, and a console to visualise your data.

Getting ready for the Unstructured Data Boom?

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