About the Startups category

Are you using Neo4j for your startup? If so, you are invited to share your story with the developer community. Whether it’s about overcoming obstacles, scaling efficiently, or creating innovative solutions, your experience can offer valuable insights and spark new ideas.

Here are some starter questions for you:

  • What is your startup about? (Your founder’s story)
  • Who can best benefit from adopting your solution?
  • What made you decide to implement Neo4j for your startup?
  • How did Neo4j fit into your existing tech stack or workflows?
  • Have any tips you want to share with the community?

What is your startup about? (Your founder’s story)
At engAIge, we are transforming the way organizations process and analyze unstructured data and documents. In a world where everything is interconnected, we believe that documents should be treated the same way—with links, relationships, and hierarchical structures reflecting their real-world complexity. Currently, we are focused on the financial services industry, where we apply our deep domain knowledge to help clients manage vast volumes of critical documents. Our platform not only streamlines document processing but also extracts valuable insights by understanding how documents relate to one another.

Our journey began with a simple vision: to create a solution that treats documents as part of a larger ecosystem rather than isolated files. This vision quickly grew into a powerful platform that helps companies navigate complex document management challenges. By integrating cutting-edge technologies, we ensure that our clients can efficiently process and make sense of their interconnected data.

Who can best benefit from adopting your solution?
Our solution is particularly well-suited for industries dealing with high volumes of complex, interrelated documents. Financial services, legal sectors, and healthcare providers are some of the industries that can greatly benefit from our approach. In financial services, for instance, documents often reference one another—contracts, regulatory filings, and financial reports are all part of a broader network. Our platform makes it easier to manage these documents in a way that preserves their inherent connections, enabling users to access, process, and analyze them more effectively.

Any organization facing challenges in managing document-heavy workflows or trying to derive insights from a large pool of unstructured data will find our solution valuable. We’re helping them reduce manual effort, avoid errors, and speed up decision-making processes by leveraging document relationships and hierarchies.

What made you decide to implement Neo4j for your startup?
As we built engAIge from the ground up, it was essential to find a database solution that would give us the flexibility and scalability to manage complex document relationships. Neo4j stood out because of its ability to model relationships natively in a graph format. This was perfectly aligned with our core objective of capturing document interconnections.

Additionally, Neo4j’s seamless integration with our existing tech stack, which includes Python, FastAPI, and Microsoft Azure, made it an ideal choice. The fact that Neo4j is available in the Azure Marketplace as a one-click deployment further simplified the process of getting it up and running. This made deployment easier, quicker, and more secure, ensuring we could focus on building features rather than managing infrastructure.

How did Neo4j fit into your existing tech stack or workflows?
Neo4j fit naturally into our workflow, complementing the tools we were already using. By integrating it with our Python-based backend and FastAPI framework, we were able to create a seamless flow for querying and processing document relationships. Azure, being our cloud platform, provided a secure environment where Neo4j could be deployed and managed efficiently.

The flexibility Neo4j offers allows us to scale our document processing solutions as our clients' needs grow. Whether it’s handling thousands or millions of documents, Neo4j enables us to perform highly efficient queries on large datasets, making it easy to find patterns and connections that would otherwise be difficult to uncover in traditional database models.

Have any tips you want to share with the community?
One of the strengths of Neo4j is its schema-less nature, which provides flexibility. However, we learned early on that it’s important not to take this flexibility for granted. Initially, we added nodes and relationships without much structure, and while this allowed us to move quickly, we later found that our queries became more complex and less efficient as our data grew.

Our advice to the community is to invest time in designing a thoughtful schema upfront, even though Neo4j is schema-less. Treat it like you would a relational database, where proper planning leads to better long-term performance. By continuously refining your data model, you’ll avoid slow queries and the need for extensive testing and debugging down the line. Planning for scalability from the start will pay off as your data grows and your application scales.

2 Likes

What is your startup about?
I'm the Founder of AI & product solutions, an umbrella project for developing AI powered solutions for Small to Medium sized businesses.

Barbara is an AI-powered system designed to streamline business operations, with a current primary focus on automating work scheduling and resource allocation. At its core, Barbara leverages a Graph Database for data storage, providing a flexible and interconnected structure for complex business data. The system's intelligence is powered by OpenAI and Anthropic.

Who can best benefit from adopting your solution?
Small to medium sized businesses with:

  1. Complex scheduling needs: Balancing staff availability with work demands,
  2. Skill matching needs: Assigning the right personnel to specific tasks,
  3. Coordinating across multiple sites needs,
  4. Resource allocation needs: Optimizing use of human and physical (equipment or supplies) resources.
  5. or Compliance management needs.

What made you decide to implement Neo4j for your startup?
Several reasons, the first one is because I do have extensive experience experimenting with Data modelling and indexing of Graph databases using AI. it didn't take long for me to realised that AI + Graph databases is a match made in heaven, and one it could lead to plenty of opportunities.

the second and most important reason is that leveraging a knowledge graph for my use case offers inmense scaleability opportunities. you can pretty much integrate all types of data into a graph database, and fork it to a system to perform any task possible. You could even create your own CRM system out of a knowledge graph!

How did Neo4j fit into your existing tech stack or workflows?
Neo4J is the core of Barbara. It acts as the contextual brain of the system, helping Barbara perform tasks on top if it. Barbara is also able to automate user tasks thanks to all the rich insights mapped out in the graph.

Have any tips you want to share with the community
Work on the contextualisation of you data when it comes to the ontology. I have learned the hard way that 𝘄𝗵𝗲𝗻 𝘆𝗼𝘂 𝗱𝗲𝘃𝗲𝗹𝗼𝗽 𝗮𝗻𝗱 𝗶𝗺𝗽𝗿𝗼𝘃𝗲 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝘀, 𝘁𝗵𝗲 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 𝗼𝗳 𝘆𝗼𝘂𝗿 𝗱𝗮𝘁𝗮 𝗶𝘀 𝗮𝘀 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗮𝘀 𝘁𝗵𝗲 𝗟𝗟𝗠 𝘆𝗼𝘂 𝗮𝗿𝗲 𝗳𝗼𝗿𝗸𝗶𝗻𝗴 𝘁𝗼 𝘆𝗼𝘂𝗿 𝗮𝗽𝗽.

1 Like

Hi Sraab,

Very interesting initiative! I’ve also seen first hand during my time in a big corporation how knowledge management has been a very burning pain-point. Knowledge is often dispersed through different teams and groups and in many cases, duplicated work happening at the same time. Your solution solved that!

Now I’m also working in an initiative called “Barbara” which has the mission to become the AI powered business assistant for small and medium sized companies, by leveraging knowledge graph technology.

Would you be open for a chat ?

What is your startup about?
I am the Head of IT of a logistics and procurement consultancy company. We provide consultancy and assistance to companies that need to optimise their supply chain and logistics.
We have developed u-tender as an e-procurement solution to provide a flexible application capable of digitalising the entire purchasing process.

Who can best benefit from using your solution?
Companies of all sizes and sectors looking for a flexible and easy-to-use solution to digitise and optimise their purchasing process.

What made you decide to implement Neo4j for your startup?
In addition to a flexible solution, there are other challenges. The goal was to develop an easy-to-use access authorisation system that would meet the customer's needs and could be easily expanded as needed.

Neo4j provided all the functionalities we needed to achieve this goal with ease. Adaptations for new features or changing customer requirements are no problem compared to previous approaches and relational solutions.

How did Neo4j fit into your existing tech stack or workflow?
We mainly use ASPNET for our backend services and were looking for a solution with an actively maintained and easy to integrate client library. With Neo4j we found the best possible solution in terms of usability, integration and performance.
The decision to use Neo4j in our product was a natural one, as it met all our requirements and can be easily adapted if necessary.

HI everyone,

Thanks for welcoming me to this community!

I've been working on an exploratory knowledge management tool for the past number of months (really, since the summer).

The "pain point" I've found in using LLMs extensively for both personal and professional applications is that output storage (and management) seems to be something of an ongoing blind spot in the "space." Tools targeting virtually every other conceivable facet of generative IT now abound. But oddly, it's hard to find anything that does output storage and retrieval really well.

In that spirit, this summer, I began prototyping a system for my own use using Postgres as the database (basically, a CRUD app). I began gathering my prompts, outputs, and configuring relationships between all the entities. It became apparent pretty quickly that configuring relationships at scale in RDMSes is tedious and I began exploring the idea of building the system around a knowledge graph instead.

That's just about where I am now. My current focus is becoming better acquainted with Neo4J with a view to setting up a new backend and then proceeding towards MVP (etc).

What is your startup about? (Your founder’s story)
We are edventure Studios a small Indie Gamedev Studio that works on a game that turns mathematics into an adventure. We would like to offer a game experience which motivates you to learn mathematics. As a verified social enterprise we aim to enable education for those who rarely have access to it.

Who can best benefit from adopting your solution?
We are targeting teenager but also will provide offers for university students. Our solution shall also be open for adults who are curious to refresh or explore new math skills.

What made you decide to implement Neo4j for your startup?
Neo4j is perfect for us in creating a knowledge space and user management, we are also science enthusiasts and a fan of graph theory. Neo4j has also quite some strengths in visualization which is really something we are a fan of.

How did Neo4j fit into your existing tech stack or workflows?
We used the APIs to integrate Neo4j in our workflow. It took some time to find out the best way to couple it with our game engine but after a learning phase it seems to work quite well

Have any tips you want to share with the community?
Reaching out to others that work on a similar problem is maybe best strategy - community is key