Naologic: Democratizing access to AI with Google Cloud and MongoDB
Scales seamlessly to support all AI workloads including RAG, image search, and auto-complete
Removes IT administration strain with managed services in Google Cloud
Accelerates time to market with Google for Startups Cloud Program education and credits
Improves query response times by integrating MongoDB Atlas Vector Search directly within Atlas
Naologic uses Google Cloud and MongoDB solutions to power a platform enabling all companies—regardless of IT expertise—to benefit from AI.
Naologic uses Google Cloud and MongoDB solutions to power a platform enabling all companies—regardless of IT expertise—to benefit from AI.
Tech startups are bringing innovative solutions to solve new challenges across virtually every market vertical. These companies require efficient, scalable, flexible, and powerful foundational IT infrastructure to have the freedom to experiment and grow. As startups have to contend with so many challenges, including funding, thin margins, and carving out a piece of the market, having the right technological solutions and support can go a long way toward easing growing pains.
One startup, Naologic, chose to work with Google Cloud and partner MongoDB to not only stand up the right IT infrastructure, but also take advantage of the Google for Startups and MongoDB for Startups programs to hit the ground running.
Google Cloud and MongoDB provided a powerful combination of efficient and flexible infrastructure, powerful vector search, and advanced gen AI APIs along with enhanced startup support to help Naologic accelerate its growth.
Who is Naologic?
Companies looking to capitalize on AI technologies are confronting the complex challenge of managing data across disparate systems. Naologic works to eliminate obstacles to using AI. Its AI-powered apps integrate with a company’s legacy ERP systems, ecommerce platforms, and other environments to capture data and apply the power of AI across the business.
“We launched Naologic to build business autopilots that connect a company’s data sources and optimize the value of their current platforms,” says Gabriel Paunescu, co-founder and CEO of Naologic. “We’re unique because everything we do is configurable through a visual interface. It makes it easy for businesses to create and connect custom data models that match their existing data sources.”
Naologic sets itself apart by generating for each customer unique source code, ensuring complete control and ownership of their data and infrastructure. This unparalleled flexibility, combined with the simplicity of a visual drag-and-drop system, enables businesses to leverage the full potential of AI without sacrificing security or control.
Well-managed strategies for Kubernetes, CDN, and more
Auto-scaling is easy on Google Cloud and it allowed us to deploy thousands of dockers for our customers. It’s easy to manage, performant, and feature rich. As a startup with a small IT team, these are important advantages.
Gabriel Paunescu
Co-founder and CTO, Naologic
One of the main reasons Naologic adopted Google Cloud was Google Kubernetes Engine (GKE). Naologic manages multiple clouds and prioritizes supporting private cloud options for customers with ease and offers self-hosting support for large organizations.
Unfortunately, in its previous cloud environment, managing Kubernetes was challenging. “GKE is a lot more flexible and plug-and-play than other cloud-based Kubernetes solutions,” says Gabriel. “We remove a lot of stress from our team by running Kubernetes on GKE. It’s easy to manage, high performing, and feature rich. As a startup with a small IT team, these are important advantages.”
After the success with GKE, Naologic began to look to other Google Cloud managed services, including Cloud Run to host dockers without needing to set up additional clusters, and Cloud CDN to accelerate moving data between apps and systems. Google Cloud Storage provides the agile data management capabilities Naologic needs to scale.
Naologic also took advantage of the Google for Startups Cloud Program and MongoDB for Startups, granting them access to credits to experiment, test, and scale the business. In addition, Naologic staff also use Google Cloud Program webinars and other educational opportunities to learn about new technologies, capabilities, and applications.
Naologic now has four separate clusters that each host 700 dockers on Google Cloud. “We’ve seen big performance improvements and not having to worry about scalability is huge. We easily do many demos of all sizes with Google Cloud,” says Paunescu. “We can keep our costs down and quickly clone projects. We don’t have to worry about unpredictable costs or performance thanks to auto-scaling.”
Incorporating vector search through MongoDB
Naologic has used MongoDB Atlas as its non-relational database since its inception. As the Naologic platform grew, the company needed to help customers find and filter products by images. They chose to use MongoDB Atlas for this capability.
With Naologic’s solutions, people can visually create tables, forms, dashboards, and other image-heavy components. MongoDB Atlas Vector Search allows people to search for an object within an image along with contextual data and filters.
“Response times of MongoDB Atlas on Google Cloud are fast,” says Gabriel. “With other environments, we worried about configurations. Now we just have to make sure our clouds are in the same availability zone. Our customers also see the benefits of faster responses.”
With MongoDB Atlas and Google Cloud, we get fast queries and fast vector search in the same database call. This makes the user experience fast, regardless of query complexity. We have a lot of dashboards so fast responses are critical.
Gabriel Paunescu
Co-founder and CTO, Naologic
Embedding AI across the platform
Naologic uses Gemini APIs for large context windows that simplify and accelerate creating more customized builds. “Augmenting a lot of data for particular user queries can be a challenge with a normal context window because you quickly reach limits,” says Gabriel. “Gemini APIs provide us with much larger context windows that remove limitations while reducing engineering work and increasing the quality of RAG queries.”
So far, Naologic has applied Gemini APIs to manage help desk tickets and to better analyze questions and answers. With larger context windows, Naologic can query the system about common topics, complaints, and questions and continually improve answers based on more and better available data.
Gemini APIs provide us with much larger context windows that remove limitations when building RAG applications while reducing engineering work.
Gabriel Paunescu
Co-founder and CTO, Naologic
“Gemini streamlines coding because we don’t have to conduct multiple queries. We also don’t worry about problematic summaries,” says Gabriel.
Naologic customers have full access to what is called the Pilot, a chat interface powered by Gemini APIs where people can ask questions and receive hallucination-free graphs in response to their data and more. The Pilot also generates graphs from natural language, which users can ask to interpret based on the context of their businesses.
Improving AI access for businesses
By using Google Cloud and MongoDB, Naologic has simplified AI capabilities so people can ask a simple question or press one button and complex queries automatically run in the background.
“Our mission is to enable millions of companies to benefit from AI,” says Gabriel. “They use their own data and set the priorities and we do the rest. We’re excited to democratize the potential of AI for every business.”
Naologic is a no-code platform that automatically builds AI-powered applications on top of existing legacy ERP and helps companies automate business processes.
MongoDB, a Google Cloud partner, stores your operational data, metadata, and vector embeddings in a single database to streamline building AI-enriched applications.
Industry: Technology
Location: United States
Products: Google Cloud, Cloud CDN, Cloud Storage, Google Kubernetes Engine, Gemini APIs
