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Avila reduces grant search and application times by 90%

Avila uses MongoDB to streamline grant discovery and applications, helping schools, governments, and nonprofits find funding faster with AI-powered search and automation.

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The Challenge

To reimagine the grant discovery and application process, Avila needed to parse hundreds of thousands of documents from various sources into a structured, easily navigable dataset.

Our Solution

Avila built its advanced search indexes on MongoDB Atlas. It also uses Atlas Search for keyword-based searches across aggregated data and Atlas Vector Search for semantic embedding to understand data context.

Outcome

  • 90% reduction in grant search and application time
  • 100,000 grant opportunities indexed
  • 10x faster platform development
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Industry

Startups

Computer Software & Technology

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Product

MongoDB Atlas

MongoDB Atlas Search

MongoDB Vector Search

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Use Case

Catalog

Content Management

Gen AI

Single View

THEIR CHALLENGE

Building a better grant search and writing system

Smaller government agencies, school districts, and community nonprofits across the United States rely heavily on federal and state grants to serve their constituents. However, the grant search and application process can be cumbersome, bureaucratic, and time-consuming. Avila was founded in 2023 to synthesize this process in a user-friendly platform, and it has relied on MongoDB from the outset. Organizations can now bring more funding to their community with fewer resources.

Prior to starting the company, Omar El-Sayed, founder and CEO of Avila, identified numerous challenges in the grant funding process, as well as a lack of comprehensive solutions. For one, grant search portals exist, but they are powered by time-intensive, manual, keyword-based (lexical) searches. Many other opportunities are featured on unstructured and disparate web pages, which are even more challenging to locate. Further complicating matters, grant opportunities are communicated through Notices of Funding Opportunities (NOFOs), which are difficult to parse without grant writing expertise.

“The federal grant space is a trillion-dollar market every year. There’s a huge pool of resources available out there, but identifying the right ones is very difficult,” said El-Sayed. “Organizations are potentially leaving millions of dollars a year on the table because the search and application process is so arduous that they don’t have the resources to find the right opportunities.”

El-Sayed founded Avila to reimagine the grant discovery and application process. His vision: an AI-powered virtual grant researcher and proposal optimizer.

To achieve this, Avila needed to store hundreds of thousands of web pages, PDFs, and other documents from public grant databases and other sources. Avila then needed to collect and parse these into a structured dataset and build advanced search indexes to identify opportunities most applicable to each customer. From the very beginning, MongoDB was the answer.

Avila logo
“As a lean startup, Avila hasn’t needed a dedicated database team. MongoDB just works and lets Avila scale as it grows.”
OMAR EL-SAYED
Founder and CEO, Avila

OUR SOLUTION

Using MongoDB to create a comprehensive solution for Avila

Avila set out to address three main pain points for its customers: grant discovery, NOFO simplification, and proposal writing support.

For grant discovery, Avila uses AI and semantic search to automatically and intelligently match a user’s funding priorities (derived from uploaded strategic planning documents) with relevant grants. This occurs on an ongoing basis, with new opportunities pushed to the user weekly.

Avila’s AI also simulates a seasoned grant writer to simplify NOFOs. It extracts critical information from unstructured NOFO PDFs — including narrative structure, required questions, compliance needs, and necessary forms — then transforms it into a structured, easily legible format.

Finally, for research and proposal writing, Avila integrates retrieval-augmented generation (RAG) and other large language model calls, including OpenAI and Anthropic. This enables the platform to analyze pertinent government data and pull relevant information from user-uploaded documents, generating high-quality draft narratives for proposals.

Chief among the reasons Avila chose to use MongoDB was its unmatched flexibility. MongoDB Atlas, a foundational database for document and file storage, enables Avila to manage data from diverse grant resources. This data includes highly structured content from databases, like grants.gov, and unstructured content, like articles about funding opportunities on disparate state websites.

The integrated feature set of MongoDB was another major plus for Avila, providing a holistic, end-to-end solution. Along with the storage capabilities of MongoDB Atlas, Avila uses MongoDB Atlas Search for lexical searches across aggregated grant data. Avila also uses MongoDB Atlas Vector Search extensively throughout the application, employing semantic embedding to understand the meaning and context of data, unlike lexical search. This powers more nuanced grant discovery, efficient NOFO processing, and accurate RAG. “As a lean startup, Avila hasn’t needed a dedicated database team. MongoDB just works and lets Avila scale as it grows,” said El-Sayed.

The dynamic schema adaptation MongoDB offers helped Avila ship its minimum viable product in just four weeks. The adaptation is also critical to the product’s continued development, enabling the company to tweak schemas as it discovers new grant sources and different or evolved data structures. Additionally, MongoDB facilitates accelerated development and efficiency — a boon for a company focused on maximizing resources.

“It’s an interesting moment when startups can do a lot with a lot less, where coding and computing tools let you run a tight operation,” said El-Sayed. “I want to run this company in a capital-efficient way, and MongoDB gives me the ability to do that.”

Since the initial development process, Avila has considered the MongoDB team a steadfast support system. “As Avila has iterated, MongoDB has been there as a trusted partner,” said El-Sayed.

Avila logo
“There’s a huge opportunity here: tens of thousands of municipalities, schools, and nonprofits to serve, and more resources that we can pull from. Scaling to a new set of opportunities is fully achievable with MongoDB. The sky’s the limit.”
OMAR EL-SAYED
Founder and CEO, Avila

OUTCOME

Cutting the grant search and application process by 90%

Avila currently indexes around 100,000 grant opportunities across various sources, providing unparalleled access to potential funding. It empowers organizations to find more opportunities and navigate the process 10 times faster — and, as El-Sayed puts it, “take more shots on net.” This helps agencies that lack dedicated grant staff and maximizes their ability to support their communities.

The platform drastically reduces end-user workload, cutting search and application time by approximately 90%. Tasks that once took hours now happen in seconds, with semantic matching delivering rapid results. Instead of tediously analyzing NOFOs for inapplicable grants, customers can get to work pursuing attainable funding.

Beyond the impact on customers, Avila has achieved several tangible business and technical benefits. With an estimated 10x faster development speed, the platform achieved product-market fit and secured paying customers within about four months of implementation. Avila is confident that the scalable architecture of MongoDB will support its future growth.

“There’s a huge opportunity here: tens of thousands of municipalities, schools, and nonprofits to serve, and more resources that I can pull from. Scaling to a new set of grant opportunities is fully achievable with MongoDB. The sky’s the limit.”

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