Discovering America’s Seed Fund

In the last post, I introduced how I took my idea for a self-driving skatepark, and turned it into an invitation to submit an SBIR Phase I proposal.

In this post, I’ll go through the process of preparing and submitting that Phase I proposal from scratch, as someone who had never written a grant proposal before.

Americas Seed Fund

If you’re not familiar, the SBIR program gives up to $2,000,000 (with zero dilution!) to small businesses based in the United States to develop and bring to market potentially breakthrough technology.

It starts with a Project Pitch, where someone from the NSF will take your idea, and see whether or not it will be a fit for their currently open programs. My initial proposal was a self-driving robot to protect cyclists, under the AI solicitation, and it was accepted.

When I received that acception email, I immediately became intimidated.

I assumed submitting a formal proposal would mean writing something very similar to an academic paper, something I’d never done before. (I didn’t attend university, instead opted to live in central america and farm for a few years.)

A Stroke of Luck, Meeting an Expert

In a stroke of luck, I met someone who had received two Phase I proposals a few weeks later. This person was an amazing help, and shared their full, successful proposals. This gave me a giant leg up, boosted my confidence, and important context for just how high the standards are for acceptance.

When I read his proposals, it became clear successful proposals do read like an academic papers.

But beyond being academic, these papers also had make a convincing argument for a potential technical breakthrough, show a sustainable business from said breakthrough, show a market need for the technology, and build a realistic budget and team to execute the vision.

This is a lot to take on!

My industry experience has taught me that ideas and strategies must first be tested in the real world. So I set out to start building the physical pieces of what would eventually become my strategy with the SBIR application.

Researching the Problem Space

So I started with my initial goal: How do we protect cyclists?

As I dove in to the data around cyclist safety, I found that cyclists and pedestrians tend to get hit at night. Given that computer vision doesn’t work at night (low light sensors are expensive, and infrared models need high powered lights and to be custom trained), my original computer vision only approach wouldn’t work.

Instead, I’d need a sensor that could augment the computer vision pipeline I’d originally applied with in order to truly be effective.

It turns out there’s a sensor that works in the dark, and is capable of augmenting computer vision.

mmWave radar allows for accurate tracking of objects that are occluded, and allows for more accurate speed estimation.

Using a computer vision pipeline augmented with mmWave radar would allow for an extremely resilient approach to tracking objects around a cyclist.

Luckily, the investment in self-driving vehicles has created a market for low-cost mmWave sensors. This means we can take off the shelf sensors meant for tracking vehicles while driving, and repurpose them for bicycle protection.

Applying the Problem to the State of the Art in Artificial Intelligence

Of all the industries I know of with rapid change, artificial intelligence in late 2023 and early 2024 have to be in the lead.

Over the course of the month’s research, state of the art architectures for route planning and object tracking moved from transformers, to diffusion, back to diffusion transformers. I continuously updated what my technical approach would be, given the improvements I read from the papers. I tried out a set of models that would work together to target my approach.

As I worked through it, a part of my solution would involve training a custom model. This meant I had to have a realistic approach for how I’d gather my data, train my model, and test that my model would indeed perform well in the expected environment.

Bootstrapping A Data Pipeline

recording from a cycle run

How do we bootstrap a training set to build a model (or ensemble of models) to protect cyclists?

I decided that I’d need to collect data from a fleet of cyclists in the real world. It seemed a bicycle mounted device would be best way to collect a dataset.

So I built a prototype using an NVIDIA Jetson Orin Nano, a depth camera, a DeWalt 20v battery, and a mmWave radar. I built a pipeline for recording bicyclists, and scoped out a computer vision pipeline for live tracking of hazards.

cyclist prototype

As I was writing this up for my proposal, I ran into a cyclist who had an interesting device attached to his bicycle. I asked him about it, and it was a radar device from Garmin.

It seemed my idea for mmWave radar was on the right path.

Doing the Paperwork

But as the technical details were progressing, the necessary paperwork was also there, waiting.

The NSF has a few requirements for the company who applies for funding. In the extremely helpful webinars they give, they go over all of the needs for your company.

In particular, one of most frustrating parts of the paperwork process is getting a UEI from You need to provide a set of documents that identify your company, and then follow up in the web application to ensure the UEI is actually created. I almost missed this, because it’s not clear in the UI which stage you’re in, and how you progress!

Additionally, you need to come up with a budget for your proposal. In the webinars (again, extremely helpful!), they emphasized that they’d help with creating a realistic proposal if they were interested in funding the approach.

Despite this, I took the time to try and find what I thought would be a realistic approach. Thinking through the process with the budget to accomplish my Phase I goals actually helped a lot with my overall strategy.

My Biggest Challenge, Industry Support

A key part of a successful Phase I proposal is having industry recommendations. They’re not required, but highly encouraged. This can take the form of a letter from another company saying there is a market for the product, should it come to market.

This is one area where I really struggled. I’d say I failed here if completely honest.

I started by emailing the person in charge of cyclist safety in Florida. It turns out there’s an elected official who’s entire job is to minimize cyclist deaths.

After five emails and five phone calls to his office and assistants, I got nothing back from this person.

Frustrated, I turned to my contact who’d already received two Phase I proposals. He said it would be hard to get a politician to say something on the record, and recommended I reach out to a local cycling shop.

The first cycling shop I went to, they immediately went into a diatribe about how cyclists getting hit was their own fault. When I presented my approach for reducing cyclist deaths, they simply said “we don’t do technology”.

I went to another bicycle shop, and this time they immediately “got” it. They’d ridden earlier in the day with their Garmin radar device, and knew about the cyclists who’d been hit in the past month.

It seemed after a frustrating few first interactions I’d finally found my letter of support.

This turned out to not be the case.

Despite meeting multiple times, they never followed up. As the deadline window was approaching, I submitted without their letter of recommendation.

In hindsight, I should have been more aggressive about this key component. I wanted to wait until I had a clear vision of what the device would look like, and by the time that vision was there, it was too late in the process to really have time to court a company.

If I could do it again, I’d start with a “less big” ask for a few companies at the beginning. I’d try to get them to publicly commit to public safety, and build a relationship from there. It seemed it was a bridge too far to cold ask for support for such an alien process.

Pressing the Submit Button

By this point, I had what I hoped was a great proposal that matched the style and rigor of the proposal that had been shared with me. I was proud, and confident it was as good as I’d be able to muster.

When I went to submit my proposal in the actual portal for submissions, it became apparent I’d written it in the wrong format. It turned out that the site expects the proposal to be broken up into specific PDF pieces. I rewrote what I’d written again, and made it fit the format they’d expected.

But once I’d finished it up, I still had a few days remaining. I tried once more to get a letter from a business, but just didn’t get one in time.

I submitted my proposal despite this, we’ll see whether or not it matters.

Was it worth it?

The SBIR process requires a person be in a unique situation. They must have a small business, and be willing to commit to working on the proposed project at least 50% of the time for the next 6 months.

They also need a market opportunity, and a team that seems capable of both building a breakthrough technology and bringing it to market.

It’s also a non-zero amount of work to put together this proposal. Given the proposal must be ambitious, it can feel as though you’re not being realistic, and that the proposal itself is mostly a pie in the sky idea.

I certainly struggled with that feeling through the process, and realistically, there was a non-zero cost to attempting the proposal.

But the process of taking an initially scary idea to a full proposal was an amazing learning experience. It helped me form a holistic approach to thinking about a disruptive robot technology, and what market conditions must be in place for it to succeed. It also forced me to put myself out there, despite the lack of buy in from the industry.

I hope my story inspires you to pursue ideas that scare you, no matter the outcome.

If you’re interested in doing a proposal too and have questions, don’t hesitate to reach out. Please reach out via Twitter.

In the meantime, I’ll share my updates as my proposal gets reviewed.

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