There is a lot of tech happening in Pittsburgh. Life sciences, AI, robotics are all established ‘pillars’ of our economy, and forecasted to grow. These are all capital-intensive sectors, flourishing in a town that is not exactly awash with capital.

Inevitably, the conversations with technology entrepreneurs in Pittsburgh will drift to the lack of capital in Pittsburgh, and how to overcome that obstacle. Pittsburghers do seem to overcome it.

Every ‘second tier city’ (ie, cities that aren’t Silicon Valley, NY, Boston, Austin) with a technology community has somehow overcome this. The technology companies and the environment in these cities share some common attributes:

* Entrepreneurs learn how to rub the head, and the tail, off of a nickel

* Entrepreneurs are willing to work a second or third job to provide themselves with the runway they require to build their businesses

* Companies focus on customer acquisition at the earliest stage, rather than capital acquisition

* Companies are adept at acquiring non-dilutive sources of funding, such as SBIRs

* A university system that trains and graduates technology domain experts and supports technology commercialization

* An economic development support system that can provide some combination of seed capital, industry cross-connects and access to talent (that is, serve as a focal point for companies and people attracted to those companies)

* A ‘moderate to very active’ angel investor community

In fact, in 2014, CB Insights published a remarkable stat regarding institutional funding (venture capital); namely, that 73% of technology firms that exited that year took in no institutional capital. None. The presenter of this graph mentioned that this stat in 2017 was even more biased towards business building vs. raising equity capital.

This fact was presented by a west-coast investment bank at a breakfast gathering for entrepreneurs. Frankly, many in the audience dismissed it as, ‘no way.’ It is so counterintuitive given the daily news about unicorns and funding announcements that we are all bombarded with every day by the multiple websites that follow the technology sector.

Obviously, software companies shift this data, but the presenter, when this was pointed out, agreed, but stated that even hardware companies were more often built without institutional capital, but to a lesser degree. Life science businesses, as you would suspect, bucked this overall trend.

But the point is obvious. At the end of the day, starting up and building a company is a value creation contest, not a money raising contest.

A Robotics Company Finds First Success with Bootstrapping

This white paper chronicles the journey one Pittsburgh-based robotics company that has managed to launch and bootstrap to gain adoption/customers without raising any outside capital. That journey remains underway; the company may take in capital in the future and the ultimate outcome for this company remains unclear. One caveat – every company is different. This is not presented as a blueprint; rather, it will hopefully stimulate entrepreneurs to think differently or more broadly as they work through the how of starting up and moving forward to build a business.

Company background

Platypus, located in Pittsburgh (, utilizes autonomous, cooperative boats to collect data about inland waterways. That data is reported, characterized and analyzed using the company’s predictive analysis platform, Aquatical Analytics™. The company has performed data collects on every continent except Antarctica, and has shifted its focus from boat design, which is now optimized for manufacturing and cost, to expanding the analytics capabilities of its SaaS software platform. It does not sell boats. The boats are provided on a Robotics As A service model, and returned to the company after the data collect is completed (either by company staff, or a 3rd party contractor).


The CEO of this robotics company, Paul Scerri, was the director of a robotics lab at Carnegie Mellon University for 14 years. During that time, one of the projects tackled by him and his team was the role that robotics and AI could play in a disaster recovery scenario, in a remote, underserved locale. Specifically, the project focused on collecting data about inland water after a natural disaster (assessing the impact of the event on sources for drinking water).

First Challenge:

The problem was well defined by the team, which had gained experience in the field. The CEO focused on solving the problem within the constraints of the application, rather than constructing the most elegant solution, the team focused on constructing the most relevant solution. This resulted in a very, critical design decision – the boat had to be readily available, using off the shelf hardware components, and very inexpensive. Essentially, the team had to build a disposable robot.

                    Second Challenge:

Engineers had to anticipate unknown conditions; for example, a river that was flooding and full of debris This project would have never seen the light of day had the focus been predicated on implementing a fully autonomous boat, due to the variability of the application. RC controls were as important as the boat’s autonomous capabilities to b effective. Rather than attempting to develop a fully autonomous boat that could anticipate the anticipatable, the balance of autonomy and human control was the right one for the operating environment.

Third Challenge:

Platypus needed to build a prototype with the team that was on board at the time. The challenge, the team turned over every four to five months, and were predominantly software / AI undergrads and graduate students. The simple hardware and mechanical components that were implemented were enabled and made useful by advanced software controls, the development resource available to the CEO.

Fourth Challenge:

Lastly, the director of the lab had taken business classes as an undergrad and managed corporate commercialization partners as the director of his lab at CMU. He understood that ultimately the technology would have to support a viable commercial financial model. The low-cost design decision made at the onset enabled an economically viable Robotics As A Service business model, which ultimately emerged as the preferred approach in the customer and investor communities.


Paul made the decision in 2014 to pursue the commercial opportunity. This required several decisions and actions:

* Negotiate a technology transfer with CMU

* Locate space

* Recruit and deploy a staff

* Construct a rudimentary, flexible business plan

* Generate revenue

The technology transfer aspect of the commercial transition proceeded smoothly. The rights to employ the intellectual property were conveyed and included a secondary

benefit. Now that the university was on the company’s cap table, they actively assisted with customer and staff introductions in order to help to propel this new company forward.

The space requirement was solved in partnership with two other university spinouts. All three companies required space that exceeded the legendary ‘garage’. So, all three went in on a space on Robotics Row (an area in the Strip District of Pittsburgh where robotic companies coalesced, at rates that were very affordable when shared.

Getting Creative with Compensation

Recruiting talent was a challenge. The founder took a $20K cash advance on a credit card, but the majority of that went to establish the office and build a small number of boats, and he didn’t possess the cash to pay salaries, let alone pay market rates. So, he did several things:

* Utilized the currency available to him – stock options; and

* Aggressively promoted the key attributes of the business back to the people who had, and were working in the university lab – very challenging work, hands-on field applications and technology that is being used for the good of the planet; and

* Was completely flexible with hours worked, and where those hours were worked; and

* Explicitly stated that moonlighting (working a second job) was acceptable

* Every contractor, regardless of position, spent time, with a boat, on the water. This resulted in a part-time staff that understood customer issues, not just their areas of expertise

The results were both effective and chaotic. A small group of part-timers, numbering 10, committed to varying levels of time to the company. The founder was adept at managing fluid workforces, like that in his university lab. People were at the office at all hours, working as teams assembled with people ’on hand’, at the time. It was not the most efficient workforce, but it got the job done, the job required at the time. Also, the company avoided a common challenge of building a staff that couldn’t scale as the technology evolved from a technology / product, into a business.

Time to Generate Revenue

On to the hard part – generating revenue. Marketing videos were developed using smartphones and distributed via social media and through the web site. Concurrent with that, the founder took every relevant speaking engagement. He implemented the beginnings of an organic marketing campaign. He didn’t overplan – he constructed a cost model and established high level targets in order to frame the company’s early business activities and measure progress.

It worked. A handful of small mapping projects closed, and the company was on its way. It never succumbed to ‘free pilot syndrome’ and was able to generate cash, albeit modest amounts of cash, from the get-go.

Enough cash was quoted to pay for travel to and from the customer deployments, and the company managed the deployments with the small number of boats it had developed. The product roadmap was defined by customer interactions, and the part-time employees were being paid as contractors when new customer transactions closed.


Since its modest pre-launch and launch phases, Platypus is now operating under its own power. It can’t always go as fast as it wants, and it’s still not paying employees full market rates, but its steps forward are

* Laser-focused on customer acquisition, expanding its marketing capabilities and dialing in its business and pricing models

* Engaging subcontractors to drive cost down further and facilitate ease of assembly

* Evolving its business planning function architect how it will traverse next step function in its corporate development

* Now focusing the majority of its development resources on expanding its software analytics platform and construct data collection partnership to shift the company’s core business to analytics

* Engaging senior-level business talent, on an interim basis, to expand its business strategy and execution to assist with the new issues that the company will face as it transitions to a more scalable business model

As mentioned earlier, Platypus may still choose to raise outside money, but when it does, it will be doing so as a business (as opposed to a technology or a product) that desires to grow bigger, faster.


This whitepaper is not intended or presented as a blueprint for a startup tech company. It is how one company solved its early stage and entered the elbow of the growth curve. The intent was to illustrate how creative approaches can be used to launch and grow a business. Additional takeaways to consider, that may be relevant to a more generalized situation:

* Service businesses are generally easier to start than product businesses. And sometimes, a product company can launch as service company.

* Say you have the idea for the next generation carpet cleaning machine but can’t afford to commercialize it. Why not start a carpet cleaning business with rented equipment to generate the cash required to develop your new machine, and gain invaluable field experience before spending a single dollar on product development?

* If you are a business person rather than a domain expert, you must figure out where those experts are today. One approach is to reach out to the tech transfer department at universities, which generally are a hotbed for product and service opportunities and can be very helpful in connecting technologists and business builders

* If you are a domain expert, don’t be afraid to link up with a business person. 1+1 can be greater than 2

* Don’t discount the value of deploying a disruptive business model into an existing market. How you do business can be used as a competitive weapon

* One last thing. If you can’t convince people to follow you, perhaps your vision isn’t compelling

Author, Dan Seitam, Business Strategist, PD Marketing PGH

At PD Marketing PGH, we work with you to construct, optimize and market your growth plans, regardless of your stage. We’d like to learn more about your business, and how we can help. Visit us at