Pricing AI software
with zero usage visibility.
Booz Allen Hamilton built an AI platform for government and commercial buyers, years before the current wave of AI products, and had to price software it would never see running.
Booz Allen Hamilton grew the platform out of years of work helping large organizations manage complex technology projects. As the software became available, the firm faced two questions at once: how to price and sell it to government buyers, and how to commercialize it to large enterprises. Classified deployments meant it would never see how the software was used. No user counts, no transaction volumes. Every consumption model in the market started from a usage signal the firm would never have.
SPP worked inside the platform with Booz Allen’s AI model builders and enterprise architects to find where its value sat when usage could never be measured, and built the licensing, packaging and pricing from that reading, along with the partner channel for the commercial market. Following the engagement, Booz Allen Hamilton was awarded an $800 million contract to provide artificial intelligence services to the Department of Defense.
awarded after the engagement.
or transaction volumes.
moderate to mega-sized.
On classified networks, Booz Allen would never see a user count or a transaction volume. The consumption models the AI market runs on all begin with a usage signal, and this platform would never report. The software still had to be monetized, software and services revenue still had to line up with the value delivered, and the platform still had to earn back the services fees it would replace.
Pricing had to work without a usage signal.
An AI platform born
inside a services firm.
Booz Allen Hamilton helps businesses, government and military organizations transform: a global firm of approximately 27,600 engineers, scientists, software developers, technologists and consultants, headquartered in McLean, Virginia, with 80 additional offices around the world.
As an outgrowth of its work helping large organizations manage complex technology projects, the firm developed proprietary software of its own. One of those development efforts sat squarely in artificial intelligence. After years of building and testing different solutions, the platform was born.
The platform was built for two markets from the start, government and commercial, and the Department of Defense bought it after it was built. As the software became available, Booz Allen faced the challenge of figuring out how to price and sell it to government buyers and how to commercialize it to large enterprises. The firm engaged Software Pricing Partners (SPP) to monetize the platform for both markets and to leave Booz Allen with the capability to implement, analyze and refine the model itself.
What a consumption model
could not see.
Due to the highly sensitive nature of AI combined with deployments to classified networks, Booz Allen would have no visibility into how its software was used, including the number of users or the volume of transactions. That seemingly negated a consumption model of any kind and set up the challenges the engagement had to solve:
Usage nobody
could observe
Classified deployments meant no user counts and no transaction volumes would ever reach the vendor. Every pricing approach that starts from measured consumption was off the table before the engagement began.
Software and services
revenue to align
The firm had to monetize the software and align both software and services revenue with the value delivered and the value received, inside accounts where it already earned services fees.
A platform that would
replace billable work
The software would ultimately replace some of the work Booz Allen was being paid services fees to manage. The new model had to deliver enough revenue to overcome that reduction.
A partner channel
still to be built
To commercialize the platform beyond government, the firm would need a partner channel and a way to compensate partners that was effective and fair.
A model the firm
had to own
It was critical to the firm that the engagement deliver the internal capability to implement, analyze and refine its own pricing model once the work was done.
Pricing built from
the architecture up.
To price a platform of this complexity without a usage signal, Software Pricing Partners worked from the architecture outward, alongside the people who built it.
The services engagements,
read first
SPP reviewed the firm’s services engagements around the platform to see which billable work the software would replace and what those fees had been paying for. Software and services revenue were then set against each other on purpose, so the platform earned back the services it displaced.
Reading the architecture
for where value sits
With Booz Allen’s AI model builders and enterprise architects, SPP went through the platform layer by layer, technology, data and infrastructure, down to each AI model type in it and the chaining that routed work between them and composed one result, an early form of what the market now calls an AI harness, to find where its value sat and what the platform itself could stand in for when no usage would ever be measured. The licensing, packaging and pricing were built from that reading.
The market read
and the channel
Primary and secondary research established how buyers used and judged competing software and what they paid for it. That read shaped a licensing position buyers could scale into, and a partner channel for the commercial market, with a way to compensate partners that worked for the firm and for them.
Proving the model
without a history
No transaction history existed, so the candidate models were tested against sample transactions and scored against each other before one was chosen. The firm was left able to implement, analyze and refine the model itself.
What the pricing
architecture delivered.
Following the engagement, Booz Allen Hamilton was awarded an $800 million contract to provide artificial intelligence services to the Department of Defense.
Software Pricing Partners’ engagement with Booz Allen Hamilton delivered significant and positive results, including:
Pricing and packaging
that helped win the deal
The way in which the software was delivered, including the pricing and packaging model, was instrumental in getting the DoD contract.
A model that scales
to any deal size
Booz Allen now has a solution and a business model that scales to any customer size, from moderate to mega-sized deals.
A model the firm
runs itself
Booz Allen can now manage and adapt the model internally, including adjusting it over time and identifying the triggers for pricing changes.
Other architectures
that held.
Booz Allen is one of several architectures SPP has built where the usual usage signal was missing or could not be trusted. If you are pricing AI software and the telemetry does not tell you where the value lands, start with how SPP approaches AI software pricing.
BDNA
20% exit premium attributed to the pricing architecture. Two years post-engagement, Flexera acquired BDNA at a measurable revenue lift that went straight to enterprise value.
Nearmap
Aerial imagery SaaS rebuilt licensing and packaging around a metric customers could predict. Close rates moved to near 50% within the first month of rollout.
BambooHR
ARR grew 750% in three years and approached $250M, with the enterprise segment opened on the same pricing architecture.
Looking for profitable growth?
If your product runs where you cannot see it, if the usage signal arrives late or incomplete, or if the software you built is about to replace the services you bill for, the same architecture work applies. Bring your version of the problem.