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Hey, everybody.
My name is Akshay Krishnaswamy, and I'm
the Chief Architect for Palantir's commercial business.
I'm excited to talk to you guys today about the Foundry
Platform.
Just one note on who Palantir is for folks who might not know.
We were founded in 2003 with the mission
of building data-driven operations
and decision-making software.
We got our start in intelligence and defense,
working across national security contexts.
And a lot of how we think about our software
was informed by the kind of learnings
in those front-line deployment settings.
Today we work across a lot of different industries,
40-plus industries, a lot of places outside of government
and across the commercial sector,
in the non-profit sector, and all parts of the government
now as well.
We have three software platforms at Palantir
that we think of as operating systems.
Gotham is our operating system for intelligence and defense.
Apollo is our operating system for deploying and managing
complex software footprints across
many different environments.
And Foundry, which we're going to talk about today,
is what we think of as our operating system
for the modern enterprise.
If we think about the modern digital landscape,
we recognize that most organizations are already
on a journey.
They're setting up data lakes, data warehouses.
They're deploying many different types of analytics solutions.
And in fact, we're partners with a lot of the folks
that you might think of out there in the industry.
I think what we tend to see is that those technologies come
together in a very classical reference architecture.
You have different data sources coming in as batch and streams,
being loaded into different data platforms, data lakes, data
warehouses.
That data then undergoes different types
of transformation.
It's then prepared for analytics and typically
then deployed into BI applications or reporting.
You can think about this as a linear flow
or an assembly line of data, where you have producers
on one end responsible for putting the data together
and then producing the data products,
which are then consumed by different types of business
users through reports or dashboards.
And while there's nothing inherently wrong with reports
or dashboards, it does leave a lot on the table
when it comes to, well, how do I benefit
from people learning what to do when they actually
see that data?
How do I understand what actions to take
as a consequence of presenting that data to business users?
And how do we actually engineer a feedback loop between people
on the front lines and people in the back office
actually doing data and analytics work?
You see data coming together in reports or dashboards.
You might notice an insight.
But then as a business user or an operational user,
you just pivot away to the next thing you have to do.
And we think that while this is sufficient,
this model, this assembly line for reporting
and for dashboards, most organizations that we talk
to feel the need to go beyond this model,
just given the complexity in the world.
And so you're limited by this producer-consumer paradigm.
And I think if we think about what's happening in the world
today, both in terms of exogenous shocks
out there in the world, the complexities
inside organizations' four walls with their partners, just
having this assembly line approach isn't
sufficient for dealing with that complexity.
And so what we see over and over again
is that folks want to be able to use the exhaust, the learnings,
the feedback from people interacting
with data and models to better inform their processes.
They want to consider those learnings not exhaust,
but fuel for the business.
And so we think about, well, how do
we turn this typical producer-consumer paradigm
on its head and actually have a different modality,
where there are data producers and consumers
in every part of the business working together
in a common platform?
So we think about Foundry as providing an open architecture
for closing the loop between operations and analytics.
It provides the ability to bring your existing data and model
tooling together inside of an ontology which you can then
use to build workflows, applications,
and actually capture decisions with
to inform better operations over time in continuous learning.
With Foundry, we say to everybody in the enterprise,
to data teams, bring your data lakes.
Bring your data warehouses.
Bring all the data that exists across different systems
and connect that into Foundry as what
we think of as the nouns of the enterprise-- the semantics.
And to the analytics teams, we say the same thing.
Bring the models.
Bring the linear programming models, the ML models,
the stored procedures, and allow those
to be connected into the same foundation
as the verbs that go along with the nouns that give you
all the business processes.
And we think if you can then assemble this operating
layer iteratively over time through use cases,
you then build out a very powerful foundation
to do many things.
You can drive more and more operational
workflows that are read/write, where business users are
contributing their knowledge back into the foundation.
You can do more sophisticated analytics
like running scenarios and what-if analysis.
And critically, you can capture decisions and pipe those
to all sorts of different enterprise systems,
both new and old.
So again, we think by closing the loop,
it's a very different architecture
than the one-way assembly line of data.
In terms of how it works, Foundry
comes with everything you need from top to bottom
to implement complex operational workflows.
This includes data integration; model integration;
an ontology layer that encompasses
objects and relationships and actions and business processes;
an entire workflow layer that includes application-building,
self-serve analytics, and more; and a decision orchestration
layer that's designed to capture learnings from end users
and actually then feed those back
to analytics and data teams and other business systems.
And so for fresh architectures, we
think Foundry can get folks operational in days.
But we also understand that most organizations
have made investments in existing data and analytics
tools.
And so Foundry's modular architecture
allows you to bring your own data platforms, data lakes,
data warehouses, analytics tools, ML services,
and plug those into Foundry's data integration and model
integration layers and extend them up into the ontology
and into operational workflows.
And so Foundry is designed to work
in heterogeneous, complex architectures that are changing
over time, all the time.
One of the most common integration patterns
we get asked about is, how does Foundry
work with my existing data platforms--
my Snowflake, my GCP, my Azure, my AWS data warehouse?
And Foundry can be deployed in a mode that
is purely extending those platforms into operations,
where Foundry will never fracture
the source of truth that exists in those data platforms
and instead will marry them up with different analytics tools
and business processes to build the ontology
in a way that respects the governance
policies in place in those analytics and data tools.
And so you can think about this as setting retention policies,
security policies, and bidirectional data syncs that
will ensure that Foundry is always
in sync with those existing data systems.
As organizations evolve, we expect
they're going to continue to invest
in new data tools, new analytics tools, new governance tools.
And we've designed Foundry to make sure
that it can be a great citizen in a landscape that's
only going to get more and more complex over time.
As underlying data and analytics architectures
continue to evolve, Foundry is designed
to serve as a resilient, stable operating layer that
can continuously benefit from different systems coming online
and allow different user groups to make
better decisions over time using the ontology-driven approach.
So in summary, Foundry is designed to deeply integrate
with existing architectures--
data platforms, data lakes, data warehouses,
and all manner of analytics solutions
as well, integrating both data and analytics primitives
into an operating layer that can be
used to power feedback-driven workflows
across the entire business.
You can get started today with a single workflow in Foundry.
But the power of Foundry is really
in the compounding that occurs when
you scale from a single workflow to enterprise use cases that
span the entire organization.
We're excited to see what you're going
to be able to do with Foundry.
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