[Music] AIP empowers organizations to use large language models and other Cutting Edge AI safely
and securely the platform allows you to do three things first AIP lets you deploy large language
models and any other AI within your private Network anchored in your private data it helps you
create a full Fidelity real-time representation of all the concepts actions and decisions within
your business every truck every Warehouse every shipment every delay that can then be used by AI
second it enables you to define the ground rules around which data llms
and AI can and cannot see and what they can and cannot do on behalf of humans
you can do this Based on data sensitivity laws and regulations and competencies of the model
AIP provides the framework for AI to hand off tasks to other trusted task specific models
as well as to trusted humans finally with this great power comes great responsibility AIP brings
industry-leading guard rails to control govern and Trust the AI powered business of tomorrow
AIP automatically captures a full digital footprint of all AI inputs outputs and
actions including which AI was used for which decision which humans were in the
loop and how they align with specific business purposes let's take a look at it in action
in this demo let's say you're a leader at a us-based manufacturing company with customers
all over the country you've just received an alert that a hurricane is forecasted to hit
one of your major distribution centers in the South and you'll need to shut it down
you want to know whether you should accelerate delay or cancel orders to your customers and other
remediations you can take here in AIP terminal you can ask questions and collaborate with a
large language model or llm to what extent will hurricane Cynthia affect our distribution centers
in Louisiana as well as follow-ups how does this impact customer orders and Associated Revenue
under the hood as you ask questions the llm is able to Traverse a data Foundation powered by
real-time data feeds from all across your business importantly you can control which
parts of the business the llm has access to for example we can see here that although the
data Foundation contains employee level pii data the llm can't see or access that data
this has been informative you want to understand your options and take action you can ask AIP to
simulate a baseline scenario what would happen if we shut down the affected Distribution Center
it uses a transportation Network Optimizer model and shows you the impact on backlogs
revenue and commitments and highlights the impact on your highest priority customers
you can also see which specific orders can be seamlessly fulfilled by other distribution centers
this is a good start but you want to do more you want to know if you should Charter additional
trucks to increase the volume of deliveries before and after the closure what are some options for
chartering additional transportation for order fulfillment and the impact
AIP offers three simulated courses of action alongside estimated cost
option b a 20 truck capacity increase seems to have the best cost benefit trade-off in your
highest priority orders will all be taken care of after validating it further you propose your plan
for cross-functional sign-off for manufacturing supply chain and customer service stakeholders
let's look under the hood again many of these steps required a deep understanding of how your
business works L alums alone don't have the right context and we definitely don't want
the llm to give answers not grinded in reality AIP connects llms with trusted models across
your business including forecasting optimization machine learning and standard procedures AIP then
facilitates a secure handoff between these models as needed which keeps each model in its own lane
this lets you then use the llm plus all of your other models in concert
safely to enable reasoning through the different scenarios and courses of action
all stakeholders have approved your plan and you now want your operational team to get cracking
much of the chartering and rerouting has already happened through automation as you authorized the
operational team can monitor from their dedicated workspace and adjust as any surprises come up
they'll also need to stay in the loop for certain steps by policy such as verifying
customer consent for early deliveries as they make decisions and updates routing
and optimization models rerun autonomously on their behalf within the limits around key kpis
as decisions are made they are continually pushed to your operational systems triggering real world
action they're also logged for future review let's go under the hood one last time and look at what
enables your organization to safely govern llms and other AI to assist you through scenarios such
as this one here in the AIP control panel you can set the guard rails and limits per model including
which data objects they can see which actions they can recommend or take on behalf of humans which
tasks and workflows they are trusted to drive who can use them how cost is attributed and so on
you and your organization have formed an optimal multi-pronged plan of attack that are taking real
world action within minutes all using natural language within AIP without a single line of code