How Does Board Integrate with your Existing Data & AI Ecosystem?

Every company has a variety of business systems that their teams are operating on

a daily basis. What you don't want to be doing is have hundreds of planners

independently writing their own logic, writing their own agents, and then very

soon, you're just going to have a spaghetti of all of this across your organization

without a clear definition of what is the right workflow logic, what is the

approval process, et cetera. Now, this is where we would highly recommend a layer

sitting on top of your enterprise data fabric called a contextual decision

layer. This is a logical layer that understands

context and plans, and helps you drive action.

So this is a layer that sits on top of your systems and data fabric, but sits

right below all of your agentic and AI services layer.

Yes, you want to take advantage of AI, but again, you want to be doing all of these

hardcore calculations on a board engine.

And because this is where the less you use and burn tokens, and the more you take

advantage of a board software engine, this is the most cost-effective way to go do

this. Then as you start to go even deeper around causal reasoning and understanding

root causes, cause and effect to make better decision, probabilistic methods of

AI just does not naturally gel into this, and this is where you need the

powerful tool such as Board to go help you around deeper root cause

analysis and digging back. And then finally, if you're talking about

really have agents do write-backs, you want

to really start very controlled write-backs with the right amount of governance,

validation, and auditability. And this is again, where Board can

absolutely be the safeguards for all of your agents.

So in a nutshell, what we would say is there needs to be a separation between the

agents and then your business systems or your data fabric so that the agents are

not running rogue and either pulling data out with no context,

running complex calculations without fully understanding it, or doing any

write-backs into your data layer.

And so this is where a contextual decision layer such as Board is going to be very,

very powerful

as a reference architecture for your agentic journey in decision-making and

planning.