INSIGHTS

Custom Agents in Action, Unlocking Real Value

By: Michael Patton, Chief Operating Officer and Co-Founder at MUDRICK & ASSOCIATES

This article was written without the use of AI.

Custom Agents in Action, Unlocking Real Value post image (3)

The Bard understood the significance of culture...

Building Agentic Organizations Part 2: Custom Agents in Action, Unlocking Real Value.

Recently we discussed why templated agents often overlook an organization’s unique culture and the context required for making critical business decisions. When people make business decisions they are doing so with these nuanced details layered into their process. This is why bespoke decision science is the key to making responsible and effective AI agents for organizations.

But what does that actually look like? Let's take time to look at how custom agentic systems, built with bespoke decision science, are driving real value for different parts of the organization.

Real world examples:

Sales and Business Development

We build agents with machine learning that predicts the next best customer (client) and prioritizes highest value opportunities. A human in the loop feedback mechanism is built allowing the agents to learn to prioritize company culture and human context in decision making. When/If the AI agent falls short with a recommendation, the team provides feedback directly into the agent which allows for continued improvement and further alignment. Sales teams are able to shift the time spent in the past doing manual data hunting to making more impactful outreach and building meaningful customer relationships.

Executive Insights

Similarly, we build highly secure natural language chatbots (with the same human in the loop feedback mechanism) trained on the organizations own unique enterprise data to give leaders near instant insights to complex business questions. This eliminates weeks of back and forth with analysts and enables faster, more confident decision making.

Forecasting and Operations

Here we take it a step further, from descriptive to prescriptive. Sophisticated ensemble machine learning models deliver granular, accurate forecasts at scale (FAR beyond legacy tools). Teams gain confidence in inventory, demand, and resource planning. Human in the loop checks and balances ensure continued refinement and accuracy. We've seen >$150M incremental lifts in annual revenue from this increase in forecast accuracy for large organizations.

AI agents shouldn't replace company culture, as they say "culture eats strategy for lunch." Done right, they allow more time for innovation, collaboration, and strategic thinking.

How is your organization using AI Agents? Have they been useful? Where do they fall short?