Marc Scibelli
Marc Scibelli

Motific Platform - Unlocking Trusted GenAI Adoption for Enterprise Customers

At Cisco, we embarked on a transformative journey to develop Motific, a platform engineered to accelerate and secure Generative AI deployments.

About Motific

About Motific

About Motific

About Motific

Motific is designed to empower IT Admins, Data Scientists and Developers to deploy powerful, secure AI applications while securely leveraging existing organizational data sources and maintaining rigorous policy controls for compliance.

Organization

Cisco

Role

Design Lead

How do we design human-agent interfaces that are consistent, comprehensible and scalable across products?

Approach

Approach

Designing Motific for enterprise deployments presented unique challenges, notably in compliance with stringent security policies, managing complex user access controls, and seamless integration with existing enterprise data sources.

One of the early steps in Motific's development was the identification and analysis of our target user group - IT Admins and their workfow. In this particular case we were exploring a new are of AI deployment and management so it was important we listened to the market segment while approaching it with point of view n how best to manage this emerging issue.

The HAX Framework

The design principles gave us a foundation, but teams still needed a way to apply them consistently in real products. We set out to create a system that connects those principles to the tools, components, and checks developers use every day. That effort became HAX—a unified framework for designing, building, and governing meaningful human agent collaboration.

HAX
Principles:

Design for collaboration

Five research based, human-centered rules: Clarity, Control, Recovery, Collaboration, and Traceability that define trustworthy agent behavior.

HAX
SDK:

Build with
consistency

Toolkit that turns those principles into schemas, components, and checks so agents act and explain predictably.

Custom Repositories:

Reusable Explainability:

Behavior layer that travels with the agent. The same evidence, reasoning, and actions appear across any product or surface.

Portable Explainability:

Consistency Everywhere:

Behavior layer that travels with the agent. The same evidence, reasoning, and actions appear across any product or surface.

The HAX Framework

The design principles gave us a foundation, but teams still needed a way to apply them consistently in real products. We set out to create a system that connects those principles to the tools, components, and checks developers use every day. That effort became HAX—a unified framework for designing, building, and governing meaningful human agent collaboration.

The design principles gave us a foundation, but teams still needed a way to apply them consistently in real products. We set out to create a system that connects those principles to the tools, components, and checks developers use every day. That effort became HAX—a unified framework for designing, building, and governing meaningful human agent collaboration.

HAX
Principles:

Design for collaboration

Five research based, human-centered rules: Clarity, Control, Recovery, Collaboration, and Traceability that define trustworthy agent behavior.

HAX
SDK:

Build with
consistency

Toolkit that turns those principles into schemas, components, and checks so agents act and explain predictably.

Custom Repositories:

Reusable Explainability:

Behavior layer that travels with the agent. The same evidence, reasoning, and actions appear across any product or surface.

Portable Explainability:

Consistency Everywhere:

Behavior layer that travels with the agent. The same evidence, reasoning, and actions appear across any product or surface.

process

Our team took an evidence-based design-led approach, allowing for rapid iteration and continuous feedback and fostering ongoing collaboration across design, product, and engineering teams. We conducted extensive interviews, mapped out valuable touchpoints in managing AI deployments and gained a deep understanding of perspectives, pain points, and challenges.

All of this was crucial to explore this emerging area and innovate both around IT best practices and AI deployment next practices.

We initiated a design discovery process which enabled a systematic exploration and validation of ideas, ensuring each phase, from discovery to release, was grounded in evidence and iterative improvement.

We initiated a design discovery process which enabled a systematic exploration and validation of ideas, ensuring each phase, from discovery to release, was grounded in evidence and iterative improvement.

outcome

The benefits of our design-led strategy were evident throughout Motific's rapid development.

Early and continuous user engagement, prioritization of learning, and evidence-based decision-making allowed us to evolve rapidly from an initial concept to a market-ready product in less than 10 weeks.

Our approach ensured our solution was both relevant and innovative and aligned with Outshift’s mission of driving innovation through curiosity.

Creating Clarity

The idea of a Motif

The idea of a Motif

The idea of a Motif

A Motif is a bundling of the data, user access, policies and model that is then deployed and managed inside Motific. I created the idea of a "Motif" as a cognitive aid to guide the user toward understanding the purpose of their actions and how they relate to the overall system.