Sasha Martynchuk
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2025

Lumus AI

Lumus AI is an enterprise AI orchestration platform designed to make powerful AI capabilities accessible to organizations of all sizes. Our mission is to transform how businesses build, manage, and deploy intelligent systems by providing intuitive tools that balance power with accessibility.

Founded by a team of AI and enterprise software veterans, Lumus AI is trusted by leading organizations across industries to power their most critical AI initiatives.

My role
Senior Product Designer
Timeline
March 2025 – May 2025 (2 months)
Team
PM, 2 Engineers
Lumus AI — product imagery

Key contributions

  • End-to-End Product Design. Led the design process from research through information architecture and feature definition.
  • Visual Workflow System. Developed a unique visual workflow system that balances power with accessibility.
  • Cross-Functional Collaboration. Facilitated collaboration between business, engineering, and AI research teams.
  • AI Assistant Builder. Designed an innovative AI assistant builder that differentiates the platform.

Current results

  • Successful Beta Launch. Platform launched in closed beta with multiple enterprise clients actively using the system.
  • Design System Integration. Engineering team successfully implemented the Align UI design system, accelerating development and ensuring consistent user experience.
  • User Satisfaction. Beta users rate the platform 4.7/5 for usability and have highlighted the assistant builder as particularly valuable.

01

The challenge

AI has rapidly evolved from experimental technology to essential business capability, but organizations face significant challenges in effectively implementing and scaling AI systems:

  1. Fragmented Tools and Approaches: Teams use disconnected tools for different aspects of AI development, creating silos and inefficiency.
  2. Collaboration Challenges: AI development involves multiple stakeholders with different expertise, but existing tools lack effective collaboration features.
  3. Governance and Oversight Gaps: Organizations struggle to maintain visibility and control over increasingly complex AI systems.
  4. Integration Difficulties: Connecting AI capabilities to existing systems and data sources requires significant custom development.
The fragmented AI tooling landscape Lumus set out to consolidate

02

Design process

Research methodology:

  • Stakeholder Interviews: 8 interviews with product managers, developers, and AI specialists
  • Competitive Research: Evaluated leading AI orchestration platforms
  • Technical Feasibility: Collaboration with engineering to understand implementation constraints

Key insights:

  • Visual Programming Gap: Existing tools either sacrificed power for simplicity or became overwhelmingly complex for non-developers.
  • Assistant Creation Complexity: Building product-specific AI assistants required specialized expertise across multiple tools.
  • Integration Challenges: Connecting to enterprise systems often required significant custom development.
Research and workshop artefacts — 1 of 4
Research and workshop artefacts — 2 of 4
Research and workshop artefacts — 3 of 4
Research and workshop artefacts — 4 of 4

03

Software solution

A comprehensive AI orchestration platform designed for enterprise teams who need to create, deploy, and manage specialized AI agents without deep technical expertise.

Agents

Your command center for all AI assistants.

Agents — final solution

Workflow builder

Build an AI Agent in seconds using simple building blocks.

Workflow builder — final solution

Custom AI Agent Builder

Create your own AI Assistant, custom chatbots, website widgets, browser extensions, forms, and more — all without writing a single line of code.

Custom AI Agent Builder — final solution

Integrations Page

Connect your AI agents to the tools your team already uses.

Integrations Page — final solution

04

Takeaways

  • Always start with information architecture. Creating a solid foundation for the complex feature set ensured a coherent user experience.
  • Balancing power and accessibility Progressive disclosure and thoughtful defaults made complex capabilities approachable.
  • Early design system saved dev time Prevented UI rework and enabled faster, more consistent delivery.
  • Early engineering collaboration. Partnering with engineers from the concept phase ensured technical feasibility and smoother implementation of complex features.