Arkimedes
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Arkimedes is a B2B AI platform built for M&A and private equity professionals, supporting teams across deal sourcing, research, portfolio intelligence, monitoring, and board operations. My work spanned multiple core areas of the platform, including the AI Advisor, Knowledge Engine, Deal Sourcing, Board Assistant, monitoring and risk workflows, agent-building tools, dashboards, settings, and supporting product infrastructure. Across these areas, I designed information-dense dashboards, conversational AI experiences, node-based agent workflows, tables, Kanban views, calendars, multi-step wizards, contextual sidebars, document-management experiences, and monitoring interfaces. The broader product challenge was creating a coherent experience across a platform with many interconnected workflows — making sophisticated AI capabilities understandable, predictable, and actionable without reducing the flexibility required by investment teams.
Completion Date
Ongoing / 2025-2026
Timeline
Product design contribution during 2025-2026
Category
AI Platform / SaaS Product
Sector
Artificial Intelligence / Enterprise SaaS / B2B / Research Automation
The Challenge
Arkimedes combined several inherently complex product models within the same ecosystem: AI agents, company knowledge, source documents, generated outputs, monitoring systems, deal pipelines, board workflows, structured data, and configurable automation. The challenge was not simply designing each feature independently. It was creating a consistent interaction language that allowed users to move between very different workflows without having to relearn how the product behaved. At the same time, AI introduced an additional layer of complexity. Users needed visibility into what the system was doing, control over generated outputs, access to relevant context and sources, and clear ways to move from AI-generated insight to concrete action. The experience therefore needed to balance complexity, flexibility, transparency, and usability across a broad and evolving product ecosystem.
Approach
The design approach was shaped by four principles. Design systems, not isolated screens Each new workflow was considered in relation to the rest of the platform. Reusable structures, states, navigation patterns, tables, cards, contextual panels, and interaction models helped maintain consistency as the product expanded. Make complex information easier to navigate Many workflows involved dense datasets, documents, AI outputs, alerts, and multiple levels of context. Clear hierarchy, progressive disclosure, filtering, multiple visualization modes, and strong scanning patterns helped make that complexity manageable. Keep users in control of AI AI-assisted interactions were designed around explicit user intent, clear system feedback, reviewable outputs, and predictable actions. Where AI could modify or generate meaningful content, interaction patterns prioritized visibility and user control rather than silent automation. Prototype before committing For complex or ambiguous interactions, I used interactive prototypes to test product direction with stakeholders before refining the experience in Figma. Development requirements were treated as hypotheses to interrogate rather than fixed UX solutions, helping identify usability issues earlier in the process.
Outcome
The work helped shape a more cohesive product experience across multiple areas of Arkimedes, establishing stronger patterns for AI interactions, dashboards, knowledge management, monitoring, deal workflows, board operations, structured data, and navigation. Instead of treating each feature as a separate product surface, the design evolved toward a more consistent system of reusable interaction models that could support new workflows without introducing unnecessary complexity. This created a stronger foundation for the platform to continue expanding while preserving clarity across increasingly sophisticated AI and investment workflows. This phase of product maturation also coincided with Arkimedes securing a $2M pre-seed round, where the evolving product experience and clearer system-level thinking played a meaningful role in strengthening the company’s positioning at a key moment of growth. Due to confidentiality, this case study focuses on selected interfaces, interaction patterns, and high-level product decisions rather than proprietary business logic, customer information, or internal platform details.
Deliverables
Product design / UX flows / Dashboard design / Agent workflow design / Design system support / Prototyping / Handoff documentation
Credits
Andrés Soria in collaboration with Simple Studio