SeemaS - Enterprise FinTech AI Platform for Financial Valuation by Dmitriy H.SeemaS - Enterprise FinTech AI Platform for Financial Valuation by Dmitriy H.

SeemaS - Enterprise FinTech AI Platform for Financial Valuation

Dmitriy H.

Dmitriy H.

SaaS • FinTech • Enterprice • Startup • AI Workflows • Design System SeemaS is an Al-powered enterprise platform that helps financial advisory firms streamline complex valuation, transfer pricing, global reporting, tax compliance, and regulatory workflows.
Role: Product Design Lead · Initially the sole product designer Scope: Product UX/UI, information architecture, AI interactions, design system, and implementation support Team: Founders, domain experts, product managers, engineers, and fellow designers
I joined SeemaS as its first product designer when the platform was still an idea. Over two years, I led its design through the MVP launch and platform 2.0, working with founders, tax and valuation experts, and engineers to turn complex financial methods into usable workflows.
SeemaS helps corporate tax and valuation teams prepare data, run analyses, review results, and produce reports with AI support.

The Challenge: Different financial analyses require different inputs, methodologies, and outputs. The platform needed to preserve that specialist depth while giving users a consistent way to find their work, move through an analysis, interpret results, and collaborate.

We first had to make the core journey work: from providing data to reviewing an analysis and preparing an output. As the product grew, the challenge shifted toward organizing more analyses, supporting teamwork, and keeping the experience coherent across modules. AI introduced another consideration: its contribution needed to be clear enough for professionals to review and use with confidence.
I worked closely with domain experts to understand how they expected information to be structured and presented. Usability testing, analytics, support feedback, and client input relayed by the product team informed later decisions. I also worked with founders and engineers to weigh user needs against backend capabilities and release priorities.

Understanding the people behind the work

The platform needed to support several responsibilities:
Preparing analyses: providing data, working through the methodology, and reviewing outputs.
Reviewing work: understanding the analysis and checking its conclusions.
Managing collaboration: organizing workspaces, participants, and access.
These responsibilities shaped the product’s structure. Specialists needed depth and control, while shared work required clear organization and context.

Learning the domain: I worked closely with financial experts to understand both the methodologies and how professionals expected to see information presented. Competitive research, usability testing, analytics, support feedback, and client feedback relayed by the product team informed subsequent iterations.

Three findings directly changed the design:
The number of analyses was growing, and users needed better support for teamwork. I reorganized the flat dashboard around organizations, workspaces, and module-specific views.
Our initial bar charts displayed comparison data accurately, but experts found them less effective for interpreting financial ranges.
I introduced a candlestick-style visualization to show the lower bound, scenario value, and upper bound in a format more familiar to the intended audience.
Users found the path through Workspace → Module → Create unnecessarily slow.
I added a contextual “+” shortcut beside modules in the sidebar, allowing users to start the relevant analysis directly.

Keeping experts in control of AI-assisted work

AI-assisted report authoring and scenario modeling added new ways to work with complex information. In the interfaces I designed, generated content sat alongside editable text, source references, assumptions, and results that users could review. The intent was to make AI useful within an expert’s existing workflow while keeping the underlying work visible and open to judgment.

Design System & Foundation:
I created the design system from scratch, covering navigation, dashboards, filters, forms, settings, and module-specific patterns. It included component states, responsive behavior, accessibility checks, and implementation documentation.
. Reusable components . Design tokens · Variables . Responsive layouts . Interaction patterns . Documentation . Developer handoff guidelines
I worked with engineers through implementation and design QA. As the team expanded, I brought in another designer, assigned work, reviewed solutions, and mentored juniors while remaining hands-on with core UX/UI.

Outcomes

Launched MVP and platform 2.0, taking SeemaS from an idea to a working enterprise product.
Unified design system supporting modules and shared workflows.
Improved organization and collaboration through workspaces and focused sharing capabilities.
Enterprise demos that led to new contracts with Fortune 500, including Paramount.
$4M raised by SeemaS during the product’s journey.
My contribution was leading the design of the product behind these milestones, working alongside the broader team.

Beyond the Product Our work extended beyond the platform itself.
We also designed: • Company visual identity • Typography & color system • Product website • Motion graphics • Spline 3D animations • Product videos • Investor presentation assets • Marketing visuals
Analysis Output - Interactive valuation results with tabbed navigation, financial summaries, and clear data visualization.
Analysis Output - Interactive valuation results with tabbed navigation, financial summaries, and clear data visualization.
Forecast Visualization - Interactive charts, scenario comparisons, legends, and tooltips for exploring valuation assumptions and results.
Forecast Visualization - Interactive charts, scenario comparisons, legends, and tooltips for exploring valuation assumptions and results.
Scenario Modeling - Adjust forecast assumptions using historical data, AI guidance, and real-time valuation previews.
Scenario Modeling - Adjust forecast assumptions using historical data, AI guidance, and real-time valuation previews.
AI Report Authoring - AI-powered report editor with templates, source references, collaborative editing, and content generation.
AI Report Authoring - AI-powered report editor with templates, source references, collaborative editing, and content generation.
Forms Library - Global compliance library with regulatory forms, search, filters, filing status, and country-specific requirements.
Forms Library - Global compliance library with regulatory forms, search, filters, filing status, and country-specific requirements.
Regulatory Forms - Collaborative form completion with approvals, comments, revision tracking, and client coordination.
Regulatory Forms - Collaborative form completion with approvals, comments, revision tracking, and client coordination.
User Management - Manage organization members, roles, workspace permissions, and access across multiple teams and workspaces.
User Management - Manage organization members, roles, workspace permissions, and access across multiple teams and workspaces.
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Posted Aug 19, 2026

Led the UX/UI design of an AI-powered enterprise platform that streamlines valuation, transfer pricing, and financial analysis.

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Timeline

Aug 20, 2024 - Jul 30, 2026

Clients

SeemaS, Inc.