Product type
- SaaS
- B2B
- AI product
- Web App
AutoGDIS
About
AutoGDIS is a web application for interpreters in the oil & gas industry, comparable to existing industry solutions (“Saphire”) and Russian solutions (“RN-Vega”, “RN-Geosim”), but with extended features. Its key advantage is the integration of machine learning and neural databases for geological modeling.
Work period
+ ongoing support and development
My role
End-to-End Product Design (Solo) — the only designer on the project, full design cycle from research to delivery and post-release support
Problem & Goals
Geologists and engineers work with complex well-testing data and analytical models. Existing industry tools often have outdated interfaces, complex navigation, and inefficient workflows. As a result, analysis becomes slow and confusing, not only increasing the learning curve for new specialists but also reducing the overall efficiency of experienced users
My contribution
- Full-cycle design: from research to implementation
- Developed a design system and guidelines from scratch
- Built user flows and prototypes, aligned with the product owner and stakeholders
- Created final UI layouts
- Handoff to developers, quality control, and product testing
- Continuous support and feature improvements after release
Business goals
- Build a competitive product capable of competing with established industry solutions
- Deliver a modern and professional interface suitable for corporate clients
- Improve product usability to support adoption by large oil companies
- Create a scalable interface architecture for future modules
User goals
- Reduce complexity of analytical workflows
- Simplify navigation and interaction with complex datasets
- Improve clarity of data visualization and parameters
- Speed up common interpretation scenarios
Process
- Research & analysis — competitors (e.g., Sapphire, Rosneft solutions), business goals, user needs, and technical limits
- UX design — building user flows, sketches, wireframes, and interaction scenarios
- Prototyping — interactive prototypes, feedback from product owner and stakeholders
- UI design — final visual style, design system, components, and screens
- Handoff — specifications, collaboration with developers
- QA & testing — checking quality of implementation
- Product support — improvements and new features after release
User Flow
The software supports complex workflows used by geologists, interpretation engineers, analysts, and operators working with well-testing data.
A typical scenario includes:
A typical scenario includes:
- loading well data
- running analysis and interpretation
- verifying well parameters
- generating analytical reports
Previously, the workflow consisted of 12 steps across multiple screens. Through UX redesign and restructuring of system logic, the core workflow was reduced to 4 main steps, while advanced configuration options remained available for experienced users.
The redesign also introduced:
The system supports several key workflows:
The redesign also introduced:
- structured filtering and parameter management
- automatic switching between system modes depending on user selections
- clearer visualization of analytical data
- simplified interaction with complex parameter sets
The system supports several key workflows:
- Well Test Registry — data management and tracking
- Well Stock — well database and information overview
- Interpretation — analytical modeling and interpretation tools
- Admin Panel — configuration and system management
- Notification System — alerts and operational monitoring
Key Design Decisions
- Simplified navigation and reduced the number of steps in typical interpretation workflows
- Introduced step-by-step configuration for complex modules (e.g., PVT phase setup and model curve configuration)
- Reorganized system settings to make complex analytical tools easier to configure
- Prioritized key parameters and visualizations within the main workspace
- Designed modular UI patterns to support multiple analytical scenarios
Design Trade-offs
- Showing many analytical parameters increases accuracy but can overload the interface
- Simplifying workflows reduces flexibility for advanced users
- Large data visualizations improve analysis but require careful layout to keep screens readable
- Balancing data density with interface readability
- Complex configuration options had to remain accessible without overwhelming the main workflow
Results
- Before the product was introduced, the analysis workflow relied on manual operations and several disconnected tools, including physical interaction with sensors, manual data processing, and work in legacy software
- By consolidating these steps into a single digital system with optimized user workflows, the time required to complete key analytical processes decreased from approximately 2 working days to about 3 hours, significantly improving operational efficiency
- The core interpretation workflow was simplified from 12 steps to 4, reducing interaction complexity by approximately 67%
- The improved interface structure reduced onboarding time for new specialists from about 1 week to 2 days, making the system significantly easier to learn
- Clearer parameter configuration, structured workflows, and improved data visualization reduced common user errors during analysis
- The product was successfully launched and adopted by several large oil and gas companies shortly after release
- A scalable design system was created, enabling consistent development of future product modules.
This project gave me deep experience in leading a complex B2B product from scratch.
I worked closely with product owners, analysts, and developers to translate complex domain processes into clear user workflows and scalable interface patterns.
The project strengthened my expertise in workflow optimization, design systems & collaboration within cross-functional product teams, and I’m proud that the design contributed to the product’s successful market launch.
I worked closely with product owners, analysts, and developers to translate complex domain processes into clear user workflows and scalable interface patterns.
The project strengthened my expertise in workflow optimization, design systems & collaboration within cross-functional product teams, and I’m proud that the design contributed to the product’s successful market launch.
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