The low-code platform that turns optimization models into business-ready applications — in days, not months.
From Model to Application
Without the IT Overhead
DB Gene Studio is a web-based application that takes your optimization and planning models from prototype to production. Build decision-making applications with interactive dashboards, scenario analysis, and operational business rules — all without writing frontend code.
An intuitive, low-code environment for building planning and scheduling applications
Describe your data model in natural language. Configure dashboards with powerful widgets.
No frontend development required.
- GenAI–assisted data modeling, scenario analysis and visualizations — describe your entities and relationships in plain language
- Configurable dashboards with powerful out-of-the-box widgets
- Planning Board and Scheduling Board with interactive Gantt chart
- Embedded Jupyter notebooks for Python-based visualizations
- Tables, pivot tables, charts, maps, and KPI widgets
- What-if scenario analysis across multiple datasets
- Business rules engine (Drools) for data validation and quick reports
Key Capabilities
Design Your Data Model with the Help of GenAI
Starting a new planning application used to mean hours of manual schema design — defining entities, attributes, relationships, and constraints before you could write a single line of optimization logic.
DB Gene Studio changes that. Describe your business objects in natural language — « a warehouse with a capacity, a set of products with demand forecasts, a fleet of vehicles with availability windows » — and GenAI generates the structured data model for you. Review it, refine it, and move straight to building your algorithms.
Configure Dynamic Dashboards with Powerful Widgets
Build custom dashboards by dragging and dropping business widgets — no frontend development required. Out-of-the-box components include Planning Boards, Scheduling Boards, interactive Gantt charts, tables, pivot tables, charts, maps, and KPI indicators.
Model, Validate, and Visualize — All in Jupyter Notebooks
DB Gene Studio integrates natively with Jupyter notebooks, giving your team a single environment to build optimization models, validate data quality, and create rich visualizations — all without leaving the notebook.
- Use your preferred solver — CPLEX, Gurobi, or others
- Work in the programming language you know (AMPL, Python)
- Write data checkers directly in notebooks to validate inputs before they reach your model
- Embed notebook visualizations into dashboards, leveraging the full Python ecosystem
- Embedded visualization widget that lets users launch optimization jobs directly from any dashboard with a single click—no coding required.
Run What-If Analysis Across Scenarios
Compare multiple planning scenarios side by side. Business users and analysts can test different assumptions, adjust parameters, and evaluate trade-offs — all within a user-friendly interface that requires no coding.
Speak with an Expert
How It Works
DB Gene Studio lets you go from raw data to a stakeholder-ready application in three steps. GenAI accelerates the most tedious part — data modeling — so you and your team can focus on decision-making logic and business impact.
Design your data model
Start from what you have.
Upload your data files (CSV, XLS, JSON) and let GenAI infer the structure, or describe your business entities in natural language — « a distribution center with storage zones, a product catalog with seasonal demand patterns, and a delivery fleet with shift constraints and vehicle capacities ».
Either way, GenAI generates the structured data model — entities, attributes, relationships, and constraints — ready for you to review and refine.
Design the decision-making & planning logic
Build your optimization algorithms in Python or Java. Use your preferred solver (CPLEX, Gurobi, or others) and iterate directly in JupyterHub.
Configure dynamic dashboards
Set up interactive visualizations — Gantt charts, KPIs, scenario comparisons — using powerful out-of-the-box widgets. No frontend code required.
Business Value
Built for Every Role on Your Team
Focus on what you do best — building and refining models — not on infrastructure overhead.
-
- AI-assisted setup: Let GenAI handle the data model scaffolding so you can jump straight to optimization & ML logic
- Rapid prototyping: Go from algorithm to working application on the cloud or on-premise in minutes
- Solver flexibility: Bring your own solver (CPLEX, Gurobi, or others) and work in Python, AMPL, etc.
- Notebook-native: Embed Jupyter notebook visualizations directly into stakeholder-facing dashboards
Turn model outputs into actionable insights without waiting for developers.
-
- Natural-language modeling: Describe business concepts in plain language to help shape the data model — no SQL or JDL schema expertise needed
- Self-service dashboards: Configure widgets and KPIs tailored to your needs
- Data validation: Write business rules and data checkers to ensure quality inputs
- What-if analysis: Test scenarios and present trade-offs to decision-makers
Accelerate the path from idea to value demonstration.
-
- Faster PoCs: Build stakeholder-ready applications in days, not months
- Stakeholder buy-in: Let business users interact with models directly, building trust and alignment
- MVP-first approach: Build a minimum viable application to validate your approach and demonstrate value before committing to full-scale development
- AI-accelerated start: Reduce the data modeling phase from days to minutes — your team demonstrates value sooner
