
Let's build together.
Talk with a senior engineer about your product idea, architecture, and what it would take to build it.
6
years on the market
73%
new clients come from referrals
510+
finished projects
80+
software engineers
Services we offer
- 01Data Science Services
> INSIGHT-DRIVEN OPERATIONS <
Our data science services turn raw data into systems that identify patterns, anticipate outcomes, and support faster decision making. Typical use cases include churn prediction for Florida SaaS companies, dynamic pricing for real estate firms responding to population growth, and risk scoring for regional banks managing loan portfolios. We build systems that integrate with your existing workflows and deliver value within weeks, not years.
- Churn prediction for SaaS
- Dynamic pricing models
- Risk scoring for lenders
- Demand forecasting
- Customer segmentation
> PRODUCTION-READY MODELS <
We design every model for monitoring, retraining, and iteration. This includes alerting when model performance degrades, data pipelines that handle real time data feeds, and documentation that supports compliance audits.
- Model monitoring and alerts
- Automated retraining pipelines
- Performance drift detection
- Audit trail generation
- 02Data Analytics Solutions
> CLEAR REPORTS, FASTER DECISIONS <
Many Florida companies face scattered data across multiple systems, causing slow reporting and unclear insights. Our solutions integrate CRM, ERP, and operational tools into unified, automatically updating dashboards. Clients use these analytics to respond swiftly to events like hurricanes, tourism peaks, and population shifts. For example, real-time data helps manage inventory and staffing or anticipate demand spikes during spring break in Orlando, enabling faster, informed decisions.
- Real-time dashboard updates
- Self-service report builders
- Trend analysis and forecasting
- Cross-system data integration
- Mobile-accessible insights
- 03Enterprise Data Management
> ONE SOURCE OF TRUTH <
Enterprise data management builds the foundation for analytics and AI by designing data warehouses, lakes, and integration pipelines that unify CRM, ERP, EMR, and other core systems. This eliminates manual work of reconciling data from multiple sources. Fragmented data wastes time and increases costs, especially with compliance pressures from Florida’s data privacy law. Florida companies face unique challenges: healthcare networks require secure patient data flow, banks need audit-ready customer data, education institutions consolidate data from many campuses, and construction firms need accessible project data across sites. We create systems tailored to these needs.
- Data warehouse and lake architecture
- Data quality and lineage tracking
- Master data for customers and assets
- ETL and integration pipelines
- Access control and audit logging
- 04Data Strategy and Governance
> RULES THAT MAKE DATA USEFUL <
Data strategy and governance define how your company collects, owns, and uses data. Without clear rules, analytics become inconsistent, responsibilities unclear, and compliance risks increase. Good governance builds trust internally and with customers expecting responsible data handling. SoftDoes helps leaders decide which data to collect, structure ownership, and set clear decision rights. This is vital for Florida companies managing cross-border data flows, remote teams, and multi-location operations. We create governance frameworks that scale with growth and adapt to changing laws.
- Data catalog and ownership assignments
- Retention and deletion policies
- Access rights and approval workflows
- Quality standards and monitoring
- Compliance documentation
> INSIGHT-DRIVEN OPERATIONS <
Our data science services turn raw data into systems that identify patterns, anticipate outcomes, and support faster decision making. Typical use cases include churn prediction for Florida SaaS companies, dynamic pricing for real estate firms responding to population growth, and risk scoring for regional banks managing loan portfolios. We build systems that integrate with your existing workflows and deliver value within weeks, not years.
- Churn prediction for SaaS
- Dynamic pricing models
- Risk scoring for lenders
- Demand forecasting
- Customer segmentation
> PRODUCTION-READY MODELS <
We design every model for monitoring, retraining, and iteration. This includes alerting when model performance degrades, data pipelines that handle real time data feeds, and documentation that supports compliance audits.
- Model monitoring and alerts
- Automated retraining pipelines
- Performance drift detection
- Audit trail generation
PRODUCTS BUILT ACROSS INDUSTRIES
Finance
We support banks, fintechs, and payment companies with AI for risk management and fraud detection, handling real transactions and regulatory demands with precision and reliability.
Healthcare
We build HIPAA-compliant analytics solutions to help Florida health systems manage seasonal patient surges efficiently, optimize resource allocation, and improve patient outcomes through data-driven insights.
Education
Our tools empower Florida schools and universities to track student engagement, monitor academic performance, and implement interventions that improve educational outcomes and retention rates.
Construction
We create integrated software solutions that connect office planning with fieldwork for large Florida developments, streamlining project management, resource scheduling, and compliance reporting.
Technology
We build scalable, custom data pipelines and AI-driven platforms for Florida tech firms that require tailored solutions beyond off-the-shelf tools, enabling innovation and faster time to market.
Startups
We design scalable data and AI foundations for fast-growing Florida startups, providing the agility and robustness needed to support rapid growth and evolving business models.
Compliance
Our systems automate audit preparation and ensure compliance with Florida privacy laws and regulations, including data protection and processing personal data securely to meet regulatory requirements.
Energy
We provide advanced analytics for utilities to manage assets reliably amid Florida’s risks, enhance operational efficiency, and support sustainable energy initiatives through predictive maintenance and real-time monitoring.
Transparency at each stage
Discovery & Alignment
Clear goals and a detailed roadmap to eliminate surprises.
Technical Strategy
Expert tool selection with logical architectural backing.
Iterative Development
Real-time access to code, staging, and regular progress demos.
Careful Testing
Transparent QA, security, and performance reporting before launch.
Deployment & Support
Full documentation and ongoing monitoring for total control.
Numbers Don’t Lie
Recent projects showcasing how we design, engineer, and deliver production-ready software solutions.

WHAT IT WAS LIKE TO BUILD TOGETHER
Direct feedback from founders and product owners – including many of our partners right here in Florida – after shipping, scaling, and maintaining real production systems.
WHAT CHANGED IN PRACTICE
Clients didn’t stay because of promises. They stayed because delivery became predictable, ownership was clear, and the product kept moving forward after launch.
- 01Direct Access to Senior Engineers
You work directly with senior software and data engineers building your system. No account managers relaying messages. No information loss between decisions and implementation. When questions arise about data models, architecture tradeoffs, or integration approaches, you get answers from the people doing the work. Custom software development and data science consulting work better with direct communication.
- 02Predictable Delivery
Work is scoped, sequenced, and delivered in clear increments. You see progress in demos and working software, not just status reports. No surprises, no rushed rewrites, no stalled releases. Agile delivery with fixed milestones means you know what to expect each week. Iterative development lets us adjust based on feedback without derailing timelines.
- 03Built to Last Past Launch
Systems are designed for long-term use, maintenance, and change. Launch is the starting point, not the finish line. We implement versioned data pipelines, MLOps practices for model monitoring, automated testing, and observability for production systems. Production data pipelines need to run reliably for years, handle schema changes, and support new features without breaking existing functionality.
- 04No Babysitting Required
SoftDoes teams drive work forward, communicate proactively, and do not require constant client reminders. Execution does not depend on you pushing every task. You stay informed without becoming a project manager for your own vendor.
Technologies We Use
Front end
Databases & cloud
Other / Frameworks
Back end
DevOps & tools
Frequently Asked Questions
How is communication handled in data science projects?
A project manager leads updates, scope discussions, and timeline tracking. Engineers join for planning sessions, technical decisions, and tradeoff discussions so details do not get lost in translation. We use regular standups, weekly summaries, and shared tools like Slack, Jira, Microsoft or email based on your preference. Data science project communication stays transparent, and you always know where things stand.
What types of data science projects are a good fit for SoftDoes?
Long-term products, business-critical systems, and software that needs maintenance and evolution after launch. Examples include core data platforms, AI features embedded in products, and analytics for regulated workflows. We focus on enterprise data science and mission-critical software for Florida and U.S. clients. Short-term projects with no path to production are not a good fit.
Do you build MVPs or only large data science systems?
We build MVPs when they are designed to grow into production systems. We do not build throwaway demos or prototypes with no future. Even MVPs use clean architecture and data models that support scale. Scalable MVP development means your first version does not become technical debt when traction arrives. Production-ready prototypes save rewrite costs later.
How do you handle scope and changes in data science engagements?
Work starts from a defined scope. Changes are discussed, estimated, and prioritized explicitly, not absorbed silently or ignored. Project scope management includes change control with visible tradeoffs tied to timelines and budgets. This approach keeps expectations aligned and prevents scope creep from derailing delivery.
What happens after launch in a data science project?
We continue supporting, maintaining, and evolving the system. Launch is the beginning, not the end. Post-launch support includes monitoring, maintenance, and iterative improvement of models and data flows. Options include support retainers, SLAs, and expansion phases for new features or datasets. Ongoing data operations ensure your investment keeps delivering value.
Will we own the code and intellectual property (IP)?
Yes. You own 100% of the code, repositories, and intellectual property from day one. This is non-negotiable. SoftDoes works under agreements that protect custom software IP ownership and your data rights. AI model ownership stays with you, including trained models, datasets, and documentation.
What makes SoftDoes different from a typical data science agency?
Senior engineers, direct communication, predictable delivery, and systems built for long-term use. We are an engineering-focused data science partner, not volume-based outsourcing. We do not rotate junior staff through your project or treat delivery as someone else’s problem. High-skill software agency work means ownership and accountability from the people building your system.
How do you price data science projects?
Engagements are structured around clear scope and outcomes. We offer fixed-scope phases, long-term retainers, or hybrid approaches depending on project needs. Software development engagement model depends on your situation. Data science project pricing reflects long-term value, not lowest upfront cost. We discuss budget openly and design scope to match.
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How I Built SoftDoes. From Solo Developer to Custom Software Development Company
In 2019, I was a freelance software engineer working from a small apartment in Ukraine. Today, I lead SoftDoes, a 70+ person AI focused <a href='https://softdoes.com/'>custom software development company</a> headquartered in Kansas City, Missouri. This is the story of how I built it, project by project, client by client, through a war and across continents.










































