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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
> ADVANCED ANALYTICS IMPLEMENTATION <
We approach advanced analytics as a complete system. Our data scientists build end to end solutions covering data collection, processing, modeling, deployment, and ongoing maintenance. Every engagement starts with understanding your business objectives, not our preferred tools.
- Custom predictive analytics models
- Integration with existing internal teams
- Production ready deployment pipelines
- Documentation and knowledge transfer
- Ongoing optimization and support
> CUSTOM MODEL DEVELOPMENT <
How do you build models that actually solve your specific problem? We start with your data and your questions, then design algorithms that fit.
- Domain specific feature engineering
- Model selection based on your constraints
- Explainability for regulated environments
- Performance optimization for production
- 02Data Analytics Solutions
> ACTIONABLE INSIGHTS FROM COMPLEX DATA <
Analytics turns questions into answers. What happened? Why? Our analytics solutions process large volumes of data from various industries and transform raw information into dashboards, reports, and visualizations that support data driven decision making. We build systems using modern business intelligence tools that your team can actually use without constant technical support. Boston’s competitive market demands speed. Companies need to understand customer behavior, track operational metrics, and respond to changes quickly. SoftDoes builds descriptive analytics and diagnostic analytics systems that connect to your existing data sources, providing valuable insights without months of integration work.
- Real time dashboard development
- Custom reporting systems
- Data visualization for executive teams
- Diagnostic analytics to identify root causes
- Integration with existing business processes
- Self service analytics capabilities
- 03Enterprise Data Management
> ORGANIZE DATA AT ANY VOLUME <
Enterprise data management addresses a common pain point. Many organizations have data scattered across systems, formats, and departments. Our data engineering teams build data architecture that unifies multiple data sources into coherent, accessible structures. We design data warehouses, data lakes, and integration layers that handle big data without breaking. Data governance matters more in Boston than most cities. SoftDoes builds governance frameworks into every system, ensuring data security and compliance are built in, not bolted on.
- Master data management implementation
- Data integration across legacy systems
- Data lineage and metadata tracking
- Role based access controls
- Automated data quality checks
- Cloud and hybrid deployment options
- 04Data Strategy & Governance
> ALIGN DATA WITH BUSINESS STRATEGY <
Strategy determines whether data investments pay off. Without clear governance, companies waste resources collecting data they cannot use. We work with leadership to define what data is needed, how it should flow through the organization, and who owns each piece. This creates a data driven organization rather than a data overwhelmed one. Boston’s regulatory environment requires proactive approaches to data governance. SoftDoes helps companies build frameworks that satisfy auditors while enabling business outcomes, balancing compliance with competitive advantage.
- Data governance policy development
- Compliance framework implementation
- Data quality standards and monitoring
- Ownership and stewardship models
- Privacy by design architecture
- Regulatory audit preparation
> ADVANCED ANALYTICS IMPLEMENTATION <
We approach advanced analytics as a complete system. Our data scientists build end to end solutions covering data collection, processing, modeling, deployment, and ongoing maintenance. Every engagement starts with understanding your business objectives, not our preferred tools.
- Custom predictive analytics models
- Integration with existing internal teams
- Production ready deployment pipelines
- Documentation and knowledge transfer
- Ongoing optimization and support
> CUSTOM MODEL DEVELOPMENT <
How do you build models that actually solve your specific problem? We start with your data and your questions, then design algorithms that fit.
- Domain specific feature engineering
- Model selection based on your constraints
- Explainability for regulated environments
- Performance optimization for production
PRODUCTS BUILT ACROSS INDUSTRIES
Finance
Financial institutions use predictive analytics to assess risk, detect fraud, and optimize portfolios. Our data science services create models that analyze transaction data and customer behavior to support faster, accurate decisions.
Healthcare
Patient data offers insights to improve outcomes. We build analytics solutions that predict readmissions, optimize resources, and ensure compliance with privacy regulations.
Education
Data driven approaches help understand student performance and improve results. Our solutions gather data systematically and turn it into actionable insights for administrators and faculty.
Construction
Better data analysis improves project timelines, resource use, and cost control. We develop predictive models for demand forecasting, supply chain, and operational efficiency.
Technology
Product analytics and customer metrics guide decisions. Our teams help technology companies analyze user behavior for improved product development and customer loyalty.
Startups
Speed is critical. We help early stage companies set up data pipelines and analytics quickly, enabling competitive advantage without large upfront costs.
Compliance
Regulations require audit trails, access controls, and data governance. Our solutions integrate compliance into data architecture, reducing risk and easing audits.
Energy
Predictive maintenance and optimization enhance energy operations. We build analytics that process sensor and operational data to forecast outcomes and reduce downtime.
Transparency at each stage
Discovery & Alignment
Defined goals and a precise roadmap ensure your vision is realized without unexpected pivots or hidden costs.
Technical Strategy
Senior engineers select the optimal tech stack with clear architectural reasoning for long-term scalability.
Iterative Development
Gain real-time access to code and staging environments with regular demos to track every milestone as it happens.
Careful Testing
Receive transparent QA, security, and performance audits to ensure a flawless and stable launch every time.
Deployment & Support
Stay in total control with full documentation and proactive monitoring to keep your systems running at peak performance.
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 our partners right here in Boston, MA– 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
When you work with SoftDoes, you work directly with experienced data scientists. No project managers filtering communication. No junior developers learning on your project. Our teams consist of engineers who have built and deployed machine learning systems in production environments. This direct collaboration means faster problem solving and higher quality results. Questions get answered by people who understand both the technical details and your business context.
- 02Predictable Delivery
Data science projects often spiral. Scope creeps. Timelines extend. We structure engagements with clear milestones and regular checkpoints to prevent this. Our project management approach breaks complex work into measurable phases. You see progress weekly. Risks surface early when they can be addressed. This transparency builds trust and keeps projects moving toward business outcomes rather than endless exploration.
- 03Built to Last Past Launch
A model that works once is not a solution. We build data systems meant to run reliably for years. Code is documented. Architecture is maintainable. Monitoring catches problems before they affect your business. Our advanced algorithms come with retraining pipelines because we know production data changes over time. When your team takes over, they inherit something they can actually maintain.
- 04No Babysitting Required
Our teams operate independently. We ask questions upfront, establish communication rhythms, then execute without requiring constant oversight. You focus on running your business while we build. Regular updates keep you informed. We flag issues proactively rather than waiting to be asked. This proactive approach respects your time while ensuring nothing falls through the cracks.
Frequently Asked Questions
How is communication handled during data science projects?
We establish communication protocols at project kickoff. Most clients prefer weekly syncs with async updates between meetings. We use tools your team already knows. Slack, Teams, email, or whatever works. Technical documentation stays current in shared repositories. Our data scientists respond to questions directly, no routing through account managers. This keeps collaboration efficient and ensures nothing gets lost in translation.
What types of projects are a good fit for SoftDoes?
The global market for data analytics is rapidly growing, with significant investments being made in technologies that enable organizations to analyze and utilize data effectively, particularly in urban centers like Boston. We work across the full spectrum. Early stage companies building their first predictive analytics capabilities. Established organizations modernizing legacy data infrastructure. Quick proof of concept projects to validate ideas. Multi year enterprise implementations. Our data science services adapt to what you actually need. Project size matters less than clarity of objectives and commitment to working collaboratively.
How do you handle data privacy and security during model training?
Data security is foundational, not an afterthought. We work within your security requirements, whether that means on premise deployment, specific cloud providers, or hybrid approaches. We implement encryption, access controls, and audit logging. When the Massachusetts Data Privacy Act takes effect, our systems will already comply. Your customer data stays protected throughout every phase.
How do you handle scope and changes in data science projects?
Changes happen. Data reveals unexpected patterns. Business priorities shift. We use milestone based structures that accommodate reasonable evolution without derailing timelines. Clear change control processes document what shifts and why. We discuss implications before implementing changes. This flexibility paired with discipline keeps projects on track while remaining responsive to what you learn along the way.
What happens after data science model deployment?
Launch is a milestone, not an endpoint. Our predictive models include monitoring for drift and degradation. We provide documentation and knowledge transfer so your internal teams understand what we built. Support options range from ad hoc assistance to ongoing managed services. Retraining pipelines ensure models stay accurate as your data evolves. We build systems meant to optimize performance continuously, not just work on day one.
Will we own the code and intellectual property for our data models?
Yes. Full ownership transfers to you. All code, models, documentation, and related intellectual property belong to your company. We retain no rights to use your work elsewhere. This includes custom algorithms, trained neural networks, and any data architecture we create. You receive complete access to repositories and can engage any team to maintain or extend our work.
What makes SoftDoes different from a typical data science agency?
Organizations that implement predictive analytics can enhance customer engagement by making informed predictions about customer behavior, which can lead to improved marketing strategies and customer retention efforts. Technical depth. Most agencies staff projects with junior resources supervised loosely by senior people. Our teams consist entirely of experienced engineers who have built production systems. We function as a technical partner, not a vendor executing specifications. This means we contribute to business strategy discussions, push back when approaches seem wrong, and take ownership of outcomes rather than just deliverables.
How do you price data science projects in Boston?
We price based on value and complexity, not hours. Boston market rates for senior data scientists run high, and our pricing reflects the experience level we bring. Most engagements start with discovery work to define scope precisely. Fixed price options work for well defined projects. Time and materials suits exploratory work. We discuss tradeoffs transparently so you understand exactly what you are paying for and why.
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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 custom software development company 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.
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