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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
> TURNING RAW DATA INTO BUSINESS VALUE <
Data science solves specific business problems: predicting customer behavior, optimizing supply chains, detecting anomalies, and automating decisions that previously required manual work. For Los Angeles companies competing in media, advertising, and healthcare, the difference between guessing and knowing directly impacts revenue. We build data science systems that move beyond dashboards into real decision-making infrastructure. Our team handles statistical analysis, machine learning model development, and deployment, so your data scientists focus on business problems, not pipeline maintenance.
- Predictive modeling for customer churn and demand forecasting
- Recommendation engines for content personalization
- Anomaly detection for fraud and operational issues
- Natural language processing for unstructured data
- Computer vision for media and manufacturing applications
> LOCAL EXPERTISE MATTERS <
What separates data science work in Los Angeles from generic consulting? Understanding the industries, the regulations, and the talent market. LA’s concentration of media, entertainment, and advertising companies creates unique data challenges around content personalization, audience measurement, and ad attribution that firms elsewhere rarely encounter.
- Direct experience with California privacy law compliance
- Familiarity with media and entertainment data workflows
- Access to cross-disciplinary domain expertise
- Understanding of LA startup velocity and iteration cycles
- 02Data Analytics Solutions
> Data Analytics Solutions <
Analytics transforms business questions into clear answers. Los Angeles companies dealing with ad campaign performance, content engagement metrics, or supply chain visibility need systems that deliver data insights without requiring a PhD to interpret. We design analytics solutions that connect directly to business intelligence workflows. Real-time dashboards, automated reporting, and self-service tools let your team analyze data and make strategic decisions faster than competitors.
- Custom dashboards for KPI tracking and performance monitoring
- Marketing attribution and ROI measurement
- Operational efficiency reporting across departments
- Audience analytics for media and entertainment
- Sales pipeline and revenue forecasting
- 03Enterprise Data Management
> Enterprise Data Management <
Data management forms the foundation for everything else. Without clean, organized, accessible data, machine learning models fail and analytics produce garbage. LA enterprises working with streaming media, healthcare records, or geospatial logistics data need infrastructure that scales without breaking. We architect data warehouses, data lakes, and pipelines using tools like Snowflake, BigQuery, and Spark. Our approach handles big data volume while maintaining quality controls that satisfy both technical requirements and California’s strict regulatory environment.
- Data warehouse and lakehouse architecture
- ETL/ELT pipeline development and maintenance
- Data quality monitoring and validation
- Feature stores for ML model training
- Cloud and hybrid infrastructure design
- 04Data Strategy and Governance
> Data Strategy and Governance <
Strategy without governance creates risk. Governance without strategy creates bureaucracy. Los Angeles businesses operating under CCPA and CPRA face real penalties for mishandling consumer data, fines, lawsuits, and reputation damage that can sink companies. We build data governance frameworks that satisfy California’s privacy regulations while keeping your teams productive. Our approach covers data catalogs, lineage tracking, access controls, and the documentation required for audits under the new ADMT transparency rules.
- CCPA/CPRA compliance frameworks and risk assessments
- Data catalog and metadata management systems
- Access control and privacy policy implementation
- Audit preparation and documentation
- Automated decision-making transparency requirements
> TURNING RAW DATA INTO BUSINESS VALUE <
Data science solves specific business problems: predicting customer behavior, optimizing supply chains, detecting anomalies, and automating decisions that previously required manual work. For Los Angeles companies competing in media, advertising, and healthcare, the difference between guessing and knowing directly impacts revenue. We build data science systems that move beyond dashboards into real decision-making infrastructure. Our team handles statistical analysis, machine learning model development, and deployment, so your data scientists focus on business problems, not pipeline maintenance.
- Predictive modeling for customer churn and demand forecasting
- Recommendation engines for content personalization
- Anomaly detection for fraud and operational issues
- Natural language processing for unstructured data
- Computer vision for media and manufacturing applications
> LOCAL EXPERTISE MATTERS <
What separates data science work in Los Angeles from generic consulting? Understanding the industries, the regulations, and the talent market. LA’s concentration of media, entertainment, and advertising companies creates unique data challenges around content personalization, audience measurement, and ad attribution that firms elsewhere rarely encounter.
- Direct experience with California privacy law compliance
- Familiarity with media and entertainment data workflows
- Access to cross-disciplinary domain expertise
- Understanding of LA startup velocity and iteration cycles
PRODUCTS BUILT ACROSS INDUSTRIES
Finance
Built for systems where latency, correctness, and auditability matter. We ship data analytics software that handles real money, real risk, and real regulators.
Healthcare
Designed for workflows where data privacy and reliability aren’t optional. We build machine learning software that fits clinical reality, not just specs.
Education
Platforms built to scale users, content, and outcomes at the same time. From internal tools to student-facing analytics systems that actually get used.
Construction
Software that mirrors how projects run in the real world. Data management for scheduling, reporting, and coordination without breaking existing workflows.
Technology
Complex systems, integrations, and internal platforms built to evolve. We step in when off-the-shelf data analytics tools stop being enough.
Startups
From first version to real traction without painting yourself into a corner. Data science built for speed now and strategic decisions later.
Compliance
Systems designed around controls, traceability, and change management. Data governance built so audits don’t become fire drills.
Energy
Infrastructure software built for long timelines and high stakes. Reliable data systems for assets that can’t afford guesswork.
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.
Ready to Build Data Systems That Actually Work?
SoftDoes brings senior data scientists, proven technical expertise, and a track record building systems that survive contact with reality. Whether you’re optimizing advertising spend, building healthcare analytics, or scaling logistics operations, we’re ready to start. Contact SoftDoes today to discuss your data science project.

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 Los Angeles, CA – 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 the data scientists building your system. No account managers translating requirements incorrectly. No information loss between decisions and implementation. Our team has extensive experience with production ML systems, not just academic exercises. Technical expertise gets applied directly to your problems without management overhead.
- 02Predictable Delivery
Work is scoped, sequenced, and delivered in clear increments. No surprises mid-project. No rushed rewrites before deadlines. No stalled releases waiting for unclear decisions. We document what we’re building, when it ships, and what it costs. Clients know project status without asking.
- 03Built to Last Past Launch
The system is designed for long-term use, maintenance, and change. Launch is the starting point, not the finish line. We architect for evolution, new data sources, model updates, scaling requirements. Ongoing support means your data science investment compounds over time. Software development practices ensure future teams can understand and modify our code.
- 04No Babysitting Required
Clients weren’t managing the team or pushing work forward. Execution didn’t depend on reminders. We operate autonomously within agreed scope and surface decisions when they matter. Our team handles technical problems without escalating everything. You focus on your business; we focus on delivering quality data solutions.
Frequently Asked Questions
How is data science project communication handled?
A PM leads updates, scope, and timelines for all data science services. Engineers join planning sessions for technical tradeoffs and architecture decisions so nothing gets lost in translation. Weekly status reports cover progress, blockers, and upcoming milestones. You get direct access to the team building your system when technical questions arise.
What types of data science projects are a good fit for SoftDoes?
Long-term products, business-critical analytics systems, and machine learning implementations that need ongoing maintenance and evolution. We work best with organizations that view data as strategic infrastructure rather than a one-time project. If you need a proven track record and technical expertise, we’re a good fit.
Do you build data science MVPs or only large systems?
We build MVPs when they’re designed to grow into production data systems. We don’t build throwaway demos or proofs-of-concept that require complete rebuilds. Every MVP includes architecture decisions that support future scaling. Our software development approach treats early versions as foundations, not prototypes.
How do you handle data science project scope and changes?
Work starts from a defined scope with clear deliverables and timelines. Changes are discussed, estimated, and prioritized explicitly, not absorbed silently until they cause problems. We document scope modifications and adjust schedules transparently. This protects both our team and your budget from scope creep.
What happens after data science system launch?
We continue supporting, maintaining, and evolving the system. Launch is the beginning of operational life, not the end of our involvement. Ongoing support includes model monitoring, performance optimization, and feature development. Many clients maintain long-term partnerships as their data analytics needs evolve.
Will we own the data science code and IP?
Yes. You own 100% of the code, repositories, models, and intellectual property from day one. No licensing restrictions. No dependencies on our systems. Everything transfers to you fully documented and deployable. Your data management infrastructure belongs to you completely.
What makes SoftDoes different from typical data science agencies?
Senior data scientists working directly on your project. Direct communication without account management layers. Predictable delivery with documented milestones. Long-term ownership mindset rather than volume-based digital agency work. We build systems designed to transform businesses, not check boxes on a requirements document.
How do you price data science projects?
Engagements are structured around clear scope and measurable outcomes. We focus on long-term value delivery, not lowest upfront cost. Pricing reflects the expertise level of our team and the complexity of production data systems. Detailed estimates come after discovery so both sides understand what success looks like.
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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.
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