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AI Automation
Document processing, workflow orchestration, decision support, and cross-system automation built around your business logic.
Explore AI AutomationProduction AI & ML Engineering
Custom AI and ML systems, engineered for production.
We are an AI and machine learning development company with 14 years building custom LLM systems, ML models, and AI automation for startups and growth-stage businesses. No off-the-shelf wrappers. Production-grade systems built to last.
Certified partners & compliance
Explore our partnerships Partnered with the platforms you build on
Software Sushi is a Select Tier member of the Claude Partner Network.
A long-term engineering partner
Built to last, not just launch
Choosing an AI development partner is a long-term decision. The system you build today will need to be maintained, updated, and scaled. The team building it needs to understand your business, not only your tech stack.
Software Sushi has been doing this since 2015. We specialize in large language models, GPU-optimized inference, and custom automation, with experience across insurance, logistics, manufacturing, IoT, and healthcare. We are AWS certified, Databricks certified, and HIPAA compliant.
2015Building since
8 yrLongest client partnership
3Countries
What we build
Hard AI and ML problems, engineered as complete systems
Custom LLM applications, predictive models, and automation integrated into real business infrastructure, not demos or wrappers.
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LLM Development
Fine-tuned models, RAG pipelines, and complete LLM applications grounded in your data and integrated into real workflows.
Explore LLM Development
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AI & ML Consulting
A clear feasibility assessment, architecture recommendation, and build plan before you commit meaningful budget.
Explore AI & ML Consulting
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AI Integration
Connect AI to the CRM, product data, APIs, and workflows your team already uses without replacing what already works.
Explore AI Integration
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Custom AI Development
Built around your data and constraints, from system architecture and models through deployment on infrastructure you control.
Explore Custom AI Development
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Custom Machine Learning Development
Predictive models and causal inference systems that hold up on real-world data, from forecasting to anomaly detection.
Explore Custom Machine Learning DevelopmentFrom prediction to product
Custom AI development, from model to working product.
A model becomes useful when it connects to the software people work with. Software Sushi builds the application interfaces, backend services, data pipelines and cloud infrastructure around custom AI and machine learning systems.
Plan the build
Assess feasibility, data readiness and architecture before committing to development.
AI & ML consultingBuild a prediction system
Connect predictive models with the data pipelines and applications they need to operate.
Machine learning developmentIntegrate AI into existing software
Work with the platforms, databases and workflows your team already uses.
AI integrationThe product around the modelFrontend applications ↗Backend and data systems ↗Mobile products ↗Cloud infrastructure ↗
Selected work, current scope
See how the engineering works in practice.
Production applications and engineering projects, with the implementation and current scope behind each one.
Production project
Healthcare risk prediction and professional review
Software Sushi delivered prediction models, services, and a clinician-led assessment application for a healthcare project that reached production.
Explore the case study
Engineering project · v1 in development
Self-hosted PII/PHI redaction pipelines
Configurable text protection with explicit detector, policy, evidence, and delivery boundaries.
Explore the project
Engineering prototype · development implementation
Fraud-detection prototype with Kafka and Python
Implemented ingestion, inference, and routing components, with reproducible evaluation as the next milestone.
Explore the projectReported results, with the context.
Figures from individual published case studies, not guaranteed outcomes.
Cloud infrastructure
62% cloud spend reduction
Infrastructure matched to actual usage, with monitoring to prevent drift.
Read the case
Field operations
15h saved per week
Automated scheduling and more inspections per day.
Read the case
Demand forecasting
27% less production waste
Production planning tailored to each flavor’s seasonality and demand.
Read the caseRisk estimates in the healthcare case support professional review, not autonomous diagnosis.
Explore all 6 case studies & projectsTeam credentials
View all certifications Credentials held by the engineers who build your system
AWS Certified Machine Learning – Specialty
AWS Certified Solutions Architect – Professional
AWS Certified Machine Learning Engineer – Associate
Claude Certified Developer – Foundations
AWS Certified Solutions Architect – Associate
Generative AI Leader Certification
Issuer verification links are included where available.
From the blog
View all articlesAI engineering guides for your next technical decision.
Why Most AI Pilots Never Reach Production (And What Separates the Ones That Do)
Understand why a convincing demo can still leave integration and production work unresolved.
Read the guide
Can We Send PHI to an LLM?
Map the PHI path and review the boundaries before choosing how to use an LLM.
Read the guide
How to Evaluate RAG Retrieval Quality Before You Tune the Model
Evaluate retrieval against a labeled set before assuming the model needs tuning.
Read the guideFrequently asked questions
Find the right starting point.
Practical answers about scope, existing systems and the work around a model.
Should we start with AI consulting or a custom build?
If the decision is still about feasibility, data readiness or architecture, start with AI and ML consulting. If the scope and constraints are clear, explore custom AI development.
How does a prediction model become part of a working application?
A working prediction system needs the application and backend workflows around the model. Our anonymous healthcare case shows one production project connecting prediction services, structured assessments and professional review.
Can you connect AI to our existing software?
Yes. Our AI integration work connects models with existing platforms, databases and workflows. The starting point is assessing what should stay and what needs to change.
What kinds of companies do you work with?
We primarily work with startups and growth-stage companies, from founders validating technical IP to scaling teams putting production systems in place. We also support focused enterprise AI and ML engagements.
Where can we review your credentials and compliance practices?
Team certifications, platform partnerships, and HIPAA compliance are separate. Review our engineers’ credentials, our platform partnerships and our published compliance practices to understand each in its own context.
What happens after the first release?
Every engagement is scoped with production in mind from day one. We stay involved after launch and measure success by how deeply the system becomes part of the way your business operates.
Bring us the problem
Discuss your AI or machine learning project.
Tell us what you want to build, the data you have and the systems it needs to work with. We can help identify a practical next step.