Modernize your Enterprise SaaS!
Whether greenfield development or legacy modernization, Simplicitize helps companies move from AI experiments to production systems — LLMs and generative AI, Retrieval-Augmented Generation, and Deep Learning — served by battle-tested JVM (Java, Kotlin, Scala) microservices, such as Spring Boot, and built with the engineering discipline that enterprise software demands.
What we do
Expert Level Software Engineering
Highly scalable distributed systems on AWS — resilient, observable, cloud-native systems engineered for scale and reliability. Polyglot by design — Java, Kotlin, Scala, Python, and Rust — using the right language for each problem.
AI Native Development
Claude Code and Cursor in expert hands — transform existing codebases into AI-native systems, vibe code with professional guardrails and review discipline, and fix the AI slop unsupervised agents leave behind.
GenAI & Agentic AI
Production-grade applications on large language models — from chat assistants, copilots, and document intelligence to autonomous agents that plan, call tools, and execute multi-step workflows.
Retrieval-Augmented Generation (RAG)
Connect your proprietary knowledge to AI safely with retrieval-augmented generation and vector search. Semantic search finds what your users mean, not just what they type — surfacing answers by meaning instead of keyword matching.
Deep Learning
Custom neural networks with PyTorch — model training, fine-tuning, and inference optimization, from computer vision to transformer architectures.
Rust
Rust alongside the JVM and Python — memory-safe, high-performance services as part of a polyglot distributed-systems toolkit.
ML Ops CI/CD Pipeline
GitHub Actions CI/CD pipelines and MLOps workflows — evaluation, monitoring, and cost control so your AI systems stay reliable long after launch.
Software Architecture
System design that scales with your business — domain-driven boundaries, event-driven architectures, and pragmatic technology choices that keep large codebases evolvable for years.
Containerization
Ship the same artifact everywhere — lean Docker images, multi-stage builds, and Docker Compose environments that make “works on my machine” mean every machine.