CirrusLabs Tech Stack
AI and cloud modernization for data-intensive enterprises
CirrusLabs builds AI, cloud, and automation solutions for mid-market enterprises. The stack reveals a company deep in ML infrastructure—TensorFlow, PyTorch, RAG, LangChain, LlamaIndex, vector DBs (Pinecone, Weaviate, FAISS), and inference serving (TorchServe, Triton)—paired with data lakehouse tooling (Databricks, Kafka, Delta Lake). Project focus on RAG pipelines, agentic AI, multi-agent workflows, and FinOps chatbots shows the company is moving beyond advisory into production AI delivery. Pain-point clustering around database scaling, inference latency, and data modernization aligns with their hiring velocity: 11 roles posted in the last 30 days, weighted toward senior and mid-level engineers (8 engineering, 2 security), indicating active delivery of complex infrastructure.
Tech Stack 142 technologies
What CirrusLabs Is Building
◆Challenges
- Scaling database workloads
- Performance tuning
- Migration risk
- Scaling ai inference workloads
- Latency, cost, performance optimization
- Access control monitoring
- User access reviews
- Enterprise modernization initiative
- Integration of calculation-heavy applications
- Modernization of data-intensive ecosystems
▲Active Projects
- Rag pipelines
- Agentic ai systems
- Multi-agent workflows
- Scaling options
- Performance tuning
- Migration scripts
- Integration of calculation-heavy applications into databricks platform
- Design and maintain scalable lakehouse, delta lake, and unity catalog solutions
- Modernization of data-intensive application ecosystems
- Chatbot workflows for finops
