Practical ML, LLMs, and automation
AI Solutions
ML/LLM systems that drive KPIs: RAG, agents, NLP, CV, and tabular ML—with proper evaluation and MLOps.
What you get
- LLM apps: RAG & function calling
- Tabular ML: churn, LTV, forecasting
- Vision: OCR, defect detection
- MLOps: pipelines & monitoring
Tech stack
Python / FastAPIPyTorch / TensorFlowscikit-learnLangChain / LlamaIndexVector DBsAirflow / PrefectW&BDocker / K8s
Our process
- Use-case & DataKPI & data audit
- BaselineQuick wins & heuristics
- ModelingAblations & offline eval
- ProdServing & human-in-the-loop
- ImproveA/B tests & drift
Why it works
- Outcome-oriented
- Governance & eval
- Cost-aware inference
FAQs
Warehouse integration?
Snowflake, BigQuery, Redshift, PG.
MLOps setup?
CI for data/models, registry, monitoring.
Start an AI pilot
4-week ROI-positive prototype