GenMitra Competency Center
AI Solutions
LLMs, predictive models, custom agents and localized RAG architectures.
Operational Challenges
- Data privacy leaks when passing institutional logs to public models.
- Inefficient retrieval of metrics from unstructured files.
- Lacking localized semantic search across internal servers.
Engineering Approach
We implement secure, isolated vector databases (e.g. Supabase Vector) and RAG (Retrieval-Augmented Generation) pipelines, keeping your data confidential.
Standard Engagement Model:Dedicated systems integration retainer or fixed-scope sprint
Development Process
1Data ingestion & cleaning
2Semantic indexing & vector enclaves configuration
3RAG orchestration pipeline engineering
4Accuracy audits & prompt adjustments
Key Deliverables
RAG orchestration repository
Secure database vector configurations
Data parsing script triggers
Prompt handbook & user guides
Technology Expertise
PythonFastAPISupabase VectorLlamaIndexLangChain