RAG pipeline development
Build retrieval-augmented generation systems that answer from proprietary documents and databases rather than relying only on model memory.
AI consultancy building custom RAG pipelines, LLM integrations, and model APIs.
Hanabi Technologies is an AI consultancy based in Bangalore that focuses on RAG pipelines, LLM integration, and model API engineering. Its services are built on a MERN stack foundation and are aimed at organizations that need custom AI systems connected to their own data and workflows.
The site presents Hanabi as both a consultancy and a product builder. Its flagship product, Hana AI, is positioned as a Google Chat team assistant with multi-tenant deployment, broad app integrations, and enterprise-oriented security features, while the consulting practice covers custom AI architecture, delivery, and maintenance.
Build retrieval-augmented generation systems that answer from proprietary documents and databases rather than relying only on model memory.
Connect and tune large language models for domain-specific use cases, including model selection, prompt optimization, and multi-model orchestration.
Design REST and GraphQL APIs on a MERN stack foundation to serve AI models with authentication, rate limiting, caching, and observability.
Ingest content from PDFs, docs, databases, APIs, and knowledge bases, with support for vector search and relevance scoring.
Support custom deployments with agile sprints, client reviews, testing, deployment, and post-launch maintenance.
Teams with scattered internal knowledge can centralize documents and app data into a retrieval layer that supports contextual answers and chat-based assistance.
Organizations can build or improve AI features that need to pull from documents, databases, or tools while keeping responses grounded in their own source data.
Product teams can expose AI capabilities through reliable REST or GraphQL APIs, with security, rate limiting, and monitoring built into the delivery stack.
Companies with existing workplace tools can connect systems such as Google Workspace, Jira, Confluence, Notion, Slack, and Zapier through custom integrations.
Regulated or security-sensitive teams can use the consultancy’s deployment process and security measures to design controlled AI systems with maintenance and support.
Hanabi Technologies offers a free consultation and custom proposal process. The onboarding page describes a discovery call first, followed by architecture, planning, and a scoped proposal rather than a self-serve checkout flow.
The onboarding page says most projects range from 6 to 12 weeks, depending on complexity. Development is delivered in agile sprints with regular client reviews.
The services page shows work across RAG pipeline development, LLM integration and fine-tuning, and model API engineering on the MERN stack. The case studies also mention Google Workspace, Jira, Confluence, Notion, Zapier, OpenAI, Qdrant, Pinecone, Weaviate, and cloud deployment on GCP Kubernetes or AWS Kubernetes where applicable.
The company positions itself for custom AI consultancy rather than a packaged software product. The process, pricing, and architecture are tailored to each project, so the fit depends on the specific data sources, deployment needs, and security requirements.
The service emphasizes RAG pipelines, LLM integrations, model APIs, and MERN stack implementation. The onboarding FAQ also notes security measures such as encryption, JWT authentication, and CASA Tier-2 compliance.
Traffic data is for reference only.
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