LangChain Development
That Ships to Production
LangChain is powerful — but building production-grade LangChain applications requires engineering discipline that goes well beyond the tutorials. We build, deploy, and maintain LangChain and LangGraph systems — with proper observability, evaluation, cost controls, and error handling.
Our Service Capabilities
End-to-end capability — from strategy and build to integration, monitoring, and ongoing support.
RAG Pipeline with LangChain
Production RAG pipelines built with LangChain — document loaders, text splitters, embeddings, vector store integration, retrieval chains, and citation enforcement.
LangChain Agent Development
Tool-using agents built with LangChain's agent framework — ReAct, OpenAI Function Calling, and custom agent loops with structured output and error recovery.
LangGraph Workflow Orchestration
Stateful, cyclical AI workflows built with LangGraph — multi-agent systems, human-in-the-loop flows, conditional branching, and long-running task orchestration.
LangSmith Evaluation & Observability
LangSmith integration for tracing, debugging, and evaluating LangChain applications — golden-set testing, regression detection, and production monitoring.
Cost Optimisation & Caching
Semantic caching, prompt compression, model routing (small/large LLM), and token budget management — reducing LangChain application inference costs by 40–70%.
LangChain Production Hardening
Error handling, retry logic, fallback chains, async optimisation, streaming support, and load testing — making LangChain applications production-reliable.
Our Engagement Process
A disciplined, outcome-focused approach from first call to go-live.
- 1
Architecture & Chain Design
Map the LangChain components needed — loaders, splitters, retrievers, chains, agents — and design the optimal architecture for your use case.
- 2
Component Development & Testing
Build and unit-test each LangChain component in isolation before composing into the full pipeline.
- 3
Integration & Chain Composition
Assemble the full pipeline, implement error handling, caching, and streaming — with integration tests covering edge cases.
- 4
LangSmith Evaluation Setup
Configure LangSmith tracing and build golden evaluation datasets — enabling regression testing on every code change.
- 5
Production Deployment & Monitoring
Deploy with LangServe or FastAPI, configure cost monitoring, and set up performance dashboards.
Tools & Frameworks We Master
A production-tested, vendor-agnostic stack built for enterprise security and compliance requirements.
LangChain Ecosystem
LLM Integrations
Vector Stores
Infrastructure
Use Cases by Industry
Production AI systems we have built across regulated, data-heavy industries.
Internal Docs Chatbot with LangGraph
LangGraph stateful agent over 80K internal documents — multi-hop retrieval, conversation memory, human escalation. 60% ticket reduction.
Contract Analysis Chain
LangChain pipeline: load → extract → classify → flag risks → draft amendments. Processes 200+ contracts/day, cuts review time 75%.
Clinical Coding Assistant
LangChain RAG over ICD-10 codes and clinical guidelines — medical coders get cited coding suggestions, 91% first-pass accuracy.
Multi-tenant AI Copilot
LangGraph copilot with per-tenant memory and knowledge bases — 15,000 daily users, sub-3-second P95 response time, 62% cost reduction via caching.
Literature Review Agent
LangChain ReAct agent searching PubMed, extracting findings, and generating structured summaries — 10x faster literature reviews.
CI/CD AI Analysis Chain
LangChain pipeline consuming CI/CD logs, identifying failure patterns, and generating root cause analysis reports — integrated with GitHub Actions.
What Teams Say After Shipping with Us
Real results from teams who needed LangChain systems to work in production, not just in a demo.
AndolaSoft has been a valued partner providing excellent customer service. Issues with clients or troubleshooting are handled in a timely manner and positive resolution is always the outcome.
I got a recommendation on AndolaSoft. They are more than half the cost, they have a can-do attitude, and they are responsive, timely, and easy to work with.
Andolasoft team is very hardworking, dedicated and professional that follows through with their goals. The technical leadership is also a superior value to any other developers.
Frequently Asked Questions
LangChain is a framework for building LLM-powered applications — including RAG pipelines, AI agents, document processing workflows, and multi-step LLM chains. It provides building blocks for connecting LLMs to tools, memory, and data sources.
Ready to Build Your LangChain Application?
Tell us your use case — RAG, agent, or workflow. We will scope a production-grade LangChain system with proper evaluation and observability.