LangChain Development Services - LangChain Development
Built for Production
We build RAG pipelines, AI agents, and LLM-powered applications using LangChain connecting your data to the world's most powerful AI models. Real answers. Real context. Production-ready.
End-to-End LangChain Development Services
From RAG pipelines to AI agents, vector databases & custom chains — we engineer robust LLM systems.
RAG Pipelines
Build Retrieval-Augmented Generation systems that let your LLM answer questions using your own documents, databases, and knowledge bases — with accurate, cited answers.
AI Agent Chains
Create multi-step AI agents that reason, plan, use tools, and execute tasks autonomously — from research agents to code-writing bots to complex decision engines.
Vector Database Integration
Connect Pinecone, Supabase Vector, Weaviate, or pgvector to store and retrieve embeddings at scale — the foundation of every accurate RAG and semantic search system.
Document Intelligence
Parse, chunk, embed, and query PDFs, Word docs, spreadsheets, and web pages — so your LLM can reason over large document collections accurately.
LLM Orchestration
Route queries across multiple LLMs — GPT-4o, Claude, Gemini, or open-source models — based on cost, latency, or capability, with automatic fallbacks.
Custom Chain Development
Build custom LangChain chains and tools tailored to your exact use case — memory management, structured output parsing, tool use, and multi-agent coordination.
Production-Ready. Zero Hallucinations.
LangChain enables accurate, multi-step LLM applications connected to your real business data — backed by our engineering expertise.
Disconnected prompts, hallucinations, no data context & manual parsing errors.
Production RAG pipelines, 90%+ retrieval accuracy & multi-agent coordination.
LangChain specialists since 2022
GPT-4o, Claude & open-source LLM experts
250+ AI systems delivered globally
Dedicated project manager per engagement
Clean, documented, production-ready code
NDA & full IP ownership guaranteed
Long-term support & maintenance plans
Free 30-day post-launch support included
Industries We Serve
Custom LangChain solutions tailored to the operational demands of high-growth global sectors.
E-commerce
Catalog & Support RAG
Healthcare
HIPAA Document Search
B2B / SaaS
In-App AI Agents
Legal & Finance
Contract Analysis Pipelines
Logistics
Supply Chain Query Agents
Agencies
Custom AI Client Solutions
LangChain Systems We Engineer
From RAG document Q&A to support bots, research agents, code generators, and multi-source data intelligence.
Document Q&A System
Upload your internal docs, manuals, or legal files → LangChain chunks and embeds them → users ask questions in plain English → system returns accurate, cited answers from your documents.
AI Customer Support Bot
LangChain retrieves relevant knowledge-base articles → GPT-4o generates a contextual reply → escalates to human if confidence is low → logs conversation to CRM.
Research & Summarisation Agent
Agent receives a topic → searches the web or internal docs → reads and summarises findings → produces a structured report — in minutes, not hours.
Code Generation Assistant
Internal dev tool where engineers describe a feature → LangChain agent generates code → runs tests → iterates on failures → produces a PR-ready diff.
Contract & Legal Document Analysis
Upload contracts → LangChain extracts key clauses, dates, obligations, and risks → produces a plain-English summary → flags anomalies for legal review.
Multi-source Data Intelligence
Connect your CRM, database, and docs to a LangChain agent → business users ask questions in plain English → agent queries the right source and synthesises a complete answer.
LangChain Ecosystem Tech Stack
Frameworks, vector databases, LLMs, APIs, and runtime environments that power our LangChain solutions.
LangChain
OpenAI GPT-4o
Supabase Vector
Pinecone
Python
FastAPI
PostgreSQL
Next.js
DockerFrom Design to Live Deployment
Use-case Design
Define retrieval strategy, agent architecture, memory & data sources.
Data Pipeline Build
Build ingestion pipelines to load, chunk, clean & embed documents.
Chain & Agent Build
Build retrievers, chains, agents & test accuracy against real queries.
Deploy & Monitor
Deploy via FastAPI or serverless, set up cost/latency monitoring & handover docs.
Advanced LangChain Features
Our LangChain architectures feature multi-agent orchestration, conversation memory, hybrid search, and cost optimisation.
Multi-agent Orchestration
Coordinate multiple specialised AI agents — a researcher, a writer, a reviewer — that collaborate autonomously to complete complex tasks end-to-end.
Conversation Memory
LangChain memory modules store conversation history so your AI remembers context across sessions — enabling natural, ongoing conversations not just one-shot queries.
Hybrid Search (BM25 + Vector)
Combine keyword and semantic search for retrieval — so users get accurate results whether they search with exact terms or describe what they're looking for.
LLM Cost Optimisation
Route simple queries to cheaper models and complex ones to GPT-4o — with caching, batching, and streaming — reducing LLM costs by up to 70%.
FAQ
Common LangChain Development Services Questions
Have more questions? Book a free 30-minute discovery call no commitment required.
Book a free callWhat's the difference between LangChain and just calling the OpenAI API directly?
Direct API calls work for simple prompts. LangChain adds the infrastructure for complex AI apps — retrieval from your own data, agent reasoning, multi-step chains, memory across conversations, and tool use. It's the difference between a one-shot query and a full AI application.
How accurate are RAG systems with our documents?
Accuracy depends heavily on document quality, chunking strategy, and retrieval tuning. We achieve 85–95% accuracy on well-structured documents by optimising every step of the pipeline — and we test against your real documents before delivery.
Can LangChain work with our existing database or CRM?
Yes. LangChain supports PostgreSQL, MySQL, Supabase, and any SQL database as a retrieval source — plus REST APIs for CRMs. Your AI can query your live data directly alongside your embedded documents.
Which LLM should we use — GPT-4o, Claude, or open-source?
It depends on your accuracy needs, budget, and data privacy requirements. We evaluate the right model for your use case — and often build multi-LLM setups that route queries intelligently between models to balance cost and quality.
Let's Build Your LangChain Systems
Tell us about your data and AI requirements and we'll provide a detailed LangChain proposal within 24 hours.