Why use LangChain instead of calling LLM APIs directly?

LangChain provides abstractions that dramatically speed up development — tool interfaces, memory management, output parsing, model switching, and chain composition. For simple chatbots, raw API calls work fine. But for agents with multiple tools, complex state, and production requirements, LangChain saves weeks of development time and gives you a battle-tested foundation used by thousands of production applications.

When should I use LangGraph for multi-agent orchestration?

LangGraph is ideal when your agent needs complex, stateful workflows — conditional branching, parallel tool execution, human-in-the-loop approvals, or multi-agent collaboration. If your agent follows a simple linear flow, basic LangChain chains suffice. We recommend LangGraph when you need persistent checkpoints, cycle handling, or supervisor-worker agent patterns.

How does LangSmith help with production monitoring?

LangSmith provides end-to-end tracing for every agent run — you see every LLM call, tool execution, and intermediate step with full inputs and outputs. It also supports automated evaluation with custom scoring functions, regression tracking, and dataset-based testing. In production, it helps you debug failures, identify slow chains, and continuously improve your agent based on real usage data.

Can I switch LLM providers without rewriting the agent?

Yes, that is one of LangChain's core strengths. We build agents using LangChain's model abstraction layer, so switching from OpenAI to Anthropic, Google, or an open-source model requires changing a single configuration. This is crucial for cost optimization (route simple tasks to cheaper models) and resilience (fallback to alternate providers during outages).

How stable is LangChain for production use?

LangChain has matured significantly and is now used in production by thousands of companies. We use specific version pinning, comprehensive testing, and LangSmith monitoring to ensure stability. The key is proper architecture — we use LangChain's stable interfaces and avoid experimental features in production code. LangGraph specifically was designed for production reliability with checkpointing and error recovery.

What custom tools can you build for LangChain agents?

We build any tool your agent needs — CRM connectors (Salesforce, HubSpot), database query tools, web scrapers, API wrappers, file processors, email senders, calendar integrations, payment processors, and custom ML model inference tools. Each tool is wrapped in LangChain's structured tool interface with proper error handling, retry logic, and type validation.

How do you handle LangChain version upgrades and breaking changes?

We follow LangChain's migration guides and maintain version-pinned dependencies. Our agents use stable, well-documented interfaces rather than experimental APIs. For existing deployments, we offer upgrade packages that migrate your agent to newer versions with full regression testing via LangSmith evaluation datasets to ensure nothing breaks.

LangChain Agent

LangChain Agent Development Services

Build sophisticated AI agents using LangChain, LangGraph, and LangSmith. We develop production-grade agents with custom tool chains, stateful workflows, multi-model support, and full observability — not toy demos that break in production.

Schedule a Call

INR 2000

Per Hour

50+

AI Agents Built

4.9/5

Client Rating

<2 Weeks

MVP Delivery

LangChain Agent Capabilities

Leverage the LangChain ecosystem for flexible, production-ready AI agent architectures

LangChain Tools & Chains

Build custom tool integrations and chain complex operations together. From API connectors and database queries to web scrapers and calculators — we create tools that your agent calls autonomously to complete tasks.

LangGraph Stateful Workflows

Design complex, stateful agent workflows using LangGraph's graph-based orchestration. Implement conditional branching, parallel execution, human-in-the-loop checkpoints, and persistent state across multi-step agent interactions.

Memory Management

Implement sophisticated memory strategies — buffer memory for recent context, summary memory for long conversations, vector memory for semantic recall, and entity memory for tracking key information across sessions.

LangSmith Tracing & Evaluation

Full observability with LangSmith for production monitoring. Trace every LLM call, tool execution, and chain step. Run automated evaluations, track regression, and debug issues with detailed run histories.

Multi-Model Support

Swap LLMs without rewriting your agent. LangChain's model abstraction lets you switch between OpenAI, Anthropic, Google, Mistral, and open-source models seamlessly — optimizing for cost, speed, or capability per task.

Custom Tool Development

Build domain-specific tools that extend your agent's capabilities. From Salesforce integrations and Jira automation to custom ML model inference and proprietary API connectors — all wrapped in LangChain's tool interface.

Our LangChain Agent Development Process

A proven 5-step process from requirements to production LangChain deployment

Discovery & Architecture

We map your workflows, define the agent graph topology using LangGraph, select the optimal LLM provider for each task, and plan tool integrations, memory strategy, and observability setup with LangSmith.

Prompt Engineering & Prototyping

Craft agent system prompts, build custom tools, define LangGraph state schemas, and deliver a working prototype with LangSmith tracing enabled — so you can see exactly how your agent thinks and acts.

Integration & Development

Connect tools to your APIs and databases, implement memory persistence, build LangGraph workflows with error handling and human-in-the-loop checkpoints, and optimize chain execution for production throughput.

Testing & Evaluation

Run automated evaluations via LangSmith with custom scoring functions. Test tool call accuracy, response quality, memory recall, and edge cases across hundreds of scenarios. Track regressions with evaluation datasets.

Deployment & Monitoring

Production deployment with LangSmith dashboards, cost tracking per chain, tool call analytics, latency monitoring, and alerting. Continuous improvement through feedback loops and automated evaluation pipelines.

LangChain Agent Development Pricing

Transparent pricing for LangChain and LangGraph agent projects

Starter Agent

INR 50,000starting

Single-purpose LangChain agent with basic tool chain

LangChain agent with ReAct pattern
Up to 5 custom tools
Basic memory (buffer or summary)
Single LLM provider
LangSmith tracing setup
Source code handover
14-day post-launch support

Get Started

What Our Clients Say

"Edesy built a LangGraph-powered research agent that automates our competitive intelligence workflow. It searches the web, analyzes documents, and generates structured reports. What took our team 8 hours per company now takes 15 minutes with 90% accuracy."

VP of Strategy

Strategy at Management Consulting Firm

"The LangChain agent they built handles our entire customer onboarding flow — it verifies documents, runs KYC checks, updates our database, and sends welcome emails. LangSmith tracing helped us debug and optimize every step. Onboarding time dropped from 3 days to 4 hours."

Head of Product

Product at FinTech Platform

"We needed an agent that works with multiple LLMs — GPT-4o for reasoning, Claude for document analysis, and a fine-tuned Llama model for classification. LangChain's abstractions made this seamless, and swapping models takes one config change. Saved us months of custom integration work."

Engineering Lead

Engineering at AI-First Startup

LangChain Agent

LangChain Agent Development Services

Schedule a Call

INR 2000

Per Hour

50+

AI Agents Built

4.9/5

Client Rating

<2 Weeks

MVP Delivery

Trusted by businesses worldwide

ShopifyAmazonStripeSlackNotionVercel

LangChain Agent Capabilities

Leverage the LangChain ecosystem for flexible, production-ready AI agent architectures

LangChain Tools & Chains

LangGraph Stateful Workflows

Memory Management

LangSmith Tracing & Evaluation

Multi-Model Support

Custom Tool Development

40+

Chains in Production

10K+

LangSmith Evaluations Run

200+

Custom Tool Integrations

60%

Avg Latency Optimization

Our LangChain Agent Development Process

A proven 5-step process from requirements to production LangChain deployment

Discovery & Architecture

Prompt Engineering & Prototyping

Integration & Development

Testing & Evaluation

Deployment & Monitoring

LangChain Agent Development Pricing

Transparent pricing for LangChain and LangGraph agent projects

Starter Agent

INR 50,000starting

Single-purpose LangChain agent with basic tool chain

LangChain agent with ReAct pattern
Up to 5 custom tools
Basic memory (buffer or summary)
Single LLM provider
LangSmith tracing setup
Source code handover
14-day post-launch support

Get Started

What Our Clients Say

VP of Strategy

Strategy at Management Consulting Firm

Head of Product

Product at FinTech Platform

Engineering Lead

Engineering at AI-First Startup

Frequently Asked Questions

Explore More

Resources to help you evaluate and implement

OpenAI GPT Agent RAG Agent Fine-Tuned LLM Agent Multi-Agent System

Ready to Build Your LangChain Agent?

Get a free consultation and detailed project estimate. Our LangChain experts will help you design the right agent architecture with LangGraph workflows and LangSmith observability.

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