Build AI applications faster
Ready components for prompts, tools, memory and retrieval.
AI & Data Science
LangChain
Orchestration components for language-model applications.
LangChain
LangChain can connect language models with data sources, retrieval, tools, and application logic. We use only the components a solution needs and keep evaluation, observability, security, and provider portability visible.
Useful for focused language-model applications that combine prompts with retrieval, tools, memory, or multi-step orchestration.
Planning your implementation
A technology choice is a delivery decision.
We plan the work needed to build, operate and improve the application, not just the first set of features.
- 01
Review the requirements
We test whether orchestration is needed, then assess model choice, retrieval quality, evaluation, sensitive data, latency, cost, and failure behaviour.
- 02
Validate the important assumptions
Use a focused prototype or a representative workflow where a technical uncertainty could affect scope. Agree the acceptance checks before building the full solution.
- 03
Plan the handover
Prompt and chain versions, tool contracts, evaluation cases, model configuration, observability, and operating limits.
Why LangChain
Why we use LangChain.
Where LangChain adds the most value in the projects we deliver.
Works with your knowledge
Connects language models to your documents and data.
Model flexibility
Works with several AI model providers.
Agent support
Tools for building controlled AI agents.
Questions
Common questions.
Quick answers to what people often ask us about LangChain.
What is LangChain used for?
It helps connect large language models to your data, tools and workflows to build practical AI applications.
Is our data safe?
We design what the AI can access, use providers that do not train on your business data, and keep people reviewing important outputs.
AI & Data Science
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Let’s talk
Planning a project with LangChain?
Tell us what you want to achieve and the right team will get back to you with practical next steps.