Pipeline design
We map inputs → retrieval → generation → post-processing with clear interfaces.
What We Deliver
- LangChain LCEL pipelines and tools
- LangGraph stateful agent workflows
- Document loaders and chunking strategies
- Memory, sessions, and conversation stores
- Evaluation harnesses for prompt quality
- Deployment with FastAPI, Node, or serverless
Our Process
Implement with LCEL / LangGraph
Composable chains that are easier to test and swap models without rewrites.
Evaluate
Golden datasets, regression checks, and latency/cost budgets before release.
Ship & monitor
Tracing, retries, and versioned prompts in production.
Technologies
- LangChain
- LangGraph
- OpenAI
- Python
- FastAPI
- Pinecone
- pgvector
Outcomes You Can Expect
- Maintainable LLM pipelines
- Easier model and prompt swaps
- Test coverage for AI behavior
- Production tracing and debugging
Why Choose Intellixy
- Experienced engineering team with startup and enterprise delivery
- Agile sprints with transparent progress and staging access
- Clear scope, milestones, and pricing before development starts
- Post-launch support, monitoring, and feature iterations
Industries We Serve
HealthcareE-commerceEducationLogisticsStartups
Frequently Asked Questions
Do we need LangChain for every AI feature?
No. Simple OpenAI calls are fine for basic chat. LangChain shines when you need retrieval, tools, multi-step agents, or reusable pipeline components.
LangChain vs custom code?
We use LangChain where it saves time and keep thin custom wrappers when you need full control. The goal is reliable product delivery, not framework dogma.
Do you support LangGraph?
Yes. LangGraph is our preferred approach for stateful agents and branching workflows that need checkpoints and human approval steps.
Related Services
Ready to start your project?
Tell us about your LangChain development goals. We respond within 24 hours on business days with a tailored plan.