Outcome
A maintainable LangGraph/LangChain workflow that is easier to debug, extend, test, and connect to a product, API, automation, or agent interface.
Make complex agent behavior explicit
Research agents
Add routing, retries, and review loops
Proposal or document generation workflows
Improve reliability over single-prompt flows
Decision workflows with review checkpoints
Prepare the workflow for future tools, agents, or product integration
Data enrichment flows
What you receive
- Workflow architecture diagram or map
- LangGraph/LangChain implementation
- Typed state design
- Node and routing logic
- Example runs or test cases
- Handoff notes and extension plan
Methodology
- Model the process as states and transitions
- Define graph nodes, edges, and routing rules
- Add tool calls, retries, and validation
- Add human review where needed
- Run example cases and document behavior
- Prepare integration notes for API/product usage
Scope
Includes graph/workflow design, typed state structure, nodes, edges, routing logic, tool-use points, retry paths, human-in-the-loop checkpoints, structured outputs, and basic tests or examples. It focuses on workflow architecture and execution logic, not a full product build unless combined with full-stack implementation.
Details
What to expect from this engagement
What is included?
I implement the internal logic of agentic systems using LangGraph and LangChain. This service is for workflows that are too complex for a single prompt and need explicit state, nodes, routing, tool use, validation, and review points.
Who is it for?
Teams moving from simple prompts to structured agentic systems that need reliability, debugging, and extension paths.
What do you need to provide?
Requires a target process, expected states, example decisions, required tools/APIs, and expected outputs. Does not include a complete frontend, full deployment pipeline, or large data/RAG system unless scoped separately.