Systems & data
Agentic Workflow Automation
Build a multi-step AI workflow around evidence, review and human decisions. I design and implement retrieval, drafting, evaluation and targeted revision for tasks such as report preparation, with explicit boundaries for any connected tools.
Discuss this serviceIs this the right service?
Who it is for. Operations and engineering owners with a repeatable knowledge workflow, approved source material and people who can review the result.
The problem. Finding evidence, assembling drafts and revising incomplete work require repeated manual handoffs.
The result. A reviewable workflow with defined stages, failure handling and clear responsibility for approval.
What it covers
Map the workflow and decisions
Agree the input, output and owner of each stage. Identify where a person must review evidence or approve a consequential action.
- Document the workflow, acceptance criteria and review points.
Retrieve, draft and review
Implement a sequence that retrieves evidence, prepares a draft and checks it against agreed completeness and structure requirements.
- Build retrieval, drafting and evaluation stages with traceable inputs.
Revise and handle failures
Route sections needing changes through targeted revision. Define what happens when sources are missing, checks fail or a tool is unavailable.
- Exercise revision limits, escalation and recovery cases.
Validate and hand over
Review representative runs with your domain owners before accepting the workflow. Your team receives the code and operating instructions.
- Deliver acceptance examples, configuration and a runbook.
Approach
- 01
Define the task
Agree one workflow, its sources, reviewers and expected output.
- 02
Build the stages
Implement retrieval, drafting, checks and targeted revision, with tool permissions scoped explicitly.
- 03
Review real examples
Exercise failure cases, agree remaining limitations and hand over the workflow with its runbook.
What you get
Workflow code, retrieval and review stages, acceptance examples, execution records and a runbook.
- Receive the workflow code and configuration in the agreed repository.
- Review representative outputs, execution records and acceptance results.
- Use a runbook covering source updates, failed runs and human escalation.
Tools and standards
The design follows your data environment and operating requirements. My UN delivery used LangGraph for stateful orchestration and a RAG knowledge layer with MCP-compatible access. A specific model provider or protocol is chosen only when it suits the task.
Relevant experience
At the United Nations, I built a LangGraph workflow for annual reports with separate retrieval, drafting, review and targeted revision stages. Generated sections were checked for completeness, source consistency and structure before acceptance.
Frequently asked questions
How is this different from agent API integration?
Workflow automation covers the sequence of tasks and decisions. Agent API integration starts with an agent you already have and connects it to one business system. If your workflow already runs and only its tool connection needs work, the integration offer is the narrower starting point.
Can a person review the output?
Yes. We define review and approval points as part of the workflow contract. Domain owners determine what evidence and completeness are acceptable. The workflow can prepare drafts and route them for review; the scope identifies which decisions remain with a person and how unresolved cases are escalated.
Can you automate report preparation?
Evidence-based report drafting, review and targeted revision are supported by my UN delivery experience. We would start with your approved sources, report structure and reviewers. The project scope establishes which sections can be generated, what checks they need and who accepts the final output.
Related services
If your agent already exists and needs one authenticated business system, scope agent API integration.
If you need repeatable acceptance checks for an existing assistant, start with chatbot testing and evaluation.
If the starting point is an approved document collection, explore private knowledge assistant implementation.
Working together
Projects are delivered remotely, with a defined scope, scheduled reviews and written progress updates. We agree meeting times, access requirements and acceptance criteria before work begins. Code, documentation and handover are included as specified in your engagement.
Discuss this engagement
Bring one recurring workflow, a sample input and the output your team needs to review.
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