Autonomous task execution

AI Agent Workflows

Design and build AI agent workflows that plan, execute, and complete multi-step tasks — from research and data gathering to report generation and actions.

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Research & discovery

Task decomposition and agent goal definition
Tool and API availability audit
Human oversight checkpoint mapping
Failure mode and retry strategy planning

Development approach

Agent orchestration with LangChain or custom framework
Tool registry for API and database actions
Human-in-the-loop approval gates
Execution logging and replay for debugging

Recommended tech stack

OpenAI

LLM

Reasoning and planning for agent steps.

Python

Orchestration

Agent framework and tool wiring.

Node.js + TypeScript

API

Agent trigger API and UI backend.

PostgreSQL

Database

Task state, logs, and results.

Key features

Multi-step autonomous task execution
Tool use for APIs and databases
Human approval checkpoints
Execution history and replay

Deliverables

Working agent workflow MVP
Tool integration layer
Admin monitoring dashboard
Agent prompt and config documentation

Other application types

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