build offer / workflow to production
Agent / Automation Development
Design and build one high-value AI workflow from problem framing to an integrated pilot or production-ready system with tools, evals, monitoring, and human handoff.
Best fit
There is a repeated business workflow that can be accelerated with LLMs, agents, retrieval, or automation.
A prototype exists, but it is not integrated, observable, evaluated, or safe enough for real users.
You need a senior builder who can connect product, architecture, code, data, and operational constraints.
The goal is a working workflow, not a generic workshop or slide deck.
What I build
LLM assistants, RAG workflows, classifiers, routing systems, and tool-using agents.
n8n, Telegram bots, Mini Apps, internal tools, CRM/Notion/Confluence integrations, and API workflows.
Context engineering, prompt systems, memory, retrieval, and tool orchestration.
Evals, traces, cost controls, human handoff, permissions, and rollback paths.
Deployment architecture for cloud, local LLM, or hybrid environments.
Deliverables
Problem framing and workflow map.
Working pilot or production slice for one workflow.
Architecture notes, eval set, and observability plan.
Integration checklist and operational handoff.
Next roadmap: hardening, rollout, security review, and scaling.
process
How it runs
- Pick one workflow with real business pressure.
- Define input, output, tools, permissions, success metrics, and failure modes.
- Build the smallest useful system with evals and tracing from the start.
- Review results, harden the workflow, and decide whether to scale.
Relevant background: Python since 2013, TypeScript, production LLM workflows, AI platforms, Telegram bots, Mini Apps, n8n pipelines, corporate data integrations, servers, local LLMs, and AI hardware.