You will get Set up a Claude or OpenAI workflow for your business
Rising Talent
Project details
I build practical Claude and OpenAI workflows that remove real manual work, not vague AI demos. Good fits are intake, routing, drafting, tagging, enrichment, internal operator tools, and lightweight automations tied to your existing stack. I can scope the workflow, wire the model logic, connect one integration, and shape the output so your team can actually use it. My background is full-stack, so I can also handle the surrounding API, UI, or internal tool work when the automation needs more than prompts alone.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Models
ChatGPT, GPT-4What's included
| Service Tiers |
Starter
$150
|
Standard
$400
|
Advanced
$950
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | - | - | - |
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | |||
Source Code | - |
About Dylan
AI Agent Developer | Claude & OpenAI, MCP, RAG & Automation
Brooklyn, United States - 9:47 pm local time
I specialize in agents specifically, and I work with the newest agent tooling every day: the Claude Agent SDK, the OpenAI and Vercel AI SDKs, and the Model Context Protocol (MCP) for connecting agents to your own systems.
What I can build for you:
- Custom AI agents that use tools, call your APIs, and complete tasks end to end
- MCP servers that securely connect an agent to your internal tools, databases, and SaaS (Slack, Notion, CRMs, custom APIs)
- Document and knowledge assistants (RAG) that answer questions over your contracts, docs, and data
- Workflow automation: intake and triage, research, data extraction, report and email drafting, internal copilots
- The production layer most freelancers skip: evals, guardrails, logging and monitoring, and error handling — so the agent is reliable, not a one-off demo
My stack:
- AI / Agents: Claude (Agent SDK), OpenAI, Vercel AI SDK, MCP, tool-use, RAG, evals and guardrails
- Backend: TypeScript/Node, Python, Express, REST APIs, PostgreSQL, MongoDB, Supabase
- Infra and ops: Docker, CI/CD (Vercel, Render), observability (Grafana/Loki, Sentry), Linux
An edge that helps on sensitive projects: before moving into engineering I worked in legal and risk/investigations (Paul, Weiss and Kroll), so I understand document-heavy, detail-critical, compliance-aware workflows — and I build agents that respect them.
How I work:
1. A short call to map the exact workflow you want to automate
2. A scoped plan with clear milestones — and an early working demo so you see progress fast
3. Build, test against real evals, deploy, and hand off with documentation your team can maintain
If you have a workflow you think an AI agent could handle — or you're not sure whether it can — message me a few sentences about it and I'll tell you honestly what's possible and how I'd approach it.
Steps for completing your project
After purchasing the project, send requirements so Dylan can start the project.
Delivery time starts when Dylan receives requirements from you.
Dylan works on your project following the steps below.
Revisions may occur after the delivery date.
Map the workflow
I review the goal, inputs, outputs, and edge cases so the automation scope is clear before I build.
Build and test the workflow
I wire the prompts, logic, and integration, then test the workflow with real sample cases.