AI Agent Development Services
Custom AI agent development services and AI integration services. I build production agents with OpenAI, LangChain, and Agno — with tool use, memory, multi-step reasoning, evals, and human-in-the-loop guardrails — for startups in the USA, UK, Germany, and Australia.
Why startups hire a custom AI agent developer
Off-the-shelf chatbots solve a fraction of the problem. AI agent development services deliver a system that reasons across your tools, remembers context, and takes action — not just text. The result is a product feature, an internal copilot, or an autonomous workflow you actually trust to run unattended.
I have shipped these systems for clients in 4 continents, with 100% Job Success on Upwork and 5.0★ reviews on every engagement.
What I build
Lead qualification agents
Score, route, and personalize the first response to inbound leads — connected to your CRM with structured outputs.
Customer-support copilots
Drafts replies inside Gorgias / Zendesk / Front using order context and your knowledge base. Human approves before send.
RAG over your documents
Embed and search SOPs, contracts, product manuals. Retrieval-augmented agents that cite sources and refuse to hallucinate.
Internal ops assistants
One agent that searches Notion, queries Postgres, books meetings, and drafts updates — purpose-built for your team.
Multi-agent pipelines
Coordinated specialist agents (researcher, writer, reviewer) for content, code, and analytical workflows.
AI Integration into existing apps
Add LLM-powered features to your existing Django, FastAPI, or Node backend — clean, secure, observable.
The stack I build on
LLMs: OpenAI (GPT-4 class), Anthropic Claude 4, open-source via Hugging Face · Agent frameworks: LangChain, Agno, OpenAI Assistants · Memory + retrieval: Pinecone, Qdrant, pgvector · Tooling: function calling, structured outputs, JSON schema validation · Eval: LangSmith, custom regression suites, A/B prompt tests · Deployment: FastAPI, AWS Lambda, AWS SageMaker, Docker.
How I de-risk AI agent projects
- Eval-first development — we agree on a small input/output dataset before any prompts are written.
- Human-in-the-loop by default — high-stakes outputs land in an approval queue, not the customer's inbox.
- Structured outputs — JSON schemas, not freeform text, so downstream code never breaks.
- Observability from day one — every prompt, response, tool call, and cost logged.
- Cost ceilings — per-user / per-request limits to keep your OpenAI bill predictable.
- Graceful fallbacks — when the agent is unsure, route to a human or a deterministic path.
Engagement options
- Single-purpose agent: $1,500 – $4,000 fixed-price, 2-4 weeks.
- Multi-agent or RAG system: $3,500 – $8,000, 3-6 weeks.
- AI integration into existing app: $1,000 – $4,000 depending on scope.
- Monthly retainer for prompt tuning, evals, new tools: $900 – $3,500.
Frequently asked questions
What are AI agent development services?
AI agent development services build agents that can decide, reason, and act — not just respond. They use OpenAI / Claude with function calling, frameworks like LangChain or Agno, vector stores for memory, and a tool layer (your APIs, the web, your DB). Production AI agents include evals, retries, observability, and a human-in-the-loop fallback.
How are AI agents different from a chatbot?
A chatbot answers questions. An AI agent picks tools, takes multi-step actions, remembers what it learned, and produces a structured outcome. Agents qualify leads, classify and route tickets, fill forms, run research, draft documents, and trigger downstream automations — all autonomously with guardrails.
Which AI integration services do you offer?
I integrate OpenAI / Anthropic / open-source LLMs into existing backends and SaaS stacks: Django / FastAPI services, n8n / Make.com / Zapier workflows, HubSpot / Close / Salesforce / GoHighLevel CRMs, Slack, Notion, and any system with an API or webhook.
Do you build custom AI agents for startups?
Yes — startups are most of my client base. I deliver custom AI agents end-to-end: discovery, prompts, tool layer, evals, deployment on AWS or your stack, monitoring, and a runbook. Typical first agent ships in 2-4 weeks.
How do you ensure quality of LLM outputs?
Every production agent has a written eval set (real input / expected output pairs), automated regression checks before each prompt change, a human-in-the-loop approval lane for high-stakes outputs, observability via LangSmith or custom logging, and a fallback path when the agent is uncertain.
What does an AI agent development engagement cost?
Single-purpose agents typically run $1,500 – $4,000 fixed-price (2-4 weeks). Multi-agent systems with RAG, memory, and many tools usually run $3,500 – $8,000 (3-6 weeks). Monthly retainers cover ongoing prompt tuning and new tools.
Related reading: How to Hire an AI Automation Engineer — 10-Point Checklist.
Ready to ship this for your business?
Send a 2-line message describing your stack and the workflow that costs you the most hours each week. Reply within 4 hours with a scope, timeline, and fixed quote.