AI Agent Development Company
Codroon is an AI agent development company that builds and ships production AI agents in weeks, not months. We build agents that take real actions inside your systems: update the record, send the invoice, route the ticket, run the report. Not chatbots that tell you what you should do next.
What is AI agent development?
AI agent development is the process of building software that can decide and act on its own: reading context, picking the right tool, and completing multi-step work without a person driving each step. An agent doesn't wait to be asked. It observes a trigger, plans a path, executes across your systems, and checks whether the result was actually correct.
That last part is what separates an agent from a script. A script follows the path you wrote. An agent chooses a path, and changes it when reality doesn't match the plan. Codroon builds these systems end to end: the reasoning loop, the tool integrations, the guardrails that stop an agent doing something expensive, and the monitoring that tells you when it drifts.
AI agents vs chatbots vs RPA: what's actually different
These three get sold interchangeably and they solve different problems. Here's where each one belongs.
| Comparison point | AI Agents | Chatbots | RPA |
|---|---|---|---|
| What it does | Decides, then acts | Responds in conversation | Repeats a fixed script |
| Unexpected input | Reasons a new path | Falls back to “I didn't get that” | Fails, waits for a human |
| Multi-step work | Chains tools across systems | One question, one answer | Fixed sequence only |
| How it connects | Calls APIs, databases, and tools directly | Sits on top of a chat window | Clicks the interface like a person |
| When something changes | Re-plans around it | Needs new intents written | Breaks when a button moves |
| Best for | Work with judgement in it | Answering known questions | High-volume identical tasks |
Most teams asking for a chatbot want an agent. Most teams asking for an agent need one workflow automated first, then a second. We'll tell you which on the call.
Our AI agent development services
Codroon builds agents at four levels of scope. Most projects start at the first and grow into the second.
Custom AI Agent Development
A single agent that owns one workflow end to end. Scoped to a specific job like qualifying leads, reconciling invoices, or triaging support, with the tool access and guardrails that job needs, and nothing it doesn't.
Multi-Agent System Architecture
Several specialised agents coordinating on work too broad for one. A planner that breaks the task down, workers that execute in parallel, and a reviewer that checks output before anything reaches production.
Agent Integration & Deployment
Connecting agents to the systems you already run (your CRM, database, warehouse, ticketing, and internal tools) over MCP where a server exists and direct API integration where one doesn't.
Agent Monitoring & Optimization
Tracing, evals, and cost tracking after launch. Agents drift as models update and data changes. We instrument yours so you find out from a dashboard rather than from a customer.
How Codroon builds an AI agent
Four steps, two to six weeks, and you see working software in the first two.
Discovery and scoping
Free, 45 minutesWe walk through the workflow you want handled and find where an agent actually pays off, which is often not where you expected. You leave with a written scope, an architecture sketch, and a real number. No commitment, and you keep the scope whether you hire us or not.
- written scope
- architecture sketch
- fixed price and timeline
Architecture and agent design
Week 1We decide the shape before writing the agent: single agent or multi-agent, which model, which framework, where the human approval steps go, and what the agent is explicitly not allowed to do. Guardrails get designed here, not bolted on later.
- system design
- tool and data map
- guardrail and escalation spec
Build and iterate
Weeks 2–5We build in weekly increments and you see a working agent at the end of each one. Evals run from day one, so “it feels better” gets replaced with a number. You give feedback on real output, not mockups.
- working agent each week
- eval suite
- integration tests
Deploy, monitor, hand over
Weeks 5–6We ship it to your infrastructure, wire up tracing and cost monitoring, and hand over the repository with documentation. You own all of it. If you want us to keep running it, that's a separate conversation, not a lock-in.
- production deployment
- observability dashboard
- repo and docs
The stack Codroon builds agents on
We pick the right tools, not the trendy ones. Here's what we actually run in 2026 and why.
- Models
- Claude, GPT, and Gemini. We're model-agnostic by default and benchmark on your task rather than assuming. The best model for extraction is often not the best one for planning.
- Agent frameworks
- LangGraph for stateful workflows that need auditability and human approval steps. CrewAI where role-based multi-agent setups fit the problem. The OpenAI Agents SDK and Claude Agent SDK for provider-native builds. Pydantic AI where type safety matters more than flexibility.
- Protocols
- MCP and A2A. MCP is the vertical bus, how an agent reaches your tools and data. A2A is the horizontal one, how agents delegate to each other. Both now sit under Linux Foundation governance, which means building on them is a safe bet rather than a wager on a vendor.
- Retrieval
- pgvector when you're already on Postgres and shouldn't be paying for a second database. Pinecone or Qdrant when scale or filtering demands a dedicated one.
- Observability and evals
- LangSmith, Langfuse, and OpenTelemetry. An agent without tracing is an agent you can't debug, and evals are the only honest way to know a change made things better.
- Automation and infrastructure
- n8n, AWS, Docker, Vercel, Python, TypeScript, and PostgreSQL. Boring where boring is correct.
Where AI agent development pays off fastest
Codroon builds agents across four areas where the work is repetitive enough to automate and variable enough to need judgement.
What AI agent development costs
Most AI agent projects with Codroon run $6,000–$38,000 and take two to six weeks. A single agent owning one workflow sits at the lower end. A multi-agent system with several integrations and human approval steps sits at the upper.
We quote a fixed price after the discovery call, not an hourly rate that grows. If your project doesn't need an agent, we'll say so. A well-built automation is cheaper and we'd rather tell you that up front than six weeks in.
Price your agent in about three minutes with the cost calculator, including what it costs to run each month.
AI agent development: common questions
Most AI agent projects take two to six weeks and cost $6,000–$38,000. You own the code and the agent outright. The discovery call is free and you keep the scope document whether you hire us or not.
Let's find out if an agent is the right answer
Forty-five minutes, no prep, no commitment. Walk us through the workflow and you'll leave with a scope, an architecture sketch, and a real number, even if you build it somewhere else.