Hire AI agent developers to build agents that work inside your systems
Webify.AI builds AI agents of its own, across industries. Hire our AI agent developers to build yours: agents that read requests, use your tools and hand over to a person when needed.
We build agents ourselves
Our own AI agents are listed in the Bot Store. You hire from the company that builds them.
From $45 an hour
AI / LLM engineers at $45/h and senior AI engineers at $60/h, billed hourly or monthly.
You choose the developer
Two named profiles in 48 hours. You interview them before anyone starts.
What does an AI agent developer do?
An AI agent developer builds software in which a language model decides which steps to take and carries them out through tools. They define those tools, connect them to your systems, set limits on what the agent may do, and test it on real cases. They also design how the agent hands work to a person.
An AI agent is more than a prompt. It is a loop: the model reads the situation, picks a tool, looks at the result and decides what to do next. The developer's job is to make that loop useful, safe and affordable.
- Map the task. Write down what the agent should handle, what it must never do, and when it should stop.
- Build the tools. Small, well-described functions such as "look up order", "create ticket" or "check availability", each with checked inputs.
- Connect your systems. Use the APIs of your CRM, help desk, database or booking system, through accounts with the least access that works.
- Write the instructions. The system prompt, the tone, and the rules the agent follows.
- Handle memory and state. Decide what the agent remembers within a conversation, and what it stores between conversations.
- Design the handover. When the agent passes a case to a person, and what context goes with it.
- Test and monitor. A test set of real requests, logs of every tool call, and alerts when something goes wrong.
On a small project, one developer does all of this. On a larger build, a senior AI engineer designs the agent and reviews the work. An AI / LLM engineer then builds the tools and integrations.
What is the difference between an AI agent and a chatbot?
A chatbot answers. An AI agent acts. A chatbot replies to messages, from a script or from a language model. An agent can also use tools to look things up, update records and finish a task across several steps. A project can start as a chatbot and add agent abilities one tool at a time.
Swipe the table sideways to see every column.
| Rule-based chatbot | LLM chatbot | AI agent | |
|---|---|---|---|
| How it decides what to say | Fixed flows and keyword rules | A language model, often with your documents as context | A language model that also chooses which tools to use |
| What it can do | Answer set questions and collect details | Answer open questions in natural language | Answer, then act: look up, update, book or escalate |
| Connection to your systems | Usually none, or a form | Read-only, such as a document search | Read and write through APIs you approve |
| Main risk | Users get stuck outside the script | Confident wrong answers | Wrong actions, if its limits are loose |
| Good fit | A small, stable set of questions | Questions answered from your content | Repeated tasks with clear rules, on systems that have APIs |
If you want to hire AI chatbot developers, the same engineers build all three. Start with the simplest version that solves the problem. Add tools only where an action saves real work.
A chatbot that answers from your own documents is a RAG system underneath. Our page on RAG development explains how that part is built.
Our rates
Published prices in US dollars. Monthly plans are 160 hours, about 15% below the hourly rate.
Mid-level developer
3 to 5 years
$25 / hour
$3,400 a month (160 h)
Senior developer
6 or more years
$35 / hour
$4,750 a month (160 h)
AI / LLM engineer
Agents, RAG, IBM watsonx
$45 / hour
$6,100 a month (160 h)
Senior AI engineer
Leads AI architecture and delivery
$60 / hour
$8,150 a month (160 h)
Two-week trial with the developer you choose. No charge if you stop within the first five working days. US Eastern clients get 09:00 to 12:00 US Eastern time through an evening shift, at 15% extra. Full pricing and comparisons.
What can an AI agent do for a business?
An AI agent suits repeated tasks that follow clear rules and touch systems with APIs. Common examples are answering customer questions with live order data, qualifying sales leads, booking appointments, triaging support tickets and finding answers in internal documents. Tasks involving decisions about money, health or legal matters should keep a person in the loop.
Customer support agent
Answers questions from your help content and live account data, and hands complex cases to your team with a summary.
Sales and lead agent
Replies to new leads, asks qualifying questions, then books a call or updates your CRM.
Operations agent
Checks order status, schedules jobs or appointments, and sends updates, inside the rules you set.
Internal knowledge agent
Answers staff questions from policies, manuals and past tickets, citing the source each time.
Back-office agent
Reads incoming emails or documents, pulls out the details and drafts the right record for a person to approve.
Agents in our Bot Store
Webify.AI's own AI agents, grouped by industry. Browse them to see what a finished agent looks like.
→ Read more
You can see the kinds of agents Webify.AI builds on our AI agents page. Ready-made agents are listed by industry in the Bot Store.
How long does it take to build an AI agent?
A typical first agent, scoped to one task with one or two system integrations, takes roughly six to twelve weeks from discovery to production. Discovery takes days, a working prototype takes a few weeks, and piloting and hardening take a few more. These are typical ranges, not promises; access to systems and data usually decides the pace.
Swipe the table sideways to see every column.
| Phase | Typical length | What happens | What you have at the end |
|---|---|---|---|
| Discovery and scoping | 3 to 10 working days | Pick one task, collect real examples, list the systems involved and agree what the agent must never do. | A short written scope and a first test set |
| Prototype | 2 to 4 weeks | Build the core loop and the first tools against test or read-only systems. | A working demo, scored against the test set |
| Pilot | 2 to 4 weeks | A small group of real users or staff try it. Every conversation and tool call is reviewed. | A list of failures, fixed and re-tested |
| Hardening and launch | 1 to 2 weeks | Add limits, monitoring, alerts, the handover to people, and write access where it is needed. | The agent live for all users, with a runbook |
| Ongoing improvement | Continuous | Review logs, add test cases from real failures, update prompts and tools, and re-test when the model changes. | Regular fixes and a growing test set |
Typical ranges for a scoped first agent with one or two integrations, not a promise. Waiting for API access, security reviews or test data adds time. Reusing an existing knowledge base can save it.
These things usually make an agent project take longer:
- Systems without an API, or APIs that need a long approval process before anyone can use them.
- No agreed definition of a correct result, so testing has nothing to measure against.
- Too many tasks in the first version. One task done well beats five done badly.
- Data spread across tools, out of date or full of exceptions.
How do you stop an AI agent from doing the wrong thing?
Limit what the agent can do, check what it tries to do, and record everything it did. In practice that means narrow tools, least-privilege accounts, validated inputs, human approval for risky actions, spending and rate limits, and full logs. Then test against hostile inputs such as prompt injection before real users reach it.
- Narrow tools. "Refund up to the order value" is safer than "run any database query".
- Least privilege. The agent's accounts can reach only what its task needs.
- Validation. Ordinary code checks every tool input before anything runs.
- Approval steps. Refunds, deletions, payments and messages to many people wait for a person to confirm.
- Limits. Caps on steps per task, tool calls and token spend, so a loop can't run away.
- Untrusted input. Text from users, emails and web pages is treated as data, never as instructions.
- Logs. Every prompt, tool call and result is recorded, so any action can be traced.
None of this makes an agent perfect. It makes mistakes rarer, smaller and easier to find. That is the honest goal for any agent that touches real systems.
Should you hire agent developers or use an AI agent development service?
Hire AI agent developers when you want to steer the work yourself, with your team setting priorities. Use an AI agent development service when you would rather hand over a defined scope. Choose a ready-made agent when one already fits. As an agentic AI development company, Webify.AI offers all three.
Swipe the table sideways to see every column.
| Hire agent developers | AI agent development services | Ready-made agent | |
|---|---|---|---|
| Who leads the work | You do. The developer joins your team. | Webify.AI, against an agreed scope. | Webify.AI built it already. You set it up for your business. |
| How you pay | Hourly from $45, or a monthly plan | Agreed per project | Ask us for pricing |
| Best for | Ongoing agent work, and teams that want the skills in-house | A defined agent you don't want to manage day to day | A common task where an existing agent already fits |
| Where to start | Ask for two profiles with the form on this page | Send us your scope through the contact page | Browse the Bot Store by industry |
If you are comparing agentic AI development companies, ask each one the same questions. Do they build and run agents of their own? Who exactly will write the code? Will you own it? How do they test an agent, and what happens when the underlying model changes?
Our answers: we build our own agents, and you interview the named developer. The IP is assigned to you. Testing uses your real cases, and re-testing after model changes is part of the work. To discuss a fixed-scope build instead, use our contact page.
Which frameworks and models do AI agent developers use?
Agent developers typically combine a language model that supports tool calling with either an agent framework or plain code. Common frameworks include LangChain, LangGraph and LlamaIndex; model providers also offer their own agent tools. Our developers work with the model and framework you have chosen, or keep to plain Python or TypeScript when a framework adds little.
- Models. Hosted models from providers such as OpenAI or Anthropic, open-weight models you run yourself, or IBM watsonx. Webify.AI is an IBM Partner and deploys on watsonx and open-weight models.
- Frameworks. LangChain and LangGraph for chains and multi-step flows, LlamaIndex for connecting models to documents, or the provider's own SDK.
- Tool standards. The Model Context Protocol (MCP) is an open standard for describing tools and data sources, so different models and apps can use them.
- Your stack. Python, or TypeScript with Node.js, PostgreSQL for state and logs, and your existing APIs.
Agent frameworks change quickly. A good agent developer keeps the core logic in your own code, so the framework can be swapped without a rewrite.
Some agents need deeper model work, such as fine-tuning or a model running on your own servers. For that side, see LLM engineers.
How much does it cost to hire an AI agent developer?
An AI / LLM engineer costs $45 an hour, or $6,100 for a 160-hour month. A senior AI engineer, who designs the agent and reviews the work, costs $60 an hour or $8,150 a month. In the UK the rates are £36 and £48 an hour. Model usage is billed separately by your provider.
| Role | Plan | Cost per month |
|---|---|---|
| AI / LLM engineer | Monthly, 160 hours | $6,100 |
| Senior AI engineer | Hourly, 80 hours | $4,800 |
| Total | $10,900 |
An illustration built from our published rates, not a quote. The right team depends on your scope. A small, well-scoped agent may need only one engineer.
Model usage, hosting and any paid services the agent calls are extra. They are billed by those providers. Your developer can estimate token costs from a sample of real conversations before launch.
Every rate, in USD and GBP, is on our pricing page.
How does an AI agent developer work with your team?
They work as a member of your team. They join your stand-ups, use your ticket system and commit to your repositories. UK teams overlap 09:00 to 13:00 UK time; US teams can have 09:00 to 12:00 Eastern through an evening shift. You interview them first, then start with a two-week trial.
- 1
Week 1: access and scope
The developer gets access to your repositories and test systems, meets the people who own the task, and writes down the agent's first job. If you stop within these first five working days, there is no charge.
- 2
Week 2: first tools
They start on the first tools against test data, with daily updates in your channel and pull requests for your review.
- 3
After the trial
You carry on hourly from 80 hours a month, or move to a monthly plan. The developer stays named in your contract.
UK teams get 09:00 to 13:00 UK time every working day, inside a normal Indian working day, at no extra cost. US teams get 09:00 to 12:00 US Eastern time through an evening shift, at 15% extra. If you are adding several AI roles at once, see AI staff augmentation.
You own all the code: IP is assigned to you. Developers are named in the contract and never swapped without your agreement. A person reviews all AI-assisted code, and your code never goes into public AI tools.
Frequently asked questions
Do we need our own AI model to build an agent?
No. Most agents use a hosted model through an API, under your own account. If data must stay inside your network, an open-weight model on your own servers works too.
Can one AI agent work across several systems?
Yes, through one tool per system, such as your CRM, calendar and help desk. Each extra system adds testing and more ways to fail, so a first agent usually starts with one or two.
Can an AI agent use our CRM or help desk?
Yes, if the system has an API or another way for software to read and write records. The developer connects each action as a separate tool, with its own permissions, and tests it on test data first.
Which channels can an AI agent work in?
The agent's logic is separate from the channel. The same agent can sit behind a website chat, a messaging app, email or an internal tool. Each channel needs its own connection and testing, so it usually makes sense to launch on one first.
What happens when the agent can't answer?
It should say so and hand over. A good handover passes on the conversation, what the agent tried and what it found, so the person doesn't start again. Designing that path is part of the build.
How do you measure whether an agent is working?
Against a test set of real requests, scored before launch and after every change. In production, track how often it finishes a task, how often it hands over, and what users and staff say about the results.
Who maintains the agent after launch?
Whoever you choose. You can keep the developer on an hourly plan for upkeep, or hand the agent to your own team with documentation and a runbook. The code is in your repositories either way.
Can we start from an agent in the Bot Store?
If an agent in the Bot Store is close to what you need, tell us. We will say plainly whether adapting it makes more sense than building a new one.
Are multi-agent systems worth it?
Sometimes. Splitting work across several agents can help when tasks are very different, but it adds cost and more places to fail. Start with one agent and good tools, and split only when testing shows a clear reason.
Should customers know they are talking to an AI agent?
Yes. Telling users they are talking to an AI, and giving them a way to reach a person, builds trust. In some places it is also a legal requirement, so check the rules where you operate.
Ask for two AI agent developer profiles
Tell us the role and when you need someone. We'll email two named engineers with their experience and availability within 48 hours, and you choose who to interview.
- No cost to receive profiles
- Two-week trial with the developer you choose. No charge if you stop within the first five working days.
- Invoiced in USD or GBP; IP assigned to you.