Short answer: at Xcrino, an AI agent proof of concept starts from $3,000 (about ₹2.7 lakh) and usually takes 2–4 weeks. A first production release starts from $5,000 (about ₹4.5 lakh) and usually takes 1–2 months. A dedicated AI/ML developer for ongoing work starts from $1,250 (about ₹1.13 lakh) a month. The final price depends on five things, explained below.
What is an AI agent, and why does the price vary so much?
An AI agent is software that uses a large language model to complete tasks, not just answer questions. It reads information, decides what to do next and takes actions through the tools it is allowed to use, such as updating a CRM record or drafting a reply for approval. Two agents can look similar in a demo and differ ten times in cost, because the work is mostly in the connections, the data and the safety checks around the model.
What drives the cost of an AI agent?
- The task: answering questions from documents is simpler than taking actions across several systems.
- Your data: clean, well-organised data is quicker to use. Scattered or inconsistent data needs preparation first.
- Integrations: every system the agent reads from or writes to (CRM, ERP, email, databases) adds build and testing time.
- Risk and accuracy: actions that affect money, customers or compliance need human approval steps, more testing and logging.
- Running costs: model usage, hosting and monitoring are ongoing monthly costs, separate from the build.
What do you get at each price level?
Proof of concept, from $3,000 (about ₹2.7 lakh), 2–4 weeks: one task, built on your real data, with measured results and a clear go or no-go recommendation.
First production release, from $5,000 (about ₹4.5 lakh), 1–2 months: the proven task connected to your systems, with permissions, approval steps, testing and monitoring, ready for daily use.
Ongoing work, from $1,250 (about ₹1.13 lakh) a month per dedicated developer: new tasks, more integrations, and improvements based on how the agent performs.
How can you keep AI agent costs under control?
- Start with one frequent, measurable task rather than a general assistant.
- Run a fixed-price proof of concept before committing to a full build.
- Agree success criteria up front, so you know when to stop or scale.
- Plan running costs from day one, for example routing simple requests to cheaper models and caching common answers.
- Make sure you own the code. At Xcrino, source code and IP transfer to you on full payment.
Is it cheaper to build an AI agent in India?
Building with an experienced team in India usually costs less than the same work in the US or Western Europe, mainly because of engineering rates. What matters more than location is whether the team has shipped agents to production, tests them properly and is clear about running costs. Ask any vendor for a working proof of concept and a named person who signs off on quality.
How Xcrino prices AI agent projects
Xcrino is an AI-first software development company in New Delhi, founded in 2016, that has served 560 clients in 26 countries. 94% of our projects have been delivered on time and on budget. Every AI project starts with a free consultation, then a fixed quote. Our founder and AI lead reviews whether your data can support the agent before any build starts. Learn more about our AI agent development services, our AI proof of concept, or see a machine-learning case study.
Not sure whether you need an agent at all? Before you set a budget, read our guide to AI agent vs chatbot. It compares the two with diagrams and shows when a simpler chatbot is enough.
Want to see what the build involves before you budget? Read our step-by-step guide on how to build an AI agent.
Comparing building with buying a ready-made tool? Our guide to custom software vs SaaS explains when each one wins.
How much does an AI agent cost to run after launch?
The build price is only part of the cost. After launch an agent has running costs that continue every month, and a quote that leaves them out can look much cheaper than it is. The main running costs are:
- Model usage. Each task the agent handles calls a language model, and the provider charges for that use.
- Hosting and monitoring. The servers, logs and alerts that keep the agent running and show when it fails.
- Maintenance and improvement. Fixes when a connected system changes, and updates as you add request types.
- Review time. People who approve actions and check a sample of the agent's work.
Two choices made during the build keep these costs down: sending simple requests to a cheaper model, and storing answers to common questions so the agent does not recompute them. Ask any vendor to quote running costs separately from the build.
The diagram below separates the one-off build from the monthly running cost, so you can compare quotes fairly.
A worked example: budgeting a refund-processing agent
Take an agent that handles duplicate-charge refunds, with a person approving large amounts. Using Xcrino's starting prices, the budget unfolds in three stages:
- Proof of concept, from $3,000 (about ₹2.7 lakh), usually 2–4 weeks. It tests the task on your real refund history and measures accuracy and cost per refund.
- First production release, from $5,000 (about ₹4.5 lakh), usually 1–2 months. It connects the agent to your order and payment systems, with approvals, testing and monitoring.
- Ongoing work, from $1,250 (about ₹1.13 lakh) a month per dedicated developer. It adds new request types and improves accuracy over time.
The starting prices of the first two stages add up to $8,000 (about ₹7.2 lakh). Final quotes depend on your systems, your data and the risk of the actions, so treat this as a floor for planning and not as a promise.
Why do so many AI agent projects get cancelled?
Gartner predicted in June 2025 that over 40% of agentic AI projects will be canceled by the end of 2027 because of escalating costs, unclear business value or inadequate risk controls. Each of the three causes has a budget answer:
- Escalating costs: a fixed-price proof of concept and a separate quote for running costs.
- Unclear business value: success measures agreed in numbers before anything is built.
- Inadequate risk controls: approvals, logging and testing paid for from the start, not added later.
What should you ask a vendor before you sign?
- Who signs off on quality, and can I speak to them?
- Is the running cost quoted separately from the build?
- Who owns the source code and the data when the project ends?
- How will the agent be tested, and on whose data?
- What does it do when it is unsure, and who is told?
- Can I see a working proof of concept before a full commitment?
- Is the price fixed, or time and materials, and what is excluded?
What does a vendor need from you to quote accurately?
- A short description of the workflow, step by step.
- The systems involved and whether each has an API.
- A sample of real, anonymised data.
- The actions the agent may take alone, and those that need approval.
- The expected number of requests each month.
- The measure that would make the agent a success.
Send these on a free consultation and you receive a fixed quote. Our founder and AI lead, Dr Sunil Gupta, reviews whether your data can support the agent before the build starts.
This guide is part of our series on AI agents. For the whole path from idea to launch, read AI agents for business: the complete guide.
Questions we are often asked
How much does it cost to build an AI agent?
At Xcrino, an AI agent proof of concept starts from $3,000 (about ₹2.7 lakh) and usually takes 2–4 weeks. A first production release starts from $5,000 (about ₹4.5 lakh) and usually takes 1–2 months. The final price depends on the task, your data, the integrations, the risk of the actions and the running costs.
What are the ongoing costs of an AI agent?
Model usage, hosting and monitoring are monthly running costs that sit apart from the build. Ask any vendor to quote them separately, so the build price does not hide them.
Why do AI agent quotes vary so much?
Agents differ in task, data quality, number of integrations and risk. Two agents can look similar in a demo and differ many times in cost, because most of the work is in the connections, the data and the safety checks around the model.
Can I start with a small budget?
Yes. A fixed-price AI proof of concept tests one task on your real data before you commit to a full build.
Do I own the code?
At Xcrino, source code and IP transfer to you on full payment, and we sign an NDA whenever you ask.
How do I get an accurate quote?
Describe the task, the systems the agent must connect to, your data and the actions it may take alone. Every AI project at Xcrino starts with a free consultation, followed by a fixed quote.