An AI agent's price starts with the job you want it to finish. Reading an invoice and preparing a record has a different scope from updating several business systems, handling exceptions and deciding which actions need approval.
At Ekyon, a focused workflow pilot is currently budgeted at $8,000–$15,000. A production operational workflow is $15,000–$40,000+, and a larger custom AI product is $25,000–$75,000+. These are USD planning ranges for our service, not market averages or fixed quotes. The final price depends on the agreed work. Hosting, model usage and ongoing support need their own budget.
This guide helps you work out which scope fits, what to ask a provider, and what you will pay to keep the workflow useful after launch.
AI agent development cost by project scope
| Scope | Ekyon planning range, USD | Indicative delivery | What you are scoping |
|---|---|---|---|
| Workflow pilot | $8,000–$15,000 | 3–5 weeks | One defined process, one core integration, representative examples and a human review step. |
| Operational workflow | $15,000–$40,000+ | 5–10 weeks | A production workflow with multiple integrations, permissions, exception handling, evaluations and monitoring. |
| Custom AI product | $25,000–$75,000+ | 8+ weeks | A product interface and agent tools, with the wider software, access controls and launch work around them. |
Timing assumes the required access, sample data and decisions are available. Unusual integrations, data cleanup or wider product requirements can change both price and schedule. The plus sign means there is no fixed ceiling for the larger scopes.
If you are comparing quotes, start by checking whether each provider is quoting the same outcome. A demonstration on a few hand-picked files has a different delivery standard from software your team can operate, review and recover when something fails.
What makes an AI agent more expensive?
1. The systems it needs to work across
Count the destinations as well as the inputs. A workflow that reads email, finds a customer record, prepares an update and sends it to another tool needs more integration work than a single upload screen.
For each system, the provider needs to understand access, available APIs, permissions, data formats and failure handling. Existing connectors can reduce work. A browser-based integration may be possible when an API is unavailable, but access and reliability need checking before it becomes part of a fixed scope.
Ask: Which integrations are included, and what happens if the software we use changes?
2. The decisions and exceptions
The happy path is only part of the job. Missing fields, conflicting records, duplicate requests and uncertain outputs need a clear next step.
Agree which actions can run automatically, which require approval, and which must stop for a person. More sensitive decisions need stronger permissions, testing and review controls. Model confidence alone is not enough to authorise a consequential action.
Ask: What will the workflow do when it cannot finish safely?
3. The quality and variety of the inputs
Ten similar PDFs are a different challenge from scans, photographs, forwarded emails and files in several formats. A useful estimate depends on examples that reflect your everyday work, including the awkward cases.
You do not always need to train a custom model. The implementation may use an existing model, your instructions, reference information, deterministic rules and integrations. The approach should follow the task and the evidence from testing.
Ask: Which examples will you test, and what counts as an acceptable result?
4. The product around the agent
Users still need somewhere to see the source, correct a result, manage access and recover a failed task. Those screens and controls are part of the software scope.
A background workflow inside an existing system may need a smaller interface. A product sold to customers may also need onboarding, billing, workspaces and support tools. Define those separately so they do not arrive as surprises halfway through the build.
Ask: What will my team receive beyond the model or automation itself?
Still deciding what to automate? The AI workflow automation examples guide helps you compare document handoffs, customer requests, job updates and internal questions before choosing a first scope.
A document workflow you can scope before asking for a quote
Consider a team that receives supplier documents by email and upload. Someone checks the details, assigns a category and prepares an accounting handoff.
A first pilot could cover:
- Receive documents through one agreed intake route.
- Extract the required fields and preserve the source.
- Apply a small set of agreed classification rules.
- Let a person correct the record and review uncertain cases.
- Prepare an export in one agreed format.
- Evaluate the results against representative documents.
Direct posting to an accounting system, payment execution, extra intake channels and department-wide rollout would need separate agreement. Defining that boundary makes quotes easier to compare.
For actual delivery evidence, see the document automation product Ekyon built. That project brings together email and WhatsApp collection, structured extraction, editable records, automation rules and accounting exports. It demonstrates a delivered product; it does not establish a universal price, processing speed or savings figure for your workflow.
For a larger product scope, dMaya is Ekyon's own AI design product. Its interface, agent harness and editable design/code workflow illustrate why building an AI product includes more than connecting a model API.
What should the development quote include?
A useful AI agent development quote makes the boundaries easy to inspect. Ask for:
| Quote item | What to clarify |
|---|---|
| Outcome | The exact process and definition of a successful result. |
| Integrations | Named systems, access requirements and included destinations. |
| Review and permissions | Who can approve actions, what runs automatically and what stops. |
| Evaluation | Representative examples, acceptance criteria and known limitations. |
| Failure handling | Retries, duplicate prevention, alerts and manual recovery. |
| Deployment | Hosting responsibilities, environments and access arrangements. |
| Handover | Documentation, source-code ownership and accounts, as agreed in the project scope. |
| After launch | Support coverage, running costs, response expectations and separately priced changes. |
At Ekyon, these details are agreed for the selected scope. Check the AI workflow automation and integration service for the current offer and project examples.
AI agent running costs after launch
Build cost is one part of the budget. The ongoing bill depends on how often the workflow runs, how much information it processes and the systems it relies on.
| Cost | What drives it | What to ask before launch |
|---|---|---|
| Model usage | Document length, image processing, repeated calls and model choice. | What is the estimated usage for our actual workload, including retries? |
| Hosting and storage | Background jobs, files, databases, retention and availability needs. | Which accounts will hold the resources, and who pays each bill? |
| Other tools and APIs | Connector subscriptions, external services and API charges. | Which subscriptions are needed in addition to development? |
| Monitoring and evaluation | Logs, alerts and checks on output quality. | Who checks failures and reviews performance as the work changes? |
| Maintenance and support | Software changes, provider changes, fixes and new requirements. | What is included in support, and what is a separate change request? |
There is no single reliable monthly price for every AI agent. Request an estimate at your expected workload and a higher-volume scenario, with the assumptions written down. Model/API usage, hosting, third-party subscriptions and optional support should be identified separately from the build quote.
A production workflow needs ongoing care even when the initial build is complete. New document formats and changing business rules do not automatically make an agent improve by itself.
Is the workflow worth automating?
Measure the current work before estimating savings. Record volume, handling time, corrections, delays and the cost of mistakes. Then evaluate the pilot against the same work.
For an illustrative time calculation, 500 documents per month at four minutes each take about 33.3 hours. If a tested workflow reduces the total human handling time to two minutes per document, the remaining work is about 16.7 hours. That would free about 16.7 hours per month, before additional monitoring or support effort.
Those figures are assumptions, not a result from the document automation product or a promised Ekyon outcome. The benefit depends on the time actually saved, how it can be used, recurring costs and whether output quality meets your requirements. A small-volume task may be easier to improve with a template, a process change or an existing tool.
Should you use an automation platform or commission custom work?
Existing products and workflow platforms can be a good fit when their connectors, permissions and operating model meet your needs. They can also support sophisticated workflows. For example, n8n documents branching, merging, loops and error handling, and Zapier offers integrations, workflow automation and agent products.
Evaluate an existing option against your real inputs before commissioning a build. Ask whether it supports your review process, handles the necessary exceptions and gives you the access and export arrangements you need.
Custom development becomes worth investigating when those options leave an important gap: a specific product interface, unusual integration, business rule, deployment requirement or control over how the system operates. A custom build may still use existing platforms and services where they fit.
The choice depends on the workflow and total cost of operating it. Either route needs a defined process, tested results and ongoing maintenance.
How to compare two AI agent development quotes
Compare the same process, integrations, review controls and acceptance criteria. Ask each provider to separate development, external running costs and ongoing support, and to list the assumptions that could change the estimate.
For a one-year planning comparison, add the quoted build cost to 12 months of estimated hosting, model usage, subscriptions and support. Include rollout, internal review and any separately scoped changes. This gives you a clearer comparison than choosing on the build price alone. It remains an estimate until the workload and delivery terms are agreed.
Bring these details to a scoping conversation
You can make the first discussion useful without preparing a technical specification. Bring:
- The process you want to improve and who uses it.
- Approximate weekly or monthly volume and current handling time.
- A few permitted, representative examples, including exceptions.
- The software involved and available integration access.
- Actions that must require approval and the outcome you want from a pilot.
Share sensitive samples only through an agreed secure process. We can start by discussing the workflow and the smallest useful scope.
Explore Ekyon's AI workflow service and project evidence, or book a conversation about your workflow.
What would your first useful workflow cost?
Tell us what takes time, which tools your team uses and what a useful result would look like. We will discuss whether a pilot fits and what would shape the estimate.
Ready to scope one useful workflow?
See project evidence, review controls and delivery scope for Ekyon's AI workflow automation and integration services.
