Pricing and quotation guide
AI chatbot development cost
An AI chatbot has three kinds of cost: building it, running it and looking after it. Build costs depend on the scope, how much work your sources need, whether a ready-made platform is configured or a custom assistant is developed, which systems it connects to and how thoroughly it is tested. Running costs usually include usage-based fees from the AI model provider and any platform subscription. Looking after it means staff or provider time to review conversations and keep sources current, which is easy to overlook and often the largest ongoing cost.
This guide covers cost drivers, typical scopes, pricing approaches, running costs and how to compare quotes. It gives no prices, because they depend on scope, volume and suppliers; LetGetGrow sets out the cost for your project in a custom quotation.
Illustrative diagram
What drives build cost
- Scope
- More topics mean more sources, rules and testing.
- Source preparation
- Scattered or outdated documents need sorting and rewriting.
- Platform or custom
- Configuring a product is usually quicker than building from scratch.
- Integrations
- Connecting to orders, bookings or a helpdesk adds development and testing.
- Testing depth
- Testing many real questions takes time but reduces risk.
Costs paid to third parties (separate from our fees)
- AI model usage fees
- Chatbot platform subscription
- Helpdesk or live chat software
- Hosting for custom builds
Ask for running costs to be estimated at your expected monthly conversation volume.
Chatbot projects compared
| Project | Typical scope | Relative cost |
|---|---|---|
| Focused | A few topics, existing help pages as sources, simple handover | Lower |
| Standard | Broader topics, sources rewritten, helpdesk handover | Moderate |
| Connected | Looks up orders or bookings, custom integrations, deeper testing | Higher |
How chatbot projects are priced
Fixed build
Suits you when
- Scope and sources agreed
Watch out for
- Testing included
- Changes after launch
Pilot then expand
Suits you when
- Unsure of value
Watch out for
- Success measures agreed
Monthly service
Suits you when
- Ongoing optimisation wanted
Watch out for
- What the fee covers
- Usage fees on top
Running costs
AI model providers often charge according to usage, so the bill grows with the number and length of conversations. Platforms may charge a monthly fee, sometimes with conversation limits. Ask for an estimate at your current volume and at double it, and check whether fees are paid directly by you or passed through by the provider.
Source preparation
If your help information is current and well organised, preparation is quick. If it is spread across old documents, emails and staff knowledge, writing clear source material can be a substantial part of the project. That work also improves your website and staff guidance, so it has value beyond the chatbot.
Example: a pilot to test value
Illustrative example — not a client case study
Situation: A holiday cottage business is unsure whether a chatbot is worth the cost.
- A pilot covers check-in, parking and pets, using existing guest information.
- Running costs are tracked for two months alongside the number of emails received.
- The business decides to expand scope once guests use it and emails fall.
What this shows: The pilot gave real figures before a larger commitment. This example is illustrative.
The cost of looking after it
Someone needs to review conversations, update sources when policies change and adjust instructions when answers drift. Whether that is your staff or a provider's monthly service, budget the hours. A chatbot nobody maintains becomes less accurate over time.
Integrations
Answering general questions needs no integration. Looking up a customer's order or booking means connecting securely to other systems, handling identity checks and testing failure cases, which adds cost and data protection considerations.
Comparing quotes
Check scope, source preparation, platform or custom build, integrations, testing and shared results, handover design, data protection support, running cost estimates, ongoing support and ownership of configuration.
Keeping the cost down
Start with a focused scope, tidy your help information first, use a platform if it fits, defer integrations until the basic chatbot proves useful and review conversations in-house.
Judging the value
Compare total cost with what it replaces or improves: emails answered, enquiries outside office hours, staff time freed. Count only what you can measure, and include the time spent maintaining it.
Data protection work
A data protection impact assessment, privacy notice updates and supplier terms take some time and, if you use an adviser, some cost. ICO guidance says AI use usually requires a DPIA, so include it in the budget.
Testing
Testing against a large set of real questions, including difficult and out-of-scope ones, takes time but is how problems are found before customers see them. A quote with little testing may be cheaper and riskier. Ask how many test questions are included and whether results are shared.
Questions about AI chatbot development cost
What affects AI chatbot cost?
Scope, source preparation, platform or custom build, integrations and testing.
What are the running costs?
Usage-based model fees, platform subscriptions and upkeep time.
Is a pilot worth it?
It can show real costs and value before a larger commitment.
Why does source preparation cost money?
Clear, current sources take work if information is scattered.
Do integrations add much?
Looking up orders or bookings adds development and testing.
Should data protection be budgeted?
Yes; ICO guidance says AI use usually needs a DPIA.
Sources referenced
Platform features, guidance and rules change. We check the current versions before committing to an approach. This page is general information, not legal advice.
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