★ AI chatbot · cost estimate
How Much Does It Cost to Build an AI Chatbot?
A demo chatbot takes a weekend. A chatbot customers trust takes retrieval that finds the right document, evaluations that catch regressions, and guardrails for when the model does not know. The estimator prices the second one.
- Runs in your browser
- No signup
Your estimate: $15,400–$34,100.
Want a second opinion? Send it to me and I'll tell you which features I'd cut to ship weeks sooner.
What people forget to budget for
Evaluation
Without a test set of real questions and expected answers, every prompt change is a guess. Budget time to build one and run it on every change.
Ingestion
PDFs with tables, scanned documents and stale content cause most bad answers. Cleaning and chunking the data is often more work than the chat UI.
Running cost
Token spend scales with usage. Model routing and caching decide whether your unit economics work.
How the estimate works
Each feature has a range of hours for a senior engineer building production-quality software. Those hours scale with the number of platforms, then the estimate adds what every real project needs on top of writing features.
hours = (build + 20% QA + PM overhead) × 1.15 contingency
cost = hours × hourly rate
weeks = hours ÷ productive hours per week
Ranges, not single numbers, because the honest answer depends on details nobody knows yet: how clean the third-party APIs are, how many design rounds you want, how often scope moves. If someone quotes a single number without asking those questions, the range is hiding in their change requests.
Building for web and mobile is not twice the work with React Native: the backend, business logic and much of the UI code are shared. That is why the platform factor for web plus mobile is about 1.5, not 2.
Worked example
Take an AI chatbot MVP with 6 features (sign-up & login, admin panel, file uploads & media, dashboards & charts, ai feature (llm), marketing site), built by a senior freelancer at $60/hour:
| Line | Hours |
|---|---|
| Feature build (incl. setup and design) | 172–380 |
| QA, project management, contingency | 85–188 |
| Total | 257–568 |
That comes to $15,400–$34,100 over roughly 9–19 weeks. Deferring admin panel alone would save about $4,310.
Hours by feature
The ranges the estimator uses, before platform factor and overhead. The features founders most often underestimate are payments, permissions and admin tooling: none of them are visible in a demo, and all of them are needed the week after launch.
| Feature | Covers | Hours |
|---|---|---|
| Sign-up & login | Email + Google/GitHub OAuth, password reset, sessions | 16–32 |
| Admin panel | Manage users, content and orders without touching the DB | 32–64 |
| File uploads & media | Direct-to-storage uploads, image resizing, limits | 16–32 |
| Dashboards & charts | User-facing analytics, aggregates, exports | 24–56 |
| AI feature (LLM) | Chat, summaries or generation with RAG over your data, plus evals | 40–100 |
| Marketing site | Landing page, pricing page, SEO basics, blog | 12–32 |
Questions founders actually ask
How much does it cost to run an AI chatbot each month?
Do I need to fine-tune a model?
Can I use an off-the-shelf chatbot builder instead?
How accurate is this estimate?
Why is this higher than the agency quotes I've seen?
Do AI coding tools make an MVP cheaper?
Estimate by product type
- Cost to build a B2B SaaS
- Cost to build a marketplace
- Cost to build an AI agent
- Cost to build a mobile app
- Cost to build a fintech app
- Cost to build an e-commerce store
- Cost to build a booking app
- Cost to build a CRM
- Cost to build a learning platform
- Cost to build a social / community app
- Cost to build an internal tool
Or start from scratch with the full MVP cost estimator.
More from the workbench
Fine print
Tools: on the house.
Engineer: by the hour.
Building it isn't free either, but it can be faster than you think. Send me the breakdown and I'll tell you what I'd ship first.
I'm Himanshu, an AI and full-stack engineer. I build MVPs, AI agents and the growth plumbing around them for early-stage startups.
