The honest answer
Custom AI development costs anywhere from a few thousand USD to larger five- or six-figure investments, depending on what you are building. That is a wide range because AI development covers everything from a focused workflow to a production platform.
Here's how we break it down at DK Studio, informed by 14+ products across the team.
Pricing by project type
| Project Type | Typical Range | Timeline | Examples |
|---|---|---|---|
| Single AI Agent | Low thousands | 3-7 days | Email processor, lead scorer, content generator |
| Agentic Workflow | Mid thousands | 1-2 weeks | Multi-step operations pipeline, automated reporting system |
| MVP / Web App | Mid to upper thousands | 2-4 weeks | SaaS platform, client portal, marketplace |
| Complex Multi-Agent System | Upper thousands to low tens | 3-6 weeks | Enterprise dashboard with OCR, multi-source data pipeline, decision engine |
What drives the cost up
- Number of integrations — Each external system (CRM, ERP, payment processor, email provider) adds complexity. Connecting to 2 systems is straightforward. Connecting to 10 with data flowing between them requires careful architecture.
- Decision complexity — A workflow that follows simple rules is quick to build. A system that needs to interpret documents, make judgment calls, or handle 20 different edge cases requires more engineering.
- Data volume — Processing 100 records per day is different from processing 100,000. High-volume systems need optimization, queue management, and monitoring.
- Compliance requirements — Healthcare, finance, or legal applications may need audit trails, data encryption, access controls, and compliance documentation.
- User interface — If the system needs a dashboard, admin panel, or client-facing portal, that adds frontend development time.
What drives the cost down
- Clear scope — The more precisely you can define what the system should do, the faster we can build it. Vague requirements cause iteration cycles that add time and cost.
- Standard integrations — If your tools have good APIs (Slack, Google Workspace, HubSpot, Stripe), integration is fast. Legacy systems with no API add cost.
- Starting small — Build one workflow first. Prove the ROI. Then expand. This is almost always cheaper than trying to automate everything at once.
DK Studio vs other options
| Option | Upfront Cost | Ongoing Cost | Commercial terms |
|---|---|---|---|
| DK Studio | Scoped project or ongoing team | Depends on engagement | Agreed in the scope |
| Enterprise vendor (UiPath, etc.) | Implementation fee | Annual licensing | Vendor platform terms |
| Freelancer | Hourly or project-based | Maintenance varies | Contract dependent |
| In-house team | Hiring and salaries | Salaries and infrastructure | Company employment terms |
For a deeper comparison with enterprise RPA platforms, read DK Studio vs UiPath. For help deciding whether to build custom or use an existing platform, read build vs buy AI automation.
How to think about ROI
The question isn't "can I afford AI development?" It's "can I afford not to?"
If your team spends 20 hours per week on a process that an agentic workflow can handle, that's 20 hours of salary, benefits, and opportunity cost — every single week. Most of our projects pay for themselves within 1-3 months through time savings alone.