The mid-market automation gap
You run operations at a company with 50-500 employees. Your team handles complex, high-volume processes — reporting, approvals, data reconciliation, vendor management, compliance workflows. You know these should be automated.
But when you look at the options, nothing fits:
- Enterprise platforms (UiPath, Automation Anywhere) — Six-figure licensing, 6-month implementations, and you need to hire 1-2 dedicated RPA developers just to maintain the bots. Built for companies with 5,000+ employees, not yours.
- Off-the-shelf tools (Zapier, Make) — Great for simple "if X then Y" automations, but they can't handle the judgment calls, exceptions, and multi-step decision logic your operations actually require.
- Hiring in-house — You'd need to recruit AI/ML engineers, which takes months and costs $200K+ per head. Even then, they're building from scratch with no product design support.
There's a gap in the middle. That's where we operate.
What we build for mid-market ops teams
We build custom agentic workflows — AI systems that don't just follow scripts, but understand context, make decisions, and handle exceptions. Tailored to how your specific operations work.
Common workflows we automate
- Report generation and distribution — Pull data from multiple sources, analyze trends, generate narrative reports with charts, and distribute to stakeholders on schedule. What used to take your team days happens in seconds.
- Approval workflows — Purchase requests, vendor approvals, expense reports — routed to the right person based on amount, category, and department rules. Escalation logic built in.
- Data reconciliation — Cross-system data matching between your ERP, CRM, accounting, and operations tools. The AI flags discrepancies and proposes corrections.
- Vendor and supplier management — Automated RFQ processing, contract extraction, compliance checking, and renewal tracking.
- Customer operations — Onboarding workflows, support ticket routing, SLA monitoring, and proactive outreach triggers.
- Compliance and audit prep — Continuous monitoring against your policy rules, automatic evidence collection, and audit-ready report generation.
Why mid-market teams choose us over enterprise vendors
| Factor | DK Studio | Enterprise RPA |
|---|---|---|
| Time to first automation | 1-3 weeks | 3-6 months |
| Upfront cost | Fixed project fee (thousands) | Implementation + licensing (six figures) |
| Annual cost | Hosting only | License renewal (six figures) |
| Specialist staff needed | None | 1-2 RPA developers |
| Handles unstructured data | Yes — AI reads emails, docs, images | Limited — needs structured input |
| Makes decisions | Yes — AI reasoning with your rules | No — follows scripts |
| Code ownership | You own everything | Vendor platform lock-in |
| Vendor lock-in | None — take the code anywhere | High — migration is painful |
For a detailed side-by-side, read our full DK Studio vs UiPath comparison. For a broader look at how AI agents differ from traditional RPA, see AI agents vs RPA.
How it works
- Scoping call (free, 30 minutes) — You bring your most painful operations process. We map it, identify where AI adds the most value, and tell you honestly what's automatable and what isn't.
- Fixed-price quote — No hourly billing. No scope creep. You know the cost before we start. Read our full pricing guide for details.
- Build and deploy (1-4 weeks) — We design, build, test, and deploy. You see progress weekly. We don't disappear for months and come back with a demo.
- Handoff — You own the code, the documentation, and the deployment. We train your team to use it. No lock-in — you can maintain it yourself or hire anyone to extend it.
The ROI math
Mid-market operations teams typically find that automation pays for itself within 1-3 months:
- Time recovery — If your team spends 40 hours/week on processes we automate, and your average loaded cost is €50/hour, that's €8,000/month in recovered capacity. The automation pays for itself fast.
- Error reduction — Manual data entry has a 1-4% error rate. AI agents have near-zero error rates on structured tasks. For financial operations, that error reduction alone can justify the investment.
- Speed — Processes that took days happen in minutes. Reports that took a team member a full day to compile are generated automatically before the morning standup.
Not sure where to start?
That's normal. Most operations leaders know they need automation but aren't sure which processes to prioritize. Our scoping call is specifically designed for this — we help you identify the 2-3 highest-ROI automation opportunities based on time spent, error rates, and complexity.
If you want to understand the broader landscape first, read our guide on whether to build or buy AI automation or our overview of what agentic workflows actually are.