- Support cost
- -90%
- Bookings
- +25%
- Capacity
- 600%
- Time
- 13,000h
reduction in documented automation cases.
lift in qualified lead workflows.
gain in highly repeatable task structures.
recovered through better knowledge access.
Many of the underlying implementations ran on US-cloud stacks. RakenAI transfers the operating logic into a privacy-first architecture.
Results only become useful when they can be translated into your own reality.
Customer Support
-90% support cost, 94% autonomous. How structured conversation systems absorb support load while making answers more consistent.
Open case studyLead Generation
+25% bookings. How AI improves first response, qualification, and follow-up where high-intent demand needs faster handling.
Open case studyDocument Processing
40h to 0. How repetitive document work, extraction, and review can be turned into stable operational flows.
Open case studyKnowledge Management (RAG)
13,000h recovered. How teams access distributed knowledge faster and therefore shorten decisions and execution time.
Open case studyVoice AI
500k calls automated. How phone load, wait times, and standard conversations are restructured so humans step in only where it matters.
Open case study
Case studies are not decorative social proof.
- 01
Process class
What kind of work pattern or communication load was automated?
- 02
Economics
Which metric proves that the intervention mattered commercially?
- 03
Transferability
Can the same pattern be rebuilt cleanly inside privacy-first infrastructure and your context?
Once the proof is strong enough, what remains is the right priority.
That is exactly what audit is for, before interest turns into a concrete systems decision.