Client website
Optik Dvořák
Website for a family-run optician in Pilsen, eye exams, designer frames, offers and contact.
Projects
Selected projects from recent years, three different industries, one principle: I build automation as infrastructure, not marketing slides. Numbers shown are illustrative; they convey scale and impact, not exact operational statistics.
Real projects & websites
🔒 Client website
Richard Topinka
Portfolio for a fine-art and portrait photographer from Pilsen. Themed galleries with a focus on atmosphere.
🔒 Client website
Autoservis Topinka
Website for a car repair shop in Pilsen, services, inspections, pricing, booking and contact.
Side project
Lynx Studio
Creative studio for startups and brands, digital experiences that connect and perform.
Side project
Synthetix
Landing page for AI automation and integrations, from hero to call to action.
Side project
Vrstva
Studio for tech brands, strategy, design and development on one site.
Side project
Synapse
Studio for UI/UX, branding, illustration and web, a portfolio presentation.
🔒 Client demo
Fencl Video
A clickable prototype of an AI tool for scoring marketing videos, verdict, weak-spot heatmap and top 3 fixes within two minutes.
🔒 Pitch · password
Ippa Caffe pitch
A pitch website for the Ippa café in three languages (CZ / EN / DE). Client demo, password protected.
···
In progress
Synx
A side project in development. Details coming soon.
Launching soon →
Sample case studies
Invoicing automation
A global logistics company processed international invoicing by hand: a team of four re-typed data between the TMS, the customs database and accounting. Every shipment waited on paperwork, 48 hours on average.
Starting point
- 4 full-time employees just re-typing data between three systems
- ~3% manual re-typing error rate, every error meant a customs delay
- Invoicing capped growth: more shipments = more people
Solution
I built event-driven orchestration on custom middleware: every event in the TMS (loading, border crossing, delivery) automatically triggers data validation, customs document generation and posting to accounting. It connects to the existing systems via API, so the company didn't have to change software. People handle only the exceptions the pipeline flags for manual review.
- Connected to the existing TMS and accounting system via API, no software replacement
- A validation layer with rules for 14 countries
- An exceptions dashboard, the team sees only cases that need a decision
Solution preview
#SH-88214Prague → HamburgProcessed · 9 min
#SH-88215Brno → ViennaProcessed · 12 min
#SH-88216Ostrava → KatowiceIn progress · validation
#SH-88217Prague → RotterdamException → manual review
Today: 0 shipments⌀ processing: 11 min● pipeline running
Pipeline monitoring dashboard preview (illustrative data).
Result
48 h → 11 minshipment processing time
−97%documentation error rate
3.2 monthsreturn on investment
Internal AI assistant
A bank's internal helpdesk received over 900 queries a day, from password resets to interpreting internal policies. Twelve operators dug through thousands of pages of documentation for answers. Public AI tools were unusable due to regulation.
Starting point
- Average response time of 4.5 hours, with daytime peaks
- Strict requirements: no data may leave the bank's infrastructure
- Knowledge scattered across directives, wikis and e-mail threads
Solution
I deployed a stateful conversational agent on RAG architecture, running entirely in the bank's private cloud. It was trained exclusively on internal documentation; it backs answers with source citations and hands complex cases to humans with the full conversation context.
- A private vector database, APIs with no data retention
- Every answer linked to its source directive, auditability
- Escalation protocol: uncertainty → handover to an operator, never a guess
Solution preview
What's the limit for instant payments on business accounts?
The instant payment limit for business accounts is CZK 2,500,000 per transaction. Payments above this limit automatically fall back to standard processing.Source: Directive PL-2024/07 · art. 4 par. 2
And who can raise the limit for a client?
Limit increases are approved by the risk department at the request of the client's banker. The request form is in the system under RM-07. Shall I hand this over to an operator?Source: Directive RM-2023/11 · art. 7
⌀ response: 40 s78% without escalation● data never leaves the bank
Internal agent conversation preview (illustrative data).
Result
78%of queries resolved without an operator
4.5 h → 40 smedian response time
0data leak incidents
Customer churn prediction
A fleet-management SaaS platform was losing customers quietly: when a client stopped using the product, the team found out only from the cancellation notice. Customer success reacted late and indiscriminately.
Starting point
- Monthly churn of 4.1%, growing with the customer base
- Churn signals sat in telemetry nobody evaluated
- Customer success called customers blindly
Solution
I designed predictive middleware that reads product telemetry in real time, scores each account's churn risk and triggers graduated interventions on its own: from a personalized onboarding e-mail to a task for the account manager with a precise description of what's happening with the client.
- Connected to product telemetry, CRM and e-mailing via API
- A risk model retrained weekly on fresh data
- Interventions escalate by score, automation handles light cases, people the critical ones
Solution preview
Fleetio Trans
18
stable, no action
Logimax s.r.o.
54
→ onboarding e-mail sent
TransCargo CZ
87
→ task for the account manager
Detection lead time: 0 daysMonitored: 0 accounts● model retrained 2 days ago
Churn risk dashboard preview (illustrative data).
Result
−31%customer churn per quarter
9 daysaverage risk detection lead time
5×higher retention campaign reach
Dealing with something similar? Write to me, I'll gladly look at your case and tell you whether and how it can be automated.
Get in touch