University Accelerators
University Accelerators Stream · 7 delivery partners
Live across the stream
Programme Evaluations
Oversee evaluations and stage gates across all delivery partners in this stream.
Evaluation stage gates
Seven stage-gate moments across the programme
Intake readiness review
Problem-solution fit review
Customer validation review
Business model review
MVP / product planning review
Funding readiness review
Final progression review
Delivery partner evaluation status
Comparing the 7 delivery partners in this stream
| Delivery partner | Completed | Pending | Overdue | Avg score | Progression | Evidence | Status |
|---|---|---|---|---|---|---|---|
| InQbay — ČVUT (CTU Prague) | 16 | 3 | 0 | 42% | 0 | 47% | Review |
| xPORT VŠE | 14 | 1 | 2 | 52% | 0 | 48% | Review |
| JIC STARCUBE (Brno) | 13 | 2 | 1 | 52% | 0 | 50% | Review |
| BIC — VUT Brno | 11 | 4 | 0 | 55% | 0 | 54% | On track |
| Masaryk University Incubator | 8 | 3 | 3 | 44% | 0 | 40% | Review |
| Point One — ČZU Prague | 10 | 2 | 0 | 49% | 0 | 48% | Review |
| Palacký University Incubator | 10 | 1 | 1 | 43% | 0 | 52% | Review |
Venture evaluations
Every venture in the stream, with score, evidence and recommendation
| Startup | Founder | DP | Sector | Stage gate | Score | Evidence | Recommendation | |
|---|---|---|---|---|---|---|---|---|
| Brno Bio | Tereza Černá | InQbay — ČVUT (CTU Prague) | Deep tech & engineering spin-outs | Problem-solution fit review | 20 | 43% | Re-route | |
| Říp Labs | Matyáš Svoboda | InQbay — ČVUT (CTU Prague) | Deep tech & engineering spin-outs | Customer validation review | 23 | 49% | Re-route | |
| Slovan Health | Eliška Černá | InQbay — ČVUT (CTU Prague) | Deep tech & engineering spin-outs | Customer validation review | 21 | 27% | Re-route | |
| Vega OS | Veronika Kovářová | InQbay — ČVUT (CTU Prague) | Deep tech & engineering spin-outs | Problem-solution fit review | 72 | 83% | Specialist support | |
| Bohemia Nano | Michal Kratochvíl | InQbay — ČVUT (CTU Prague) | Deep tech & engineering spin-outs | Customer validation review | 22 | 39% | Re-route | |
| Brno Mobilita | Jakub Růžička | InQbay — ČVUT (CTU Prague) | Deep tech & engineering spin-outs | Intake readiness review | 56 | 30% | Needs support | |
| Lumen Logic | Natálie Horáková | InQbay — ČVUT (CTU Prague) | Deep tech & engineering spin-outs | Intake readiness review | 34 | 45% | Re-route | |
| Slovan Pay | Barbora Horáková | InQbay — ČVUT (CTU Prague) | Deep tech & engineering spin-outs | Business model review | 69 | 80% | Specialist support | |
| Kometa Logic | Filip Kovář | InQbay — ČVUT (CTU Prague) | Deep tech & engineering spin-outs | Problem-solution fit review | 33 | 54% | Re-route | |
| Šumava Bio | Pavel Kovář | InQbay — ČVUT (CTU Prague) | Deep tech & engineering spin-outs | Problem-solution fit review | 35 | 57% | Re-route | |
| Morava OS | Jan Pokorný | xPORT VŠE | Business & digital ventures | Intake readiness review | 62 | 52% | Needs support | |
| Tatra Bio | Karolína Černá | xPORT VŠE | Business & digital ventures | Problem-solution fit review | 71 | 39% | Specialist support | |
| Berounka Bio | Martin Novák | xPORT VŠE | Business & digital ventures | Problem-solution fit review | 26 | 48% | Re-route | |
| Šumava Logic | Lucie Nováková | xPORT VŠE | Business & digital ventures | Intake readiness review | 57 | 32% | Needs support | |
| Mendel Tech | Matyáš Pospíšil | xPORT VŠE | Business & digital ventures | Problem-solution fit review | 22 | 18% | Re-route |
Evaluation criteria & scoring framework
Weighted criteria applied consistently across all delivery partners
Problem clarity
Clarity, specificity and urgency of the problem.
Customer validation
Evidence of customer demand and pain.
Market opportunity
Size, growth and accessibility of target market.
Solution fit
How well the solution addresses the problem.
Founder capability
Team strength, domain depth and resilience.
Business model strength
Revenue logic, unit economics, repeatability.
Product readiness
MVP maturity and shipping cadence.
Financial assumptions
Credibility of forecasts and funding plan.
Funding readiness
Investor materials, narrative, governance.
Impact potential
Economic, climate or societal contribution.
University Accelerators Evaluation Support
Across the University Accelerators stream, ventures are strongest on problem clarity and weakest on financial assumptions. Two delivery partners have the highest number of ventures requiring rework before funding-readiness review.
Evaluation report to Management Layer
Compile and send a stream evaluation summary to the National Layer
Bertie helps Stream Coordinators manage programme stage gates consistently across delivery partners, while using AI to summarise evidence, identify gaps and recommend the next best intervention for each venture.
