Kodesage
Startup building an AI platform to document, analyse, convert and support mission-critical legacy systems.
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Podcast Episode
🎙️ Deep Dive
Semble, Innovorder, Kodesage — operational AI for healthcare, restaurants and legacy software — Daily News June 4, 2026
Listen to the episodeAbout Kodesage
Kodesage develops an on-premise AI platform for legacy software modernisation. The solution analyses source code and documentation, creates a continuously updated knowledge layer, generates documentation, supports code conversion, test creation and AI-assisted production support. It focuses on regulated sectors such as banking, insurance, energy, transportation, telecommunications and the public sector, where decades-old systems still run essential operations. The platform targets regulated enterprises in banking, insurance, energy, transportation, telecommunications and the public sector, competing with players such as CAST Software, IBM and Micro Focus/OpenText in legacy modernisation. The $6.6M seed round, led by VentureFriends, funds product development.
The Story
Founded in 2024 by Gergely Dombi, Miklos Szurdi and Gyorgy Szilagyi.
How Kodesage works
Business Model
B2B enterprise AI platform for software modernisation, sold to large regulated organisations.
Revenue Model
Not verified; likely enterprise subscription, on-premise licensing or deployment-based pricing.
Products & Services
Key Products
- On-premise AI legacy modernisation platform
- Legacy code knowledge layer
- AI-assisted code conversion
- Documentation generation
- Test creation tools
- AI-assisted production support
Core Use Cases
- Legacy software discovery
- Codebase documentation
- Code conversion
- Test generation
- Production support
- Application modernisation
- Knowledge retention
Market & Clients
Key Customers
Regulated enterprises in banking, insurance, energy, transportation, telecommunications and the public sector.
Geographic Presence
How Kodesage competes
Competitors
Competitive Advantages
- On-premise and air-gapped deployment
- Support for legacy and modern stacks
- Focus on regulated industries
- Continuously updated knowledge layer
- AI-assisted production support
How Kodesage grows
Growth Strategy
Expand go-to-market across the US and Europe while investing in product development and engineering.
Distribution Model
Enterprise sales to regulated organisations and mission-critical software owners.
Moat (Defensibility)
Legacy system analysis know-how, code/documentation knowledge graph, regulated-industry deployment model and support for old technology stacks.
Regulatory Context
Relevant to data residency, source-code confidentiality, regulated infrastructure, banking/insurance compliance and public-sector IT governance.
Key Risks
- Complex enterprise deployments
- Need to prove accuracy in mission-critical environments
- Long sales cycles
- Competition from incumbents and consultancies
- Liability risk in automated code conversion
Strategic Insights
- Legacy modernisation is a problem of institutional knowledge before it is a coding problem.
- In regulated industries, AI must run in controlled, on-premise or air-gapped environments.
- The next frontier of developer tools is not only writing new code, but understanding and migrating old code.
Funding & Investors
Funding Rounds
- 2026 - Seed: $6.6M
Lead: VentureFriends
Key Investors
Founding Team
Founders
Key Executives
- Gergely Dombi - CEO
Key Metrics
Lessons from Kodesage
- Look for mission-critical systems where operational risk prevents rapid modernisation.
- Compliance can be an advantage if you design on-premise deployment and data residency by default.
- The most useful enterprise AI often works on a company's past, not only its future.
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