Kodesage offers an AI‑driven platform that continuously ingests an enterprise’s source code, documentation, databases, and ticketing systems to build a real‑time knowledge base of legacy applications.
Funding
$9.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
AICSMGPPCFounders
Product
Problem
Enterprises with long‑standing legacy applications face undocumented code, missing tests, complex dependencies, and fragmented knowledge spread across tickets, databases, and sparse documentation, making maintenance, onboarding, and modernization slow, risky, and costly.
Solution
Kodesage provides an AI‑driven platform that ingests a project’s source code, documentation, databases, and issue‑tracking systems to create a unified, up‑to‑date knowledge base. Users can ask natural‑language questions about system behavior, code details, or architecture and receive concise answers backed by the latest repository state. The platform automatically generates visual dependency diagrams, highlights downstream impacts of changes, and suggests fixes directly within ticketing tools. By surfacing hidden relationships and codifying tribal knowledge, Kodesage reduces developer ramp‑up time, accelerates ticket resolution, and enables business analysts and product managers to assess feature impacts without deep technical expertise.
Target Audience
Primary customers are enterprise software engineering teams, QA groups, and product/analysis teams responsible for maintaining and modernizing legacy applications in regulated or security‑sensitive environments.
Features
- Continuous ingestion of code repositories, documentation, databases, and ticketing systems to keep the LLM’s context current
- Natural‑language query interface that returns precise code snippets, design explanations, and execution flow details
- Automated generation of interactive system and dependency diagrams for complex legacy architectures
- Ticket integration that surfaces AI‑generated fix suggestions and impact analyses directly in issue trackers
- Role‑based views that tailor outputs for developers, QA engineers, business analysts, and product managers
- On‑premise deployment option to meet security and compliance requirements of enterprise environments