Seerene offers an AI‑driven software intelligence platform that automatically ingests data from code repositories, CI/CD pipelines, issue trackers and test tools to create a unified analytics layer. The platform provides real‑time metrics, predictive risk scores and actionable recommendations on code quality, delivery lead time and team performance, helping CIOs, CTOs and engineering leaders reduce technical debt and improve release efficiency.
Funding
$14M 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.
Founders
Product
Problem
Software development organizations often struggle with fragmented data from disparate tools, making it difficult to obtain a unified view of code quality, delivery speed, and operational costs. This lack of transparency hampers decision‑making, leads to hidden technical debt, and reduces the ability to align engineering output with business goals.
Solution
Seerene delivers an AI‑driven Software Intelligence Platform that consolidates data from code repositories, CI/CD pipelines, issue trackers, test suites, and other development tools into a single analytics layer. The platform applies machine‑learning models to identify defect hotspots, knowledge silos, and low‑value code, turning raw telemetry into actionable recommendations. Executives and engineering leaders can monitor real‑time efficiency metrics, benchmark teams, and prioritize improvements without manual data wrangling. By surfacing these insights, Seerene enables faster releases, higher code quality, and measurable cost reductions across heterogeneous technology stacks and development methodologies.
Target Audience
The primary customers are CIOs, CTOs, VP of Engineering, and software development managers in large enterprises that operate complex, multi‑language codebases and need enterprise‑wide visibility into development efficiency.
Features
- Automated ingestion of data from hundreds of development tools (Git, SVN, Jenkins, Azure DevOps, Jira, SonarQube, etc.) via native connectors and APIs
- AI‑powered analytics that surface defect risk, code churn, knowledge monopoly, and unused code across any programming language (Java, C++, .NET, SAP ABAP, Python, JavaScript, Swift, COBOL, etc.)
- Interactive dashboards with drill‑down visualizations of delivery lead time, quality gates, and team performance against industry benchmarks
- Predictive risk scoring for release candidates, highlighting hotspots before deployment
- Cross‑team best‑practice propagation by identifying “lighthouse” teams and recommending process improvements
- Support for both agile, waterfall, and hybrid workflows, including sprint velocity and backlog health metrics
- Scalable architecture that handles single‑developer projects to enterprise‑wide portfolios with billions of lines of code
- Role‑based access and integration with enterprise SSO for secure, governance‑compliant reporting