Skene raises €800K to tackle $113B SaaS waste problem
Helsinki-based startup Skene has secured a €800,000 pre-seed round led by Finnish venture fund Superhero Capital, aiming to combat what it describes as a $113 billion SaaS waste problem. The company is building AI agents that can read software source code and guide users directly inside the tools they already use, with the goal of automating SaaS adoption and improving user retention.
AI agents that understand source code and user behavior
Skene is developing intelligent AI agents that plug into existing software products to help users understand features, workflows, and best practices without leaving the application. Unlike traditional onboarding tours, static documentation, or video tutorials, these agents are designed to interpret the underlying codebase and dynamically adapt to changes in the product.
By reading and mapping the source code, the agents can identify how different features are wired, what data they touch, and how they are intended to be used. This technical understanding is combined with real-time user behavior analytics to offer contextual guidance, such as:
- Step-by-step walkthroughs tailored to a user’s role and previous actions
- In-product answers to “how do I do X” questions
- Proactive prompts when users appear stuck or confused
- Automated discovery of underused or hidden features
The company positions this as a new layer of product-led growth, where AI agents act as an always-on, deeply technical customer success function embedded inside every screen.
Targeting a massive and growing SaaS waste market
Global enterprises spend hundreds of billions of dollars annually on SaaS subscriptions, yet a significant portion of that investment is underutilized or completely unused. Industry estimates often refer to this as SaaS waste, covering everything from abandoned licenses and overlapping tools to features that customers never adopt.
Skene cites a $113 billion SaaS waste figure as the core market inefficiency it wants to address. The startup argues that most of this waste stems from weak onboarding, poor feature discovery, and the difficulty of driving deep adoption in complex products. Traditional solutions—like manuals, help centers, and one-off training sessions—struggle to keep up with rapidly evolving software.
By embedding AI agents directly into products, Skene aims to ensure that customers actually realize the value they are paying for. For software vendors, this translates into higher net revenue retention, reduced churn, and more effective upsell and cross-sell opportunities.
Superhero Capital leads pre-seed investment
The €800,000 pre-seed round is led by Helsinki-based venture capital firm Superhero Capital, known for backing early-stage technology companies in the Nordics and Baltics. The participation of a specialist early-stage investor is a vote of confidence in Skene‘s technical approach and its focus on the intersection of AI, developer tooling, and SaaS optimization.
With the fresh capital, Skene plans to expand its engineering team, deepen its AI models for code understanding, and run pilots with early design partners in both B2B and developer-focused SaaS categories. The company is also expected to invest in integrations with popular software development and product analytics platforms to make deployment easier for engineering teams.
How Skene’s technology works in practice
Code-aware onboarding and guidance
At the core of Skene‘s platform is a set of AI algorithms trained to analyze and interpret complex software architectures. By ingesting a product’s source code, configuration files, and API definitions, the system builds a semantic map of features, dependencies, and user-facing flows.
This map allows the AI agents to:
- Identify which parts of the interface correspond to which modules or services
- Understand how actions in one part of the app affect data or behavior elsewhere
- Automatically update guidance when the codebase changes, reducing manual documentation work
For end users, this translates into contextual assistance that is technically accurate and always up to date. For product teams, it means less time spent writing and maintaining onboarding scripts and more time focusing on core features.
Automating adoption and retention for SaaS vendors
Beyond onboarding, Skene wants to be a long-term driver of user retention. By continuously monitoring feature usage and engagement patterns, its AI agents can identify customers that are at risk of churn because they are not adopting key workflows or advanced capabilities.
Instead of waiting for human customer success teams to step in, the system can trigger automated, in-app interventions—such as personalized walkthroughs, tips, or prompts—that nudge users toward higher-value behaviors. This blend of AI-driven personalization and code-level understanding is pitched as a more scalable alternative to traditional, labor-intensive retention strategies.
Positioning within the AI and SaaS ecosystem
Skene enters a crowded landscape of digital adoption platforms, product analytics tools, and AI copilots. Its differentiation lies in treating the source code as a primary data source, rather than relying solely on front-end event tracking or manual configuration.
This code-centric approach aligns with broader trends in developer experience and AI-assisted software development, where tools increasingly understand and manipulate code directly. By extending this paradigm to end-user guidance and SaaS optimization, Skene is betting that the next generation of product-led growth tools will be deeply technical under the hood.
As enterprises continue to rationalize their SaaS spending and demand measurable returns on software investments, solutions that can demonstrably reduce waste are likely to attract attention from both vendors and investors. With its new funding round, Skene is positioning itself as one of the Nordic contenders in this emerging category of AI-powered adoption infrastructure.
What comes next for Skene
Following the pre-seed raise, Skene is expected to focus on validating its technology with early customers and refining its go-to-market strategy. Key milestones will likely include:
- Successful pilots demonstrating reduced SaaS churn and increased feature adoption
- Deeper integrations with popular SaaS platforms and developer tools
- Scaling its AI infrastructure to handle larger and more complex codebases
If the company can prove that its AI agents materially cut SaaS waste while reducing the burden on product and customer success teams, it will be well positioned for a larger seed or Series A round as demand for intelligent adoption tools continues to grow.
For now, the €800,000 pre-seed investment led by Superhero Capital gives the Helsinki startup the runway to build out its vision of code-aware, in-product guidance as a new standard for SaaS efficiency.