AI-native development
Software development is becoming a decision-making discipline. AI handles increasing amounts of design, implementation, and validation. The role of senior engineers shifts from writing code to orchestrating what gets built, in what order, and to what standard. We've built a methodology around that shift.
How we work?
Once the agentic workflow is running, the compounding effect begins. Every cycle improves the AI's ability to operate within your specific environment. Realistically, this translates to 25–40% improvement in feature throughput, time to market, or cost, depending on where your bottleneck sits. The efficiency compounds over time. That's the structural advantage of this model.
The 20% of decisions that drives 80% of results
Orchestration over implementation — Senior engineers define architecture, quality gates, and priorities. AI agents handle the volume. Human judgment stays where it has the most leverage.
Compounding, not linear — Each cycle teaches the agentic workflow more about your codebase, your standards, and your patterns. Output quality and speed improve the longer we work together.
Full transparency on what AI touches — You see what the agents produce, how it's validated, and where humans intervene. No black boxes. The methodology is auditable by design.
Agentic software delivery
End-to-end feature development where AI agents handle implementation under senior supervision. From ticket to tested code, with human decisions at every critical gate.
AI workflow design
We design the agentic workflows themselves: which tasks to automate, how to validate output, and where human oversight adds the most value. Built around your codebase and your quality standards.
Codebase onboarding and acceleration
We connect agentic tooling to your existing repositories, conventions, and CI/CD pipelines. The AI learns your environment so output matches your standards from the start.
Legacy modernization with AI
Refactoring, migration, and modernization projects where AI handles the volume of repetitive transformation and senior engineers manage the architectural decisions.
Testing and validation automation
AI-driven test generation, coverage analysis, and regression detection. The goal is faster feedback loops without sacrificing confidence in what ships.
Technical leadership and methodology transfer
Not every team wants a permanent external presence. We set up the agentic methodology, train your team to operate it, and step back. The compounding effect stays with you.
References
Solutions that speak for themselves - explore our client success stories.
Valio
Valio explores the potential of AI in its business and develops solutions in collaboration with Pareto. The partnership includes both long-term development projects and agile experiments.
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Finlandia Group
Finlandia Group, a wealth management company, had a client reporting portal that no longer met their needs in terms of user experience and appearance.
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Cyberismo
Cyberismo is developing a new way to manage information security and has created an open-source solution that makes security management in software development easier and more efficient.
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