CoreLine
SLOs and Error Budgets
A practical SLO and error budget playbook to turn reliability into ROI for enterprise web and mobile products.
Blog posts
CoreLine
Enterprise Application Readiness Roadmap
A staged checklist of enterprise-ready features—identity, auditability, governance, reliability—to take your application from MVP to enterprise scale.
CoreLine
Enterprise SSO and User Provisioning Playbook
A staged roadmap to add SAML SSO and SCIM provisioning to your MVP—architecture, timelines, pitfalls, and build vs buy choices.
CoreLine
Future-Proofing Your SaaS Product: Strategies for Continuous Improvement
Explore strategies for ongoing optimization of your SaaS product to meet evolving market demands.
CoreLine
Designing for Scalability and User Satisfaction
Explore strategies for designing scalable B2B SaaS products that prioritize user satisfaction.
CoreLine
Maximizing ROI with Data-Driven Product Development Strategies
Explore how data-driven strategies can enhance product development and maximize ROI for B2B tech companies.
CoreLine
Strategies for Effective MVP Development
Discover advanced MVP development strategies for B2B SaaS products to drive success and reduce risks.
Valentina Moguš
Thriving on Trust: A PM's Guide to Growth and Quality
Learn how our boutique IT agency thrived over the past seven years through trust, quality, and teamwork. From design discovery to QA, discover how strong communication and collaboration drive successful projects and client satisfaction
Filip Škrlec
A guide to class validation in NestJS
To maintain the integrity of the data and always get the reliable inputs to a NestJS app, the class validation should be used and this blog post provides the reader with examples that are intuitive and easy to understand.
Lovro Buday
Using Sentence Embeddings to search for semantically similar sentences
Sentence embeddings are a way to represent sentences in vector space, allowing them to be compared like vectors and letting us derive similarity scores between them. This blog post goes over how those similarity scores are calculated and how sentence embedding first came into being.
Our services
Work with us
Got a project?