Software engineers who ship — and an AI practice that ships with them

We develop custom software end to end: customer portals, SaaS platforms, marketplaces and e-commerce, mobile apps for iOS and Android, integrations with CRM/ERP/payment systems, and high-load back ends that keep working at peak. Our AI team works inside the same delivery process: forecasting and scoring models, computer vision, document understanding, LLM pipelines with retrieval, and AI agents that act inside real workflows. We also build our own AI products — a proving ground where every idea is tested on live users before it is offered to a client.

A senior-only engineering team. Every engineer at Glanit has shipped production systems for years before joining, talks to the client directly and owns their part of the product from architecture to support. No layers of account managers, no junior bench billed as seniors. That is why a small team gets 500+ projects to acceptance: fewer people, more responsibility, less rework.

Discovery first: we map the process, its numbers and its risks before writing a line of code. Then a pilot or MVP on a narrow slice, so the decision to invest is made on evidence. Delivery in short increments you can use, with tests, CI/CD and monitoring from day one. After launch we stay — support, improvements and model updates under an SLA that fits the product.

Numbers over adjectives: a case study is context, problem, what we built and the before/after delta. Human review over autopilot: generated output ships only after a person has signed off. Boring reliability over demos: production systems need monitoring, fallbacks and clear ownership. And the right tool over the fashionable one — AI where it moves the numbers, plain code where that is enough.