AI-driven Scriptum: The future of document and workflow automation by 2026
AI-driven Scriptum is set to transform document management and workflow automation by 2026, accelerating document processing and business process automation.
Custom software development for enterprise — from MVP to production-ready platforms. With architectural discipline instead of fast hacks, and business value over feature factory.
Software development is not "hire 10 developers for 3 months". It is an engineering discipline with its own methodology: domain-driven design, architectural decisions (monolith vs. microservices), TDD/CI/CD, code review as a mandatory part of the process.
In 2026 the key advantage is not delivery speed, but long-term quality: whether the project remains maintainable in 2 years, or becomes legacy that is "easier to rewrite than support".
The first year of a feature factory gives an illusion of speed. In year two, the team spends 60% of time on refactoring and fixes. This is not a bug, it is a pattern — without architectural reviews, codebase degrades linearly with time.
Microservices pay off for teams of 50+ developers with own DevOps. For teams of 5–10, it is overengineering that doubles complexity without benefits.
A team where code review is a formality ("LGTM") becomes n separate experts in a year, none of whom understands the others' code. Bus factor = 1 per component. This is a first-order organizational risk.
It is more honest to say "you do not need this yet" than to sell an engagement that will not deliver ROI.
Interviews with process owners, event-storming for bounded contexts, risk assessment. Output: domain model and architectural decision records (ADR).
Monolith vs. microservices choice, tech stack, API design, data schema, IaC approach.
First version for one use case with real users. Proves technical architecture and business assumptions at production quality.
Phased functionality expansion, performance optimization, adding new features by business value priority.
Regular architectural reviews, refactoring sprints, dependency updates, security audits. Without this, code degrades in 12–18 months.
Project lead: Softengi (custom software, AI/ML systems) and InBase (UnityBase low-code, enterprise platforms).
Brought in when needed: SL Global Service (cloud-native architecture), Data Management IG (data layer design).
Team delivered 50 features in year one. In year two, 30% of time goes to bug-fixing, another 30% to refactoring. Business asks why speed dropped.
What we do instead: mandatory architectural reviews per epic, refactoring as part of sprint capacity (not "later").
A team of 6 developers builds 12 microservices "because it is modern". DevOps overhead exceeds business logic.
What we do instead: we start with a monolith and extract services only when there is evidence-based reason: different scaling profiles, different release cycles, or teams >50 engineers.
Test coverage <10%. Every release is a week of manual QA. After 18 months, no refactoring is possible.
What we do instead: tests as part of definition-of-done (not optional). Target coverage >70% for business logic.
No precise savings percentages — actual numbers depend on the client's starting point. Instead — concrete architectural decisions and organizational changes.
Instead of an off-the-shelf CRM — a custom platform on UnityBase with integration to 14 banking systems. 12 months to production, then continuous evolution.
Business processes on 200+ Excel files. Custom platform with role-based UI, audit trail, ERP integration. 8 months. The hard part — domain knowledge transfer.
Custom API platform for a government registry serving 12 agencies and 200+ external consumers. SLA 99.95%. 14 months.
Nine recent expert articles — from thematic overviews to specific architectural decisions.
Java · Python · .NET · Node.js · Go · PHP (UnityBase)
React · Vue · Angular · Next.js · TypeScript · Svelte
PostgreSQL · MS SQL · MongoDB · Redis · ClickHouse · Elasticsearch
Domain-Driven Design · CQRS · Event Sourcing · API-first · Hexagonal architecture
Docker · Kubernetes · GitLab CI · GitHub Actions · Playwright · Cypress · JUnit · pytest
ISO/IEC 27001 · OWASP · SOLID · 12-factor app · Clean Architecture
Almost always — modular monolith. Microservices pay off only for teams of 50+ with established DevOps culture. For everyone else — overengineering with worse operational profile.
MVP — 3–4 months. Production-ready — 6–12 months. If you are promised "product in 2 months" — it is either a templated solution (then why custom?) or a product debt to be paid later.
Three metrics: (1) lead time from commit to production (target <1 day); (2) deployment frequency (target several times per week); (3) change failure rate (target <15%). These are DORA metrics — the industry standard.
For business logic — yes, mandatory. For UI and scratch prototypes — opt-in. Classic test-first → green → refactor cycle catches 80% of bugs before code review.
An approach to modeling complex business domains via ubiquitous language with business stakeholders and explicit bounded contexts. Pays off for projects >6 months with non-trivial business logic. For simple CRUD — overhead.
Real projects rarely fit in one competency. See which other areas we work in.
30-minute discovery call with an architect. We will discuss your idea, technical risks and realistic expectations.