Accepting new projects
YefrixLab is an AI-native studio: one senior engineer orchestrating a fleet of AI agents, with the output of a full team and none of the overhead. Platforms, LLM products, audits, rescues. Scoped honestly, built properly, deployed and monitored.
$ yefrixlab new --idea "your product"
→ scoping honest estimate........... done (1 day)
→ architecture + data model......... done
→ build, tests, CI/CD............... done
→ deploy + TLS + monitoring......... done
$ curl https://your-product.live/healthz
{"status":"ok","weeks_elapsed":4}
What we do
Every service exists because something in the standard way of buying software is broken. Pick the failure mode you are living through.
“Agencies quote 6 months and a "team of 8" for what is honestly a 6-week build.”
Full-stack web platforms and SaaS: multi-tenant from day one, real auth, real data models, deployed and monitored. Scoped in features, not in bodies.
“Everyone has an "AI strategy" deck. Almost nobody has AI running in production.”
LLM features that survive contact with real users: gateways with failover, structured outputs, evaluation, cost tiering. Built on existing models, not hype.
“Your runway burns while the roadmap discusses itself in sprint refinement.”
Idea to production-grade MVP in 2-6 weeks. Not a throwaway prototype: the same codebase grows into the real product.
“You inherited a codebase and nobody can tell you if it is safe to build on.”
Architecture reviews, OWASP Top 10 sweeps, dependency and secrets hygiene, performance profiling. A written report with fixes ranked by risk, not a scare-memo.
“Your cloud bill grew 40% while your deploy process is still "Dave does it".”
Docker, CI/CD, reverse proxies, TLS, monitoring, alerting, backups. Cloud when it earns its keep, bare metal when it does not.
“The previous developer vanished. The code has no tests, no docs, and a Friday deadline.”
Stabilize, document, test, then improve. Abandoned projects adopted, legacy tamed, releases unblocked.
Selected work
Not mockups. Every case below is deployed, monitored, and doing its job in production.
Multi-tenant budgeting and forecasting platform with bank statement ingestion and AI-powered transaction categorization.
OpenAI-compatible LLM gateway with automatic failover across six providers, per-route model tiering and full observability.
Self-hosted auto-accountant for Polish JDG: invoices in, tax declarations out, with rules-as-data and tiered LLM processing.
Why it works
The old math said quality software needs a PM, two devs, a QA and three months of ceremonies. AI broke that math. We rebuilt the workflow around it.
Agents write, a senior reviews
AI agents generate code, tests and docs in parallel. Every line still passes through one accountable senior engineer. Speed without the slop.
Production standards by default
Typed code, migrations, CI, containerized deploys, TLS, monitoring, backups. Not "phase 2". Default.
Bugs become tests
Every bug found gets a failing regression test before the fix. The same mistake cannot ship twice.
You talk to the person building it
No account managers translating your words into tickets. Direct line to the engineer, decisions in hours.
15+
production systems shipped and running
2-6
weeks from idea to deployed MVP
99.9%
uptime across the self-hosted fleet
24h
to a straight answer on your project
Tell me what you are building, what is blocking it, and when you need it live. You will get an honest answer about scope, cost, and timeline within 24 hours. No discovery-call theater.