Proof
Proof, in one place
Everything a team evaluating Simas Razinskas needs on one page: twelve case studies, public code, concrete service scopes and a one-page brief you can forward.
Deciding whether to book a call usually comes down to one question: has this person built the kind of system we need? This page is the shortest path to that answer — case studies, public code, and a brief you can forward to whoever else is deciding.
production case studies
AI systems, job queues, deployment infrastructure, media pipelines, SaaS isolation and automation.
years writing code
Senior engineering judgement across backend, frontend, infrastructure and applied AI.
bilingual delivery
Remote or in Vilnius, with working fluency in both English and Lithuanian contexts.
engineering in the open
Public code and commit history back the anonymized private-system case studies.
Representative case studies
Client names stay private, so each system is described by what it does: the constraint, the design, and how it behaves when things fail.
Zero-downtime blue-green deploys with health-gated rollback
Only a tested image tag can be promoted, traffic moves after health passes, and a failed release rolls back before users see it.
Docker Compose · Traefik · Postgres · shell orchestrationAn agent-operated task engine
Agents can claim, heartbeat, complete, fail, and escalate work safely while humans watch the same board update in real time.
Drizzle · Postgres LISTEN/NOTIFY · SSE · contract-first APIIdempotent webhook ingestion at scale
Data-loss risk moved from a quarterly investigation to continuous checks that detect gaps, repair them, and expose operational health.
Go · Postgres (SKIP LOCKED, matviews) · HMAC · advisory locksFrame-accurate video localization
Long clips stay locked to source timestamps while the original non-vocal audio survives beneath the synthesized dub.
WhisperX · XTTS voice cloning · Demucs · FFmpeg · CTranslate2
What the work looks like
Four concrete engagements: diagnose the workflow, harden the prototype, design the agent operating model, or steady the system already in motion.
AI automation audit
A workflow map, a risk list, an integration plan, and a first implementation slice small enough to start next week.
LLM productionization sprint
A typed service boundary, a queue and retry plan, cost controls, fallbacks, and a deployment path.
Agent workflow design
A state model, a claim-and-lease protocol, a review loop, a failure policy, and an execution trail you can audit.
AI project rescue
Stability triage, a performance and cost profile, fixes in priority order, and a simpler architecture to operate.
Where the work lands
The strongest fit is where AI behavior, backend reliability, internal operations and deployment constraints meet.
LLM media-localization pipelines
End-to-end translation and adaptation of video, audio and image content — transcription, machine translation, voice synthesis and on-image text replacement, wired together to run at scale.
Multi-service automation platforms
Monorepos stitching dashboards, queues, APIs and third-party integrations into the daily operational workflow of marketing and ops teams.
Agentic AI tooling & assistants
Retrieval-augmented helpdesk assistants, automated ticket triage and internal copilots — LLMs put to work against real business data and processes.
Browser & design-tool plugins
Figma plugins and Adobe scripting for design automation, plus Chrome extensions that fold internal tooling directly into the browser.
A brief you can forward
One generated PDF page — fit, case studies, engagement shape and the booking path — for whoever else needs convincing.
Download the one-page briefThe public record
Code, commit history and a decade of shipped work — verifiable without taking my word for it.
Proof
Case studies before claims — every service links to a system that shipped.
The engineering is public even where the clients can't be.
One page per service, so scope is visible before the first call.
A one-page brief you can forward, generated from this site's content.