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TrioAmigo

TrioAmigo is a team of three senior engineers and long-time colleagues, each with 8–10+ years of production experience, based in Belgrade (Serbia) and East Sarajevo (Bosnia and Herzegovina). We help founders and engineering leaders build new products, add AI to existing ones or strengthen in-house teams, mostly with .NET, React and AWS. Between us, we've shipped 50+ projects across web, cloud and enterprise software. What we build: full-stack web platforms and REST APIs (React, Next.js, Angular, TypeScript, .NET/C#, Node.js, Python); cloud-native and serverless systems on AWS (Lambda, SQS, S3, ECS Fargate, Step Functions) with Docker and CI/CD; applied AI with LLM features on Amazon Bedrock and RAG architecture; multi-tenant SaaS with OAuth2/OIDC; and modernization of legacy .NET Framework and Angular apps. Recent work: an enterprise inspection platform (~24 services, multi-tenant, large-scale imagery) used by a global energy company across its wind-turbine fleet, led by our architect for 6+ years; a gigapixel image pipeline rewritten from .NET to Python/libvips, benchmarked 16–20× faster on real inspection data; a serverless AI video translation and dubbing pipeline and a conversational no-code app builder on Amazon Bedrock, both in production at clients. Why a team instead of individual hires: a principal architect, a backend/cloud engineer and a full-stack engineer who already share standards and tooling. No recruiting, no long onboarding, no single point of failure, and one contract for the whole team. We prefer fixed-price milestones with a clear scope, with written design docs, a weekly demo and peer review on every pull request. Our CET/CEST hours give a full workday of overlap with the UK and EU and 2–3 hours with US Eastern. Tell us what you're building and we'll reply with an approach, milestones and an estimate.

About this company

Projects

Gigapixel Image Pipeline Rebuild (.NET → Python/libvips)

Miljan Sikimić

Drone-inspection imagery pipeline: a legacy .NET worker re-implemented as Python 3.12 services on AWS (SQS, Lambda, ECS Fargate, S3) using OpenCV and libvips, verified against the legacy output. Measured on real inspection data: 16–20× faster tile generation on the same machine, ~10× faster per blade on AWS (17–31 s vs 281–737 s), ~10× less CPU time and task memory down from 30 GB to 8 GB. 800+ automated tests.

Cloud ComputingPythonMongoDB.NET

Multi-Tenant Inspection Platform on AWS

Miljan Sikimić

Event-driven .NET platform on AWS used by a global energy company: about 24 services and thousands of high-resolution images per inspection. ASP.NET Core REST APIs with multi-tenancy, role-based access and OAuth2/OIDC single sign-on; ECS Fargate workers for PDF reports and deep-zoom tiles; SQS queues and Lambda for archiving and retention; SQL Server, MongoDB, Elasticsearch and S3; React/TypeScript and Angular web apps; Docker and multi-environment CI/CD. Led by our architect for 6+ years.

Cloud ComputingTypeScriptReactAngular

Asynchronous PDF Reporting Pipeline

Miljan Sikimić

.NET worker services on AWS that turn inspection data and high-resolution imagery into large PDF reports without blocking the web app. The ASP.NET Core API queues a job in SQS, an ECS Fargate worker renders the PDF and stores it in S3, and the user gets an email when it is ready. A scheduled Lambda and SQS-driven jobs archive and clean up binary assets according to retention rules.

Cloud Computing.NET

Industrial Image Search Platform: React UI & Serverless Video

Miljan Sikimić

Platform for searching and analyzing millions of inspection images on serverless AWS. My part: React features (virtualized thumbnail grid, bulk metadata editing, linked search filters, user and group admin, ML prediction overlays) and the serverless video pipeline: S3 and EventBridge start a Step Functions workflow, FFmpeg and MediaConvert produce animated previews and DASH streams, and a Lambda API signs every segment URL.

Web DevelopmentTypeScriptPythonReact