Services

What we build.

Every engagement starts with your problem, not a pre-packaged solution. Here's where we create the most value.

Computer Vision & Image Detection

See what humans miss

We build systems that automate visual inspection -- not toy demos, but production pipelines processing thousands of images with real accuracy requirements.

Case Study

Aris Detect

Production SaaS · Drone-based inspection

A full property inspection platform processing drone imagery with ML-powered damage detection. Real inspectors depend on it daily across Australia.

Detection

Custom YOLO models

Inference

RunPod + AWS Lambda

Collaboration

Real-time multi-user

The stack

YOLOMMDetectionPyTorchRunPodAWS LambdaWebSocketsReactLaravel
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Use Cases

  • Drone-based roof and property inspection
  • Manufacturing quality control and defect detection
  • Agricultural crop monitoring and yield estimation
  • Retail inventory and shelf analysis
  • Construction site progress tracking

In practice

  • 01Built Aris Detect -- a full SaaS platform processing drone imagery for property inspectors, with ML-powered damage classification deployed on GPU infrastructure
  • 02Custom YOLO and MMDetection model training for domain-specific object detection
  • 03Serverless inference pipelines on AWS Lambda for cost-effective scaling
ALWAYS ON

AI Agents & Autonomous Systems

Systems that work while you sleep

Not chatbots -- real autonomous agents that monitor, decide, and act. Software systems that run 24/7, handling workflows that would otherwise require a human watching a screen.

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Use Cases

  • Automated bug triage and code review
  • Deployment pipeline management
  • Customer inquiry routing and response
  • Data processing and reporting automation
  • Continuous monitoring with intelligent escalation

In practice

  • 01AI agents that poll feedback systems, create Trello cards, auto-fix bugs, and submit PRs -- running autonomously around the clock
  • 02Discord-integrated assistants that handle research, scheduling, and wiki maintenance
  • 03Multi-agent teams that coordinate parallel development tasks

Machine Learning Engineering

From experiment to production

The gap

Between a working notebook and a production ML system is enormous. We bridge it.

GPU-native

RunPod, Lambda, AWS -- we deploy where your models actually need to run.

Full lifecycle

Training, evaluation, deployment, monitoring, retraining. Not just the fun parts.

The gap between a working notebook and a production ML system is enormous. We bridge it -- handling model training, GPU infrastructure, deployment pipelines, and the operational complexity that comes with running ML at scale.

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Use Cases

  • Custom model training for domain-specific tasks
  • GPU infrastructure setup and optimization (RunPod, Lambda, AWS)
  • MLOps pipeline design and implementation
  • Model evaluation, monitoring, and retraining workflows
  • Transfer learning and fine-tuning for specialized datasets

In practice

  • 01End-to-end MLOps pipelines with automated training, evaluation, and deployment
  • 02GPU inference servers on RunPod with Docker-based deployment and SSH access
  • 03Transformer and YOLO model fine-tuning for custom detection tasks

Business Process Automation

Stop paying humans to copy-paste

Most businesses have at least one process that a smart integration could eliminate entirely. We find those bottlenecks and build the automation.

What gets automated

  • Manual report generation from multiple data sources

    Automated pipelines that compile, format, and deliver

  • Copy-pasting data between platforms

    Webhook-driven pipelines with zero manual transfer

  • Waiting for someone to process incoming documents

    Instant PDF extraction, classification, and routing

Use Cases

  • Automated report and document generation
  • PDF processing and data extraction
  • Webhook pipelines connecting disparate systems
  • Real-time collaboration and notification systems
  • Email and communication workflow automation

In practice

  • 01Automated property inspection report generation from drone data, ML analysis, and inspector notes
  • 02Real-time WebSocket collaboration systems for multi-user workflows
  • 03Webhook-driven pipelines that eliminate manual data transfer between platforms
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