Real teams. Real outcomes.

A consumer AI startup needed real-time voice-to-voice conversation with emotionally adaptive 3D avatars and persistent memory. Initial architecture had 15-30 second response delays. Streaming, memory filtering, and GPU constraints all blocked the sub-second target.

4-person AI crew. Parallelized memory, LLM inference, and TTS into a ZeroMQ microservice pipeline. Quantized 34B model to 4-bit. Built custom speech recognition with per-user pause detection. Shipped cross-platform on Unreal Engine.

A recruitment-tech company needed one system to launch, track, and sync hiring campaigns across 10+ advertising platforms - each with different APIs, targeting formats, and rate limits. Manual workflows couldn't scale. Data was inconsistent and reporting was unreliable.

Crew built a centralized orchestration layer - single campaign input deploys across all platforms simultaneously. Algorithmic data normalization handles cross-platform inconsistencies. Hybrid sync system combines batch processing with real-time recovery to work within API rate limits.

An infrastructure inspection company needed to process massive 360° imagery datasets synchronized with LiDAR point clouds and ESRI maps. Proprietary tools were costly, lacked LiDAR support, and couldn't handle scale. Processing 10K images took ~24 hours. Uploads over 500GB failed regularly.

Crew built an event-driven pipeline - chunked uploads, FFmpeg stitching, overlap deduplication, tiled LiDAR denoising, and unified timeline synchronization. Auto-scaling GPU burst processing replaced long single-thread runs. Delivered through a single-link browser viewer with synchronized imagery, LiDAR, and ESRI overlays.

A scuba hardware company's companion app was killing device sales. It crashed 5x daily, destroyed dive photos, and developers refused to touch the codebase. The hardware was solid but the software - the soul of the product experience - was a liability.

Crew ran a full 1.5-year rebuild with 5-6 member crew. AI-powered post-capture pipeline for deblurring, recoloring, and upscaling. Depth-adaptive UI tested for visibility at 80 meters. Built-in decompression safety timers. Self-guided onboarding for non-expert divers

A Danish edtech startup needed a system that creates noise-free learning environments for students with ADHD, autism, and concentration difficulties. The core technical problem: connecting multiple headphones to a single teacher microphone with zero perceptible latency and real-time noise cancellation.

Crew solved multi-device connectivity through OS-level multi-threading for audio broadcasting. Optimized bit rates and packet sizes to eliminate latency. Integrated RNNoise for real-time noise cancellation at the sender's end. Shipped a teacher-facing touch screen interface for per-student control.