Infinity Neural
Software Architect & Tech Lead · 2017 – 2024
Nearly seven years building the Computer Vision core of Infinity Neural: from developer and architect to the team’s Tech Lead. Real-time computer-vision systems —crowd counting, tracking, access analytics— taken from R&D to a homologated product deployed in production at scale for enterprise clients.
- 250+ servers in production
- 6,5 years (2017–2024)
- 6 people on the team
- >99% homologated accuracy (CEM)
Clients
- Fira Barcelona (MWC)
- IFEMA
- Renfe
- Coca-Cola
- Acciona
- Abertis
- PortAventura
- Casino de Barcelona
- San Fermines (Pamplona)
- Aeropuerto de Barcelona – El Prat
- FGC
- Tech Lead & Software Architect Jul 2022 – Apr 2024 · Full-time
I led the production rollout of a Computer Vision system across 200+ servers, plus the team’s technical leadership, architecture, scaling and monitoring.
- Software Architect & Computer Vision Developer Nov 2017 – Jul 2022 · Full-time
Architecture and development of the Computer Vision core: real-time computer vision systems for object detection and tracking.
Projects
Remote diagnosis & repair MCP
Remote diagnosis & repair MCP
An MCP that navigates the 250+ server ecosystem to diagnose and fix remote incidents with the power of LLMs.
- The problem
- Diagnosing and fixing incidents across a 250+ server ecosystem where many resources are only reachable by hopping through the network: cameras accessible only from their remote server, and local databases with temporary data on each server.
- Stack decision
- An MCP (Model Context Protocol) that exposes tools to the LLM to navigate the network of servers and load balancers, inspect remote servers and cameras, query the local databases and apply fixes, on top of the video-analytics ecosystem’s 443 reverse-proxy/load-balancing architecture.
- The technical challenge
- Reaching deeply nested resources (cameras and local DBs only accessible by hopping server to server through the load balancers) and exposing that navigation as reliable tools so the LLM can diagnose and repair autonomously.
- Impact
- Monitoring and diagnosis of a 250+ server production ecosystem, speeding up the resolution of errors on remote servers and cameras.
Crowd-counting system
Crowd-counting system
The first crowd-counting system homologated by the Spanish Metrology Center, with >99% accuracy and real-time multi-camera fusion.
- The problem
- Certifiably accurate crowd counting in massive venues (trade fairs, casinos, street festivals), where a single camera can’t cover wide entrances and overlap between cameras causes double counting.
- Stack decision
- Python prototype (YOLOv2 + a custom tracking algorithm) rewritten in C++ with CUDA to scale performance; multithreading to process many cameras on a single GPU.
- The technical challenge
- Fusing and synchronizing up to 12 aligned cameras in real time into a single view where analytics run, with fine overlap configuration so the same person is never counted twice.
- Impact
- Over 99% accuracy homologated by the Spanish Metrology Center — the first certified counting system. Robust with up to 200 people under a single camera (San Fermín festival).
Access & platform analytics — Renfe
Access & platform analytics — Renfe
Turnstile counting, fraud detection and platform occupancy deployed across the entire Renfe network.
- The problem
- Monitoring accesses and platforms across an entire rail network: turnstile counting, fraud (two people at once, jumping the gate), people carrying objects, track intrusions and occupancy.
- Impact
- Deployed across the whole Renfe network and periodically audited by the client, recurrently validating its accuracy.