My AI prototype works. Now what?
Most AI projects die between prototype and production — stuck on data pipelines, unreliable outputs, and scale.
Altiv Labs treats that gap as an engineering problem, and closes it.
Two minutes. One URL. No sales call.
Trusted by teams across Brazil, Spain, the UK, Canada and Qatar
FROM PROTOTYPE TO PRODUCTION
Build it.Feed it.Deploy it.Monitor it.
A four-stage delivery loop: build, feed, deploy, monitor — then back to build.
Multi-agent AI systems
Turn your concept or prototype into scalable, secure, production-grade AI. Orchestrated agent pipelines with guardrails, monitoring, and cost tracking.
Data enrichment & ML
Clean, connect, and activate your data for AI-ready decision making. Automated pipelines that turn raw data into intelligence.
Cloud & edge deployment
Ship to production on AWS, or deploy AI where the data lives — factory floors, vehicles, remote sites. Cloud infrastructure or offline-resilient edge inference.
Observability & evals
Watch quality, latency, and cost once the system is live. Traces, evals, and drift alerts tell you what to fix — and feed the next build.
HOW WE'RE ORGANIZED
The hard problems others walk away from — we engineer through them.
Complex AI architectures, constrained edge hardware, demanding RF specs — our senior engineers combine deep agentic AI expertise with hands-on hardware capability to tackle the challenges that exceed what a single discipline can solve.
Engineered outcomes
Production systems we've helped engineer
Visual QA for PCB manufacturing
A tier-1 European electronics OEM runs our inspection models at the edge, trained on their own line data and wired into the existing MES.
Accounting automation over WhatsApp
Multi-agent pipeline for a regional services firm: LLM extraction, ERP reconciliation, approvals in WhatsApp. Every action logged.
AI exhibit guide for museum visitors
Built in partnership with IBM: visitors ask about the work in front of them and get a grounded answer in their own language. Recognised with a Cannes Lions and a D&AD Impact award.
Our stack
Engineered on foundations that hold up in production
Latest insights
From our engineering team
on-premiseShipping a React app as a Windows MSI, database included
How we package a full-stack web app: React frontend, Node backend, PostgreSQL included, into self-contained Windows MSI and Linux .deb installers that run fully offline, survive upgrades without losing data, and build automatically in CI.
hardwareRF Filter Design for ESP32-S3, Part 1: The Ideal Filter and First Layout
An ESP32-S3 RF filter that passes simulation can still fail on the fabricated board. Part 1 of this series builds the foundation: a CLC PI filter designed in CST Studio Suite, optimized with CMA-ES across the 2.4 GHz Wi-Fi channels, and carried into a controlled-impedance Altium layout.
deep learningIndoor Positioning with Deep Learning: Turning Beacon Signals into Coordinates
How we taught a neural network to pinpoint people indoors from Bluetooth beacon signals. GANs and RNNs failed; a simple regression network with a Euclidean-distance loss got us to ~1.5 m accuracy — proof that feature engineering beats model sophistication.
Ready when you are
Your prototype is waiting to become a product.
The free AI Opportunity Scan maps what AI could unlock in your business — and what it will actually take to ship it.