ProductivIA is not a product assembled once and for all, or a simple resale of APIs. It is an active, permanent research project: a platform that works 24 hours a day to produce, verify and maintain the material that gives it intelligence. While you use it, dozens of AI agents collaborate continuously: they evaluate models, build knowledge bases, observe the world and review one another. That is what allows the intelligence you use to remain lucid, cultivated and synchronized with reality.
Three major workstreams run without interruption. Here they are.
A platform that works for you, permanently
Continuous multi-AI orchestration, at the very heart of the platform.
At the core of ProductivIA, Matania continuously orchestrates AI agent chains that produce benchmarks, scientific images, news bulletins, podcasts and knowledge cards that feed the whole platform. No manual action. No copy-paste. Truly industrial multi-AI, triggered, verified and enriched on its own, under human supervision.
1. Understand AIs to orchestrate them better
Before entrusting a task to a model, you need to know what it is worth. We do not simply believe provider spec sheets: we measure, compare and make AIs debate each other. These lessons feed Matania's routing rules directly, so the right intelligence is called for the right task.
Concrete result: Matania knows precisely which model to call for which type of task, and routing policies evolve with the lessons collected.
2. Build knowledge
Multilingual, multicultural, scientifically verified, by an AI committee.
AI is only as strong as the material it feeds on. Instead of depending only on existing corpora, we actively manufacture knowledge: visual, scientific, multilingual. Every image and every text produced in our bases is validated by a scientific committee composed of four vision AIs (GPT, Claude, Grok, Gemini), with Matania synthesizing and making the final arbitration. This is AI-assisted research, at scale.
A living encyclopedia serving general culture, education and educational content creation: owned by the ecosystem, independent from major platforms.
3. Observe the real world
So Matania and the agents remain synchronized with the pulse of daily life.
For AI to be useful to an individual, a business or an institution, it must live in the present, not in a frozen training snapshot from two years ago. We observe the world continuously, and these observations directly feed Matania and every application on the platform.
When you ask the Assistant what is happening in Rimouski today, or the key figures for your municipality, or the economic portrait of a region, you draw on this continuous observation, not on a model guess.
A virtuous loop
Each workstream feeds the others.
The three pillars are not three islands: they form a knowledge loop. Benchmarks refine routing, routing improves the quality of scientific committees, committees enrich knowledge bases, and knowledge bases plus real-world observations make the Assistant genuinely useful in your daily life. Matania orchestrates. The ecosystem learns. The platform grows by itself, always under human oversight and direction.