We're researching how AI can improve decision-making in financial markets. MatriQs is where that research lives — tools we build, run in real conditions, and keep refining based on what we learn.
TigeniQ, MatriQs, and FIP each came out of a specific problem we ran into. We're still working on all three.
We're exploring how far natural language can go as a trading interface — placing orders, setting alerts, managing risk through a conversation. TigeniQ is where we test that idea in practice.
The execution layer. We use it to run automated strategies — DCA, trailing stops, multi-exchange logic — and learn what actually holds up when markets don't cooperate.
Our signal research engine. It combines technical indicators, macro data, funding rates, and news sentiment into a single score. We're continuously testing how AI can improve what that score means in practice.
FIP's Master Signal is something we've refined over time by watching where it was wrong. We adjust the weighting, test the output against real market behavior, and keep improving. It's not finished — that's kind of the point.
We're running TigeniQ in real environments, not demos. That means dealing with edge cases, unexpected behavior, and moments where the AI gets it wrong. Those moments are where the actual research happens.
Before any order goes through, the framework checks balance, symbol validity, and exchange status. That part doesn't change regardless of how experimental everything else gets.
When FIP detects an unusual deviation in funding rates or price action, we don't just flag it — we look into it. Understanding why markets move in unexpected ways is part of what makes the whole system better over time.
Most trading signals look at one thing and call it done. FIP takes a different approach — it pulls data from multiple independent layers, weighs them according to their historical predictive value, and synthesizes everything into a single, explainable score.
The result isn't just a buy or sell indicator. It's a structured view of where the market is, what the macro backdrop looks like, how the crowd is positioned, and where the risks are — updated continuously, 24 hours a day.
Connected to the most relevant blockchains, DEX protocols, and centralized exchanges — through one unified interface.
We didn't design these tools from theory. They came out of actual trading, real losses, and the kind of questions that only come up when money is on the line.
There's a difference between tools designed in theory and tools that have been tested against live markets. Everything in our ecosystem has been run, broken, fixed, and run again.
The scoring model behind FIP has been adjusted repeatedly based on where it got things wrong. What you see is the result of that process — not a first draft.
Automated strategies and natural language commands mean you spend less time wrestling with interfaces during fast moves. The tools handle the mechanical side. You handle the judgment.
Position limits, stop conditions, and order validation are built into the framework level. They run independently of whatever else we're testing — that separation is intentional.
Right now, we're onboarding our first testers and users exclusively through personal referrals. We're keeping things small on purpose — quality over quantity. If someone sent you here, or you think you'd be a great fit, we'd love to hear from you.
Angaben gemäß § 5 DDG
Shahram Vahedi
Fineknweg 1
91085 Weisendorf
Deutschland
E-Mail: info@matriqs.de