Company
AI agents for systematic trading.
Zeviq Technologies is an AI-native research and software company founded in 2026, headquartered in Prosper, Texas. We build AI agents, and the research platform they run on, for systematic trading across futures, equities, options, and perpetuals.
Our agents read research, turn ideas into testable hypotheses, and review code and results. Statistics decide what survives: out-of-sample validation, held-out evaluation, and nothing trusted until it has been measured.
AI supervises; deterministic code executes. Trading decisions and risk limits are designed to run in tested code that agents can halt but never loosen. Our data pipelines, knowledge system, and research infrastructure are built in-house.
- Founded
- 2026
- Headquarters
- Prosper, Texas
- Company
- Zeviq Technologies
- Address
- 2120 Prairie Dr Suite 1102 Prosper, TX 75078 United States
01 — Principles
What guides us.
01
Rigor
Every model is reproducible, every result defensible. We are skeptical of our own ideas before the market has a chance to be. No strategy reaches live trading without surviving rigorous statistical validation.
02
Evidence
We do not act on intuition or narratives. Every idea is a hypothesis tested against data: historical, then out-of-sample, then paper. The data is the final judge.
03
Patience
Durable edge takes time to find and longer to trust. We do not chase short-term performance at the expense of long-term consistency. Research that takes months to validate is research worth doing.
04
Precision
In quantitative trading, the details are the strategy. Execution quality, position sizing, risk controls, and model calibration all compound over time. We optimize every layer of the stack.
02 — How we work
Research. Engineering. Markets.
From hypothesis to validated strategy: a continuous loop of AI-assisted research, engineering, and markets.
01 — Research
Research with agents.
Agents search our knowledge base, propose hypotheses with their mechanism and pass criteria, and test them on historical data, then out-of-sample and paper trading.
02 — Engineering
Build the platform.
Data pipelines, a grounded knowledge system, backtesting and evaluation: the software agents and strategies run on, measured for accuracy and latency.
03 — Markets
Run with discipline.
Only strategies that pass validation will run, under hard risk limits enforced in code; live results will feed back into research.