Studio + Labs · Blockchain · dApps · AI
ZIX DEV is a product studio and lab. We build DeFi protocols, dApps, and onchain systems — then push them further with secure AI agents and generative visual AI. Designed, built, and hardened until they hold up under real users and real money.
01 / focus
We go deep in three areas where most teams ship demos, not products. Each one is held to the same standard: safe to release, hard to break, and ready for real users.
01 — Visual AI
We build generative editing into real products — instant background and object edits, brand-consistent generation, and upscaling that keeps detail. Every output is commercially safe and carries content provenance, so your team publishes without second-guessing rights or authenticity.
02 — Agent Security
An agent that can move funds or call tools is an attack surface. We red-team agents against prompt injection, tool and MCP abuse, and memory poisoning — then ship runtime guardrails and continuous evals so they stay safe in production, not just on launch day.
03 — Onchain Systems
Protocols, full-stack dApps, and the data layer beneath them — engineered with the testing discipline the largest protocols depend on. Invariant tests, fuzzing, and external review before a dollar moves, plus the indexing and analytics your product and your models run on.
02 / why us
01
If it can't be shipped to real customers — rights-clean, licensed, provenance-tagged — we don't consider it finished.
02
Everything we build is red-teamed. We design for the prompt injection, the exploit, and the edge case before an attacker finds it.
03
Invariant tests, fuzzing, and independent review are non-negotiable. Nothing reaches production — or mainnet — unverified.
04
The people who scope your project build it. No junior bench, no offshore relay, no telephone game.
03 / approach
Every engagement runs through the same disciplined pipeline — from first whiteboard to live mainnet. Security, observability, and accountability are built into each phase, not bolted on at the end.
We open with constraints, not code — threat model, token and economic design, latency budgets, and the people who'll actually use the product. You leave this phase with a shared, written definition of done.
Deliverables
Contracts, data, and AI layers are designed as a single system. Trust boundaries, interfaces, and failure modes are mapped up front so nothing critical is improvised mid-build.
Deliverables
Senior engineers work in tight, test-driven increments. Every milestone is reviewable, runnable, and deployed to testnet — so progress is visible weekly, never quarterly.
Deliverables
Fuzzing, invariant testing, and independent review happen before any value is at risk. We remediate, re-test, and document every finding — so there are no surprises on mainnet.
Deliverables
A staged mainnet rollout with monitoring, alerting, and rollback paths in place from the first block. Launch is a rehearsed event, not a leap of faith.
Deliverables
Live dashboards, defined incident response, and a prioritized roadmap as usage and TVL grow. We stay accountable to the system long after launch day.
Deliverables
04 / model
[ studio ]
We embed with your team to design, build, and harden products end-to-end — from model and contract to the interface your users touch. Senior engineers, no hand-offs, accountable to the result.
[ labs ]
Between engagements we run our own R&D — testing attacks, tooling, and techniques across visual AI, agent security, and onchain. What we learn there goes straight back into every build we deliver.
05 / contact
Tell us what you're working on — a visual-AI feature, an agent you need hardened, or a protocol headed for mainnet. We'll come back with a clear, senior take on scope, risk, and timeline, usually within two business days.
