PRODUCTS
Commercial products
NowFlow, NeuraOS, and QFlow Studio are products we sell, each with a different job.
Research and innovation overview / for research partners
Neura Parse runs one applied robotics programme (NODERIQ), publishes quantum research (QANTIS, qmesh, QMANN), and keeps its engineering record public.
What is what
Saying exactly what stage each is at is part of the method.
PRODUCTS
NowFlow, NeuraOS, and QFlow Studio are products we sell, each with a different job.
PROGRAMME
NODERIQ is a research programme on robots working together, not a product yet.
RESEARCH + OSS
QANTIS, qmesh, QMANN, our datasets, and side projects are all public, with their tests and limits.
How we do research
Every project follows the same four steps, and each step has to be passed in order.
State the decision, the setting, the uncertainty, and the limits.
Set the classical or current method as the bar before testing a new one.
Run repeatable cases and record versions, routes, costs, and failures.
Stop, refine, keep watching, or promote, against agreed gates.
Applied research programme / NODERIQ
NODERIQ studies robot work orders that can be checked, a shared picture of the world that admits doubt, mixed fleets, human authority, and working without a cloud link.
Research programme working towards a product. Not a released product or field deployment.
NODERIQ / a robot work order
The proposed path matches the task to a capable machine, keeps the machine's own safety, records progress and completion, and can replay it all.
The goal, the test for done, the resources, the owner, and the safe stop.
The fleet manager, the robot, and its controller keep their own safety rules.
Progress, exceptions, human interventions, recovery, and proof of completion can be replayed.
NODERIQ / where quantum fits
We try quantum or quantum-inspired methods only on planning or estimation tasks that can wait and are never safety-critical.
The core must work with ordinary computers and without a constant cloud link.
Compare quality, uncertainty, run time, cost, repeatability, and fit for the job.
A good research result never widens what a safety-critical system may do.
Quantum decision research / QANTIS
QANTIS is our research on quantum-assisted decisions: planning when you are unsure of the state, and matching sensor tracks to targets.
Planning and acting stay on classical computers. The papers make no claim about total run time.
QANTIS / the two papers
The latest paper uses an IBM Heron processor for one step: updating a belief. Neura Parse's IBM Partner Plus membership is company-level only, not an endorsement.
Open-source infrastructure / qmesh
qmesh is an open-source layer that sits above Qiskit, Cirq, or PennyLane. It gives programs one typed format, schedules hybrid jobs, and signs the record.
Gate, neutral-atom, photonic, and pulse programs can share the same typed format.
Records are signed and hash-chained, so they can be verified offline.
Works with Qiskit, Cirq, and PennyLane. It does not replace them.
Open-source library / QMANN
QMANN is an open-source neural network library with a quantum memory layer. It estimates the cost before any paid hardware run.
THEORETICAL
Study the architecture on paper, with no qubit limit.
SIMULATION
Run the model with noise on a simulator, repeatably.
HARDWARE
See the cost estimate first, then run on IBM Quantum or IonQ.
Where our product helps / QFlow Studio
QFlow Studio, our web product, keeps the brief, the circuit, the generated code, the run, the results, and the reviewer's verdict in one place.
The visual circuit and its Qiskit, Cirq, or OpenQASM code stay linked.
Local simulators and real hardware routes are labelled by their status.
Assumptions, outputs, failed runs, limits, and the next decision are kept.
What is public
Datasets, code, tests, papers, and engineering notes are public, each with its status marked.
Hugging Face, CC-BY-4.0, as of 4 Jul 2026
Passing, open-source repository
Public on arXiv, 2026
TaskNebula, NeuraBar, OrbIDE preview
How to work with us
A paper, a pilot, and a consortium each end with a different kind of evidence.
Consortium design / any call
The same structure works for any funding call: name the real problem, assign the interfaces, test against baselines, and plan how results get used.
Describes the real setting, the decision, the constraints, and what success looks like.
Bring the models, workflows, devices, networks, quantum methods, and adapters.
Sets the tests, the safety and security limits, human factors, and review criteria.
Owns IP, data rights, the path to a product, standards, papers, and the route to market.
Next step
We will pick the right project to work in, agree what evidence the result needs, and keep research, programme, and product claims separate.
qflow.studio / github.com/neuraparse