Build workflows visually, connect AI to your data and tools, and review results at the steps you choose. Explore the online sandbox, then talk to us about deploying QMerse on your own infrastructure.
Your expertise. Your AI. Your control.
“Grid compliance work used to mean weeks of manual assembly just to produce something defensible. QMerse cut that down and kept the audit trail intact.”
Dr Yousef Pipelzadeh — Founder & CEO, Velon Energy
Pick a stop to see that part of the app up close, or let the tour play through them.
Explore the visual builder, try example workflows and test your ideas before discussing a deployment. The sandbox is a shared environment with usage and capability limits.
Discuss deploying QMerse within your organisation’s infrastructure. Together, we define the model setup, integrations, compute requirements and support needed for your workflows.
You decide the process, what the AI may do on its own, and where a person reviews before the workflow continues.
Connect your data, tools, AI agents and Python logic in a visual workflow.
Review inputs, outputs and tool activity to understand how a result was produced.
Configure approval steps so selected actions wait for a person to review them.
Save proven workflows and adapt them to the next task, dataset or project.
In the online sandbox: all four. With an on-premises deployment: the same, running on your infrastructure with your own Python packages, larger files, integrations scoped to your systems, and shared workspaces for your team. Compare the two
Engineering analysis, document review and recurring monitoring: what goes in, what QMerse does, where you review, and what comes out.
See all use casesQMerse sits between the information your organisation already has and the decisions someone has to make about it. A process done by hand becomes one you can run again, inspect, and hand to someone else.
Documents, spreadsheets, databases, APIs and business tools. There is no data platform to stand up first.
Extract, analyse, calculate, compare and decide, step by step, with agents, Python and the tools you already run.
Configure approval steps where human review is required. The workflow pauses there and continues once a person approves.
Structured data, reports, comparisons, alerts or processed documents. Reuse a defined process across repeated runs, and review each run’s output.
Wire documents, data, models and code together on one canvas, then reuse what works on the next project.
Connect reusable components on a canvas and see the whole process at once, instead of reading it out of a script.
Connect supported cloud and local models, such as OpenAI, Anthropic and Azure, with your own API key. We do not mark up inference.
Drop into Python for logic that must be exact, and call the systems your business already runs on, all in the same workflow.
Start from a template that already runs, then save your own and apply it to the next project, dataset or client instead of rebuilding it.
Export compatible workflows as Python for execution outside QMerse, subject to their dependencies. Keep your own model keys and a history of your runs.
QMerse is built around a job, not an industry: work that depends on someone’s judgement, turned into a workflow you can run again and inspect step by step.
Our missionTo empower domain experts to put AI to work while retaining control over their knowledge, processes and decisions.
ChatGPT and Claude give you the model. QMerse gives you the system around it: the workflow that combines AI with your data, tools, code, rules and human approvals, so you can reuse a defined process across repeated runs.
n8n is strong at connecting applications. QMerse is built for workflows where the hard part is the decision: read the data, run the calculation, have agents interpret it, validate the result, and put it in front of a person. n8n can call a QMerse workflow over a webhook.
No. Domain experts, engineers and analysts build workflows from existing components. Technical users can go further with Python, APIs, custom tools and their own models.
Yes. Zapwiser, the team behind QMerse, can identify, design and implement your first production workflow, then hand it over to your team. How the two fit together.
Try ideas in the online sandbox, then talk to us about deploying QMerse on your own infrastructure.
Want someone to build it for you?Work with Zapwiser ↗
