Connect documents, data, AI models, Python and APIs in one workflow. Add human review where it matters, inspect every step, and run it again whenever you need to.
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. That’s the part that actually matters when the regulator asks questions.
QMerse sits between the information your business 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
Extract, analyse, calculate, compare and decide — step by step on the canvas
The workflow pauses for a person on the steps that matter
Structured data, reports, comparisons, alerts or processed documents
Start with the files, spreadsheets and APIs you already have. There is no data platform to stand up first.
Connect reusable components on a canvas and see the whole process at once, instead of reading it out of a script.
OpenAI, Anthropic, Azure or a local model, 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.
Pause a workflow so a person can review or approve an important step. The approval is part of the process, not a note in a handover document.
Open any step and see what it received, decided and passed on. Run history is kept, so you can show how a result was produced weeks later.
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.
Each one runs unattended, keeps its history, and hands back a finished result rather than a chat reply.
Finds comparable homes, runs the statistics to prove an over-appraisal, maps the evidence, then fills in the official Texas protest form.
Outcome: a completed, ready-to-submit form.
Screens the market every morning, applies your criteria, and appends the results to a dataset that grows with every run — flagging anything that looks wrong.
Outcome: a research dataset that builds itself.
One extraction across a whole folder of contracts, reports or applications — the same fields from every file, with exceptions ranked for a person to check.
Outcome: a consistent, traceable pass over the whole stack.
Export compatible pipelines as Python, keep your own model keys, and keep a full history of every run. Your workflow does not depend on us to keep running.
Need it inside your own environment? Private deployment is available through an assisted enterprise engagement — talk to us.
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, and runs the same way every time.
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.
