Most AI today
A better guesser
AI works each job out from scratch on every run. Newer models guess better, but each run is still a fresh guess, and small misses add up.
Your team checks every line.
Platform
Nexhelm sits on top of the systems you already run and hands back finished work: the deliverable, the list of anything that didn't fit, and the trail behind every figure.
What arrives
Choose a part to see what lands on your side after each run.
The packet, report or file your team would otherwise assemble by hand, built from the systems it draws on and delivered where you already work.
Sample data.
Anything outside what your team approved is set aside with a reason and an owner, so it surfaces before the work goes out.
Each number in the deliverable points back to the record it came from, so review starts from the source.
Custodians, CRM, documents and portals stay as they are. Nexhelm connects with the access you grant, and works with any AI model, so a better model makes the service better without changing your setup.
From reliability to certainty
AI does the work. Nexhelm makes it certain, by checking every run against the answer your firm already approved.
Most AI today
AI works each job out from scratch on every run. Newer models guess better, but each run is still a fresh guess, and small misses add up.
Your team checks every line.
Nexhelm
AI does the job. Nexhelm holds it to a result your firm already signed off on, ties every figure to the source your firm trusts, and checks each run against it.
Your team reviews what's flagged, then signs off.
See it on one day of trades
Each line is one figure in your deliverable; the dot shows which system it came from. Sample data.
You check every line.
The dots move because each run picks its own source.
You review what's flagged, then sign off.
Stop paying people to check the AI.
Technology
Nexhelm sits above whichever AI model is best today and holds it to what your firm decided correct looks like. The model does the work; the protocol decides what counts as done.
Your operators define the result the workflow has to produce. The run is bounded by that definition: it cannot quietly decide for itself what good enough means.
Nothing is trained on your data and nothing is tuned to one task. Each step routes to the cheapest model that still passes, so every model release makes the service better without a migration.
Building this in-house against a frontier model means ten or twenty rounds of iteration to find the process. The protocol absorbs your procedures and converges in one, which is where the time and the token cost go.
The workflow runs against your systems with the access you grant, and can run entirely inside your own environment. We do not need to hold your domain knowledge for it to work.
Same inputs, same approved result, every run.
Who does what
How Nexhelm compares
Already use a copilot? Keep it. Nexhelm works alongside it and hands back finished work.
| What you get | CopilotsDraft and suggest | AI agentsDo tasks, unverified | Scripted automationRepeats scripted clicks | NexhelmFinished, checked work |
|---|---|---|---|---|
| Does the whole job | No | Partly | Partly | Yes |
| Checked against your records | No | Grades itself | No | Every figure |
| Runs the same way every time | No | No | Until something changes | Yes |
| Tells you what doesn't fit | No | Not reliably | Breaks when things change | Flags it |
| What your team reviews | Every draft | Every output | Every break | The exceptions, then signs off |
Integrations
CRM, custodians, documents, calendars and email, wired in with no rip-and-replace.

See how it runs with an answer key, on a call with the people who build it.