Build.
Custom tools and AI automations for everyday tasks.
AI fluency
where it matters.
The way we work is being rewritten. What’s your next move?
We build practical tools and work alongside leaders and individuals to put AI to work, strengthen their skills, and use technology they feel confident with.
Human expertise.
superintelligence alongside it.
Build / Protect / Clean / TeachStart with the work
The starting point
You know your work.
Make AI work for you.
Your people know the work: the contracts, the cases, the records and the numbers. Using AI should build on that expertise, without requiring them to become AI specialists. The tools should fit their work, and they should feel confident using them.
Your expertise. More possibilities with AI.
What we do
We bring the engineering
to where the work happens.
We don’t deliver a report and leave, or charge you for seats no one uses. We work alongside the people doing the job until the tools we build become a useful part of their day.
Protect.
Control what data your team shares with AI tools.
Clean.
Fix inconsistent records and prepare data for use.
Teach.
Practical AI training, one to one or in small groups.
One team for all of it. The person who builds your automation is the same person who makes sure your staff can use it.
How we work
From a useful idea to everyday use.
- 01
Understand the work.
We learn how your team works and where they need support.
- 02
Pick a starting point.
Together, we choose a task worth improving.
- 03
Build and test.
We agree what good results look like, then build and test with your team.
- 04
Put it to work.
We support rollout, train your team and check what’s working.
Who it is for
For people who work
with data that matters.
Regulated industries.
Where a wrong paste is a compliance problem, and every tool must be explained before it is trusted.
Human data teams.
For teams working on annotation, AI evaluation and data quality, where human judgement shapes how systems perform.
Freelancers.
Where one person is the analyst and the engineer, and needs tools that respect that.
Data lovers.
Where opening an unfamiliar data structures is the fun part.
Our own tool Beta
Parser.
Understand messy
data in seconds.
Paste or open anything: logs, exports, API responses, old formats and new ones mixed together. Parser shows you the structure inside, so you can read it, search it, compare it and share what matters.
Available for free. Beta.
ONE RECORD. YOUR WAYS TO READ IT
{"record":"0042","status":"ready",
"items":[{"type":"report","count":3}]}
Structure comes into view
- record
- 0042
- status
- ready
- items
- 1 item
- type
- report
- count
- 3
ILLUSTRATIVE DATA Parser by Paraneuron
Old formats and new, in one view.
Legacy records and modern structured data, nested inside each other, opened layer by layer. Nothing is dropped or changed in silence. Every transformation Parser makes is shown to you.
Built for the person who knows if the answer is right.
Not only for the engineer who built the system. It works on a phone as well as on a desk.
We never receive your data.
Parser does its work in your browser. What you open is not sent to us. It leaves your device only if you choose to send it: by connecting your own AI provider, or by exporting a file.
Team and Enterprise editions are on the way.
Custom templates, shared workspaces and controls for larger teams. Leave your email and we will write once, when they are ready.
Services, shaped around your project
The right help.
For the work ahead.
From data and AI evaluation to websites and visual design. We agree the scope, the expertise needed and what a useful result looks like before work starts.
01 / Human judgement, made useful
Better data.
Clearer evaluation.
Design annotation and review workflows that give people consistent criteria and turn their judgements into useful feedback for AI systems.
A project can include
- Annotation guidelines and evaluation rubrics
- Human review, quality checks and disagreement handling
- Structured feedback across large sets of data points
A useful starting pointA dataset, an evaluation task or a review process that needs consistency.
02 / Data you can work with
Make inconsistent
data usable.
Prepare records for analysis, migration or AI use. Define what needs correcting, what should stay untouched and how changes will be checked.
A project can include
- Format alignment, field mapping and duplicate checks
- Missing-value and consistency reviews
- Validation rules and a record of changes
A useful starting pointA sample of the data and an explanation of what it needs to support.
03 / Your work, online
A website with
a clear purpose.
Create a business website, product page or small web tool around what visitors need to understand and do.
A project can include
- Page structure, interface design and development
- Responsive layouts and useful interactions
- Deployment and an agreed maintenance handover
A useful starting pointYour audience, the content you have and the action you want visitors to take.
04 / Give the idea a clear form
Visuals that explain
and belong together.
Develop visual material for your brand, product or communications, with a consistent style and files suited to where they will be used.
A project can include
- Brand graphics and visual guidelines
- Illustrations, diagrams and presentation assets
- Reusable design files and agreed export formats
A useful starting pointThe message, the audience and a few examples of the direction you have in mind.
05 / Test beyond the expected path
Find where an
AI system falls short.
Adversarial LLM testing and red teaming within an agreed, authorised scope. Examine how the system behaves under difficult inputs, conflicting instructions and misuse attempts.
A project can include
- Task-specific adversarial scenarios and evaluation criteria
- Prompt-injection, data-exposure and tool-use checks
- Reproducible findings, prioritised fixes and retesting
A useful starting pointThe system, its intended use, permitted test boundaries and the failures that matter most.
06 / Start with the underlying problem
Some gaps need
more than a model.
We identify costly gaps in established industries and workflows that generative AI brings into focus, but a generic model alone cannot fix. Then we define what needs to change in the process, data or tools.
A project can include
- A map of bottlenecks, handoffs and avoidable costs
- An assessment of where AI fits and where it does not
- A scoped pilot with requirements and success criteria
A useful starting pointA recurring cost, delay or quality problem that existing tools have not resolved.
Bring us the problem
Tell us what you are trying to achieve, what is getting in the way and the constraints we need to work within. We will work with you to define the right approach.
Why trust us
Careful
by design.
Your data stays yours.
In our tool by construction. In our services by contract.
Plain language.
If we cannot explain it to the person who will use it, we have not finished.
Nothing hidden.
We make the architecture of the systems we build inspectable, from frontier algorithmic testing to AI in everyday business operations.
Built to be checked.
We build tools to review data points at scale, flag problems and turn human feedback into improvements.
We say no.
If AI is the wrong answer for a task, we tell you.
About Paraneuron
Who we are.
Paraneuron is a small engineering company with a team spread around the world. We build our own software, so we know what it takes to make a tool people trust with sensitive data. We bring the same standard into your organisation.
Let’s work on something useful
Start with
one task.
Tell us about the task that takes the most of your team's week. We will tell you honestly whether AI can help, and how.
Talk to us
info@paraneuron.com
We reply within one working day.