Invisible Technologies
Combines a large expert workforce with software to produce the human feedback frontier labs train on.
Highlights
- Expert human-feedback (RLHF) and preference data for aligning large language models
- Model evaluation and red-teaming with domain specialists across coding, science, and finance
- Post-training and fine-tuning data pipelines for foundation-model providers
- Agentic process automation that combines AI agents with human-in-the-loop review
- A modular platform spanning data infrastructure, workflow mapping, annotation, and automation
- A vetted global workforce of specialists managed through the company's orchestration software
- Enterprise operations delivery for back-office and customer workflows at scale
- Custom engagements for regulated industries with managed quality and oversight
External link — opens invisibletech.ai in a new tab. Invisible Technologies is a third-party product; we are not affiliated with it.
About Invisible Technologies
What it is
Invisible Technologies supplies training data and AI operations, pairing a large expert workforce with software to produce the human feedback, evaluation and post-training data that frontier labs use. It also runs process automation for enterprises, applying the same combination of people and tooling to business operations.
Why it's different
The interesting claim is the blend rather than either half. Pure crowd work cannot produce expert judgement; pure automation cannot produce judgement at all; the useful unit is a trained person with good tooling, managed as a process. Invisible operates that at scale, which is why frontier labs use it. The thing to understand about this category generally is that the quality of models you use daily rests substantially on work like this, done by people, and that the labour conditions of that workforce are a live and under-examined issue across the whole sector. As a directory listing, it is a service engagement rather than a product.
How people use it
It is relevant to organisations training or fine-tuning models who need domain-expert data they cannot produce internally, and to enterprises wanting a process run rather than a tool supplied. For most readers it is context: when a model is reliably good at something specific, a managed human data operation is usually part of the explanation, and knowing that layer exists makes the capability claims easier to read.
Written by the n3os team. We are not affiliated with Invisible Technologies.
This listing was written from public information, without Invisible Technologies’s involvement. If you own it and something here is wrong — or you would rather not be listed at all — email us and we will correct or remove it.
Get the ones worth knowing about
We write one of these for every tool worth the trouble. Get the new ones, plus what we have found genuinely useful lately.
Your address goes to Buttondown, who send the emails on our behalf. One click unsubscribes, and the list is never sold or shared.