Anotics is a software company for the people who train AI. Today we ship a working AI assistant that gives annotators grounded, cited answers to real annotation questions, plus a full career layer: verified work history, real earnings, recovery when a platform removes you, and a community of other AI-work professionals.
We're deliberately early. The Ask assistant, career layer, and community work today. On-platform live assistance, adaptive suggestions, and a broader knowledge system that compounds across the community are the direction we're building toward — we frame them as vision, not as shipped product.
Platforms own accounts. We help people own their careers, and give them an honest, cited assistant they can actually trust.
Anotics brings together everything needed to support modern AI work in one intelligent platform.
For AI professionals, it provides career management, verified work history, earnings tracking, AI job discovery, skill development, and professional identity across every platform they work on.
For organizations, it transforms everyday annotation work into structured institutional knowledge. Every verified decision, guideline, discussion, correction, and edge case becomes part of a living intelligence system that can be searched, validated, improved, and reused.
At the heart of the platform is the Anotics Intelligence Graph (AIG), a knowledge operating system designed specifically for AI work. Rather than storing documents or isolated guidelines, AIG connects knowledge across people, projects, platforms, and time, allowing organizations to understand not only what decisions were made, but why they were made and how that knowledge should evolve.
The result is better training data, faster onboarding, stronger governance, and knowledge that becomes more valuable with every project.
As AI models consume more synthetic data, maintaining high-quality human expertise has become one of the industry's biggest challenges. Organizations need more than faster annotation — they need systems that preserve experience, improve decision-making, and prevent valuable knowledge from disappearing when projects end or teams change.
We believe AI work should create long-term intelligence, not temporary output.
Every annotation, review, correction, and discussion has value beyond the task itself. Capturing and connecting that knowledge creates an intelligence asset that improves future work, strengthens AI systems, and helps people build meaningful careers.
It combines universal knowledge storage, semantic search, collective intelligence, skill intelligence, confidence scoring, temporal reasoning, and evidence-based decision making into one continuously evolving knowledge system.
Every conclusion can be traced back to its evidence. Every recommendation includes context and confidence. Every improvement strengthens the system for everyone who uses it.
Data annotators, AI trainers, RLHF specialists, evaluators, quality reviewers, AI tutors, and every professional helping train modern AI systems.
Build your career, own your work history, discover opportunities, measure your expertise, and keep a permanent professional record that belongs to you.
AI labs, foundation model developers, enterprises, research institutions, annotation companies, and data operations teams.
Capture institutional knowledge, improve annotation quality, accelerate onboarding, strengthen governance, and create proprietary intelligence that compounds over time.
Developers, researchers, product teams, and anyone building systems that rely on trustworthy human knowledge.
Anotics helps transform AI work from a fragmented operational process into a continuously improving intelligence layer.
AI should amplify human judgment, not replace it. People remain responsible for every important decision.
Every project should leave an organization smarter than it was before.
Recommendations should always explain their reasoning, show their evidence, and communicate their confidence.
Platforms may manage work, but professionals should own their experience, reputation, and achievements.
Knowledge should be verifiable, auditable, and continuously improved through evidence, not assumptions.
Users remain in control of their own information. Organizations control their own institutional knowledge. Data is handled with security, transparency, and respect.
In the coming years, the most valuable organizations will not simply collect more data, they will build better knowledge.
Our vision is to make Anotics the operating system for AI work: the platform where human expertise is preserved, institutional knowledge continuously evolves, careers become portable, and every contribution makes future AI systems more capable, more trustworthy, and more useful.
