Findings, obligations, and evidence — present and missing.
Map your AI systems, surface classification findings and the obligation areas that follow, then see which evidence you already have — and what is still missing — as systems, models and vendors change.
HRIA and FRIA support is built into the workflow where relevant — as modules, not as the whole product.
Powered by AEGIS™ — Daetis's traceable AI governance assessment engine.
AEGIS screening is not available while this panel is in construction. This is not a statutory classification or a conformity decision.
In construction
AEGIS is in construction
Screenings are turned off on this page. You can read the rest of the assessment overview. Starting or submitting a screening is not available.
Organisation-level governance. System-level findings and obligations.
One chain from inventory to evidence trail. AEGIS is the engine behind classification findings, obligation packs, evidence requests, and screening findings. This site does not invent legal outcomes.
AI inventory & role
Register systems and establish who operates, deploys, or provides them.
Classification & obligations
Surface classification findings and the obligation areas that follow from that role.
Risk, HRIA & FRIA
Run risk analysis and human-rights / fundamental-rights modules where they apply.
Controls, evidence & documentation
See which evidence is present and what is missing. Keep a trail that can be inspected.
Monitoring & reassessment
Revisit findings and evidence gaps as models, vendors, purposes, or context change.
How it works
From system facts to findings, obligations, and evidence gaps.
The public entry point is an initial AI Act assessment. Deeper evidence work, controls and monitoring live in the AEGIS workflow — not as a screening-then-consultancy funnel.
- 01
Add your AI systems
Describe purpose, context, vendor and model. Attach the documents you already have.
- 02
Surface findings, role and obligation areas
AEGIS reads the facts you supply and returns classification findings and obligation areas — including priority risks on the current engine.
- 03
See evidence present and missing
Work the gaps, information requests, and HRIA / FRIA modules where they are triggered.
- 04
Keep the evidence trail current as systems change
Revisit findings and missing evidence when models, vendors, or operating context shift.
Expertise
Built from real AI governance work.
AIHRIA is built by Daetis. Our work brings together human rights expertise, AI assessment methods, and practical training for the organisations building, deploying, and overseeing AI. Named institutions below describe method rehearsal — not endorsement.
UNDP
Assessment workflows for data protection authorities
Method rehearsal from work developing human rights impact assessment workflows with UNDP for data protection authority contexts — how we structure system review, not an endorsement.
Equinet
AI assessment for equality bodies
Method rehearsal from Equinet-commissioned training on AI profiling, discrimination, and assessment for equality bodies — connects technical evidence with investigation practice, not an endorsement.
From startups to government
Practical skills to assess AI
We train startups, companies, public institutions, and government officials to understand AI risks and apply assessment methods to real projects.
That experience shapes our approach to your project: understand the system, examine its effects on people, and turn findings into practical improvements.
Contact
Talk to Daetis
Use the AEGIS intake for an initial AI Act assessment, or send a short note if you need a conversation on inventory, evidence, or HRIA / FRIA modules.
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